US20070192254A1

US20070192254A1 - Multi-processing financial transaction processing system

Info

Publication number: US20070192254A1
Application number: US11/689,219
Authority: US
Inventors: William Hinkle
Original assignee: N_GINE LLC
Current assignee: N_GINE LLC
Priority date: 1997-10-29
Filing date: 2007-03-21
Publication date: 2007-08-16
Also published as: US6904411B2; WO1999022329A1; US6442533B1; US20050165668A1; US20020138376A1; AU1126399A

Abstract

A financial transaction processing system is disclosed, wherein substantial processing efficiencies are provided with, additionally, a substantial decrease in the size of the executable code. Each transaction processed by the transaction processing system is described by a transaction data descriptor that includes a series of subtransaction data descriptions of actions that can be performed independently of one another. Thus, complex transaction processing logic is substantially removed from the executable code, and instead such transaction data descriptors are processed interpretatively. Moreover, the independence of the subtransactions allows the subtransactions of a transaction to be processed in parallel when performed on a multiprocessor computer. Additionally, the transaction processing system provides account balancing enhancements in that there are control columns in various data tables that are automatically updated during transaction processing so that by comparing control column totals, an indication of the integrity of current financial records is provided. Additionally, the transaction processing system provides full auditability in that any changes to financial data can be traced for any effective period of time into the past so that auditors can periodically perform a full audit of the financial transaction data retained by the transaction processing system.

Description

FIELD OF THE INVENTION

The present invention relates to a financial transaction processing system, and in particular, to such a system that is capable of decomposing transactions into subtransactions and multi-processing subtransactions simultaneously.

BACKGROUND OF THE INVENTION

Computerized data processing systems for processing financial transactions have become increasingly more complex as further strides toward automation have occurred. Such complexity has generated a number of related difficulties for the financial data processing industry. In particular, complex financial transaction processing systems may have subtle programming defects or errors that may go unnoticed for long periods of time before the extent of the problems thereby generated are fully recognized. For example, the number of positions allotted for the dating of transactions has recently been problematic, wherein the dates for the millennium starting at the year 2000 can be problematic for many financial transaction processing systems.
In addition, such complex financial transaction processing systems also are typically incapable of being fully audited. That is, it is common practice in the financial data processing industry to provide only partial auditability in that it is generally believed that the amount of data required to be stored for full auditability is so large as to not be cost effective.
Further, in many circumstances, the rate of transaction increase is becoming problematic in that progressively larger computers are required for processing financial transactions at an acceptable rate. This problem is exacerbated by the fact that such transaction processing systems are not architected for use on multi-processing machines having a plurality of processors. Thus, the advantages of parallel-processing computers cannot be fully utilized by such systems.
Accordingly, it would be advantageous to have a financial transaction processing system that alleviates the above difficulties, and that additionally, provides flexibility to adapt to the changing business needs of business enterprises so that the transactions processed and the respective reports generated may be modified easily according to business constraints and demands.

SUMMARY OF THE INVENTION

The present invention is a financial transaction processing system that achieves substantial increases in auditability and processing efficiency. In particular, the present invention provides auditable trails or history in a number of different ways. For example, financial data within transactions is used in the present invention to update various control fields in different tables or files so that cross-checks of system financial integrity can be performed for assuring that, for example, cash fields, total units fields, and cost fields balance appropriately across system data tables provided by the present invention. Additionally, the present invention provides a full range of auditable history files for each system data table having information that is required during auditing.
The present invention also performs financial transaction processing using a novel computational paradigm. That is, the financial transaction processing system of the present invention has an architecture wherein financial transactions can be decomposed into corresponding collections of independent subtransactions, such that for each input transaction, the corresponding collection of subtransactions are performed by operations that are independent of one another. Thus, the subtransactions can be performed in any order, including in an overlapping fashion, such as may occur during multiprocessing of these subtransactions on a computer having multiple processors.
Further, note that each of the subtransactions is described by a relatively short (e.g., less than 8 characters) text string that can be straightforwardly interpreted as an operation (e.g., either plus or minus) together with a series of operands, in particular, a first operand having a value to be used in modifying a data table field (column) specified by a second operand. Such high level descriptions of subtransactions provide both compact conceptualization and a reduction in the total size of the executable code for the present invention. Accordingly, when one of the subtransactions is performed, not only is its corresponding operation performed on the operands, but additionally, control fields such as those mentioned above are updated appropriately in various data tables for the present invention to enhance auditability of the financial data resulting from the transaction processing. Further, note that since the subtrarisactions are independent of one another and their executable code is relatively small, there is no need for lengthy and complex flow of control transaction processing modules. That is, the size of the code for the present invention may be up to 100 times smaller than many prior art transaction processing systems. Accordingly, this has a substantial positive impact on the efficiency of the present invention in that the swapping of program elements in and out of primary computer memory is substantially reduced.
In another aspect of the present invention, the financial transactions of a plurality of business enterprises can be processed in an interleaved manner. In particular, since the present invention is substantially data driven, including the descriptions of the transactions and their related subtransactions, the present invention can be easily modified to incorporate both different or updated versions of transactions and associated data tables for an existing business enterprise (e.g., also denoted “licensee” hereinafter). Additionally, the transactions and related data tables for an entirely new or different business enterprise (licensee) may be straightforwardly incorporated into the present invention so that its transactions can be interleaved with the transactions of other business enterprises. Thus, transaction processing may be performed by the present invention for business enterprises having different transactions, different account record structures and differently organized general ledgers substantially without modifying the program elements of the transaction processing system.
For example, the present invention can be used to simultaneously process transactions for:

- (1) a single software application such as an investment management or telecommunications billing system,
- (2) multiple disparate software applications such as investment management, and ‘telecommunications’ billing, paying agencies, etc., all with disparate definitions.

Accordingly, the present invention may be viewed as a software engine, or a user-definable transaction processing tool that can be adapted to a variety of industry specific software application needs without changing the actual program code. That is, by surrounding the present invention with application specific software for inputting transaction data to the multi-processing financial transaction processor of the present invention and retrieving data from the multi-processing financial transaction processor of the present invention, a particular business enterprise can have substantially all of its financial records in condition for auditing on a daily or weekly basis.
The present invention may be further characterized along the following dimensions: flexibility, auditability, multiprocessing, efficiency and size, these dimensions being discussed, in turn, hereinbelow.
Flexibility is achieved by permitting a business enterprise to define:
(1) a series of “reference” tables (also denoted “master tables”) that describe the appropriate management decision-making, accounting structure, and regulatory information for the specific application;
(2) a series of audit controls and system procedures that provide for complete control of all processing and prevent the overwriting of any original data;
(3) a series of institutional and customer reporting files, known as the “driven” tables; and
(4) the specific processing content of each individual transaction to be processed via a series of table definitions, known as the “driving” tables.
Thus, transactions may be customized according to the business needs of a business enterprise.
Auditability is achieved by:
(1) providing separate control columns for cash, units and cost basis (if any) in detail records generated and stored for each financial transaction;
(2) repeating these three control columns, or variations thereof, in at least three different tables so that subsequent summations of each of the four tables will result in similar balances and thus prove that no critical data has been lost in the course of processing, as one familiar with auditing and financial transactions systems will understand;
(3) adding appropriate data columns:

- (a) to each reference table or master row for maintaining a history of the effects of add, change and delete commands in a current database as well as an archive database;
- (b) to each original file record (i.e. table row) that represents an add to a current database as well as the periodic archive and purge to a permanent database;
- (c) to tables for retaining transaction processing data representing error identification, error negation and error correction.
  Thus, auditabilty of transaction records is achieved by four sets of files for a specific period. These are: (a) a snapshot of all the reference files at the end of the period; (b) snapshots of a history file for each master table, wherein the corresponding history file (table) contains all changes to the master table during the specific period; (c) a snapshot of all financial transactions for the specific period, and (d) a snapshot of all of the “driven” tables at the end of the period.

Multiprocessing is achieved by:
(1) decomposing the processing of the present invention into a series of separate and independent subprocesses that may be simultaneously performed on any number of simultaneous processors, and
(2) decomposing input transactions into a series of subtransactions that are processed by independent processes, which may be executed in any particular order, with complete auditability.
For example, multiprocessing can be achieved by allocating the next prescribed subtransaction process to the next available processor.
Efficiency is achieved by:
(1) Defining and utilizing only four standard processing models that perform all prescribed functionality and auditability of the present invention. The models are:

- (a) Processing Model 1 provides an architecture for maintaining historical transaction data so that financial changes can be traced through time;
- (b) Processing Model 2 provides an architecture for automatically maintaining data columns such as Units, Debits and Credits for cross checking table sums to assure that the financial records for a business enterprise balance;
- (c) Processing Model 3 provides an architecture for automatically maintaining financial records relating to financial instruments such as stocks, bonds, real estate, etc.; and
- (d) Processing Model 4 provides an architecture for producing a common processing format for maintaining customer and institutional data tables.

(2) Defining only four primary program modules for controlling functionality of the present invention, these modules being:

- (a) a transaction processing controller module for receiving transactions to be processed, and controlling the processing thereof;
- (b) a preprocessor and decomposer module for determining the validity of a received transaction, assuring that all data tables and rows thereof are available for processing the transaction, and retrieving the appropriate subtransactions data descriptions to be processed;
- (c) a subtransaction scheduling module for scheduling instantiations of the subtransaction processing module on each of one or more processors; and
- (d) a subtransaction processing module for performing each subtransaction retrieved by the preprocessor and decomposer module.

(3) Utilizing a number of software switches to control which tables within collection of “driven” tables are to be updated when a specific type of transaction is to be processed.
Thus, by providing a small number of processing models, decomposing input transactions, and supplying only the necessary subtransaction descriptions, the reliability of the transaction processing system of the present invention is substantially increased.
The software for the present invention is small in size (both source code and object code) due to the following:
(1) defining business enterprise financial data processing methods, accounting structures, and regulatory definitions as data rather than program code;
(2) reducing the processing content to a series of individual transactions; and
(3) reducing all financial transactions to a collection of subtransactions wherein each subtransaction includes an operator and two or more operands in an 8-character string.
Thus, the financial processing by the present invention may be performed on several transactions at a time, one transaction at a time, or different processors within a multiprocessor context. Or, the subtransactions for a specific transaction may be spread over several simultaneous processors. This means that the business enterprise is afforded a large number of options in tailoring the present invention.
Hence, by defining the accounting structure and processing functionality as data rather than actual program code, the size of the total code required to process a specific industry application may be substantially reduced compared to prior art transaction processing systems. For example, the executable code for the present invention may be less than one megabyte (1 MB). Thus, since the secondary cache attached to each processor in multiprocessing personal computer servers can be one megabyte, substantially the entire executable for the present invention can be provided to each processor. Thus, the positive impact on total system efficiency is believed to be substantial in that secondary cache is typically about four times faster than normal cache, so productivity gains of about three-hundred percent would not be unreasonable. In other words, the executable code for the present invention can reside in the secondary cache of each processor, thereby allowing the off-loading of any processing function to any processor with relative ease. Additionally, given that a typical RAM memory for a personal computing devices is 16 megabytes, it is believed that such a device will have the capability to process the back office financial transactions of a major money center financial institution or communications billing system.
Additional features and benefits of the invention will become evident from the detailed description and the accompanying drawings contained herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a high level block diagram illustrating the present invention conceptually.
FIGS. 2A and 2B is another block diagram of the present invention illustrates: (a) the high level transaction processing modules, and (b) the data tables (represented by the symbols with arcuate vertical sides) provided and maintained by the present invention. Furthermore, the present figure shows the data flows as solid arrows and control flows as dashed arrows. Moreover, this figure also indicates the data tables effected by process models No. 2 and No. 3 of the present invention.
FIG. 3 is another high level block diagram of the present invention during activation of the preprocessor and decomposer 54 wherein the solid arrows are illustrative of the data flows that occur during the activation of the preprocessor and decomposer 54. Moreover, the tables within boxes represent tables having a process model No. 1 representation, and the tables having account balancing control fields include the identifier, “CNTLS.”
FIGS. 4-A through 4-E illustrate the steps of a flowchart for initializing the database tables of the present invention for a new business enterprise licensee that is to have its financial transactions subsequently processed by the present invention.
FIG. 5 is a block diagram illustrating process model No. 1 of the present invention.
FIG. 6 is a high level flowchart of the steps of an embodiment of the transaction processing controller 52 of FIG. 2A.
FIGS. 7-A through 7-D show the high level steps performed by an embodiment of the preprocessor and decomposer 54 of FIG. 2A.
FIGS. 8-A and 8-B show the steps of a flowchart for obtaining indexes or pointers to particular rows of a general ledger table wherein the rows are used in processing a transaction.
FIGS. 9-A and 9-B show the steps for a flowchart of an embodiment of the subtransaction processing module 64 (FIG. 2A).
FIG. 10 is an embodiment of a flowchart of the steps performed for processing income cash transactions by the present invention.
FIG. 11 is an embodiment of a flowchart of the steps performed for processing principal cash transactions by the present invention.
FIG. 12 is an embodiment of a flowchart of the steps performed for processing invested income transactions by the present invention.
FIG. 13 is an embodiment of a flowchart of the steps performed for processing invested principal transactions by the present invention.
FIG. 14 is an embodiment of a flowchart of the steps for performing custom accounting such as income expenses, and cash flow for a business enterprise.
FIG. 15 is an embodiment of a flowchart of the steps for maintaining a business enterprise's balance sheet related to buys and sells of financial entities or instruments.

DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT OF THE INVENTION

FIG. 1 shows a high level conceptual block diagram of a transaction processing system 50 according to the present invention. In particular, the present invention is conceptualized in the present figure as including five functional components, these being:
(a) transaction processing controller 52 for: (i) receiving transactions 58 from business enterprises, (ii) controlling the processing of such transactions, including the scheduling of subtransactions to be performed, and (iii) writing of transaction details to, for example, a transaction journal file or table;
(b) a transaction preprocessor and decomposer 54 for initially receiving a transaction 58 from any one of a plurality of business enterprises as shown, wherein the preprocessor and decomposer 54 decomposes transactions into subtransactions;
(c) a subtransaction processing module 64 for performing the instructions for each subtransaction determined by the transaction preprocessor and decomposer 54. In particular, the subtransaction processing module 64 utilizes a collection of subtransaction programmatic data descriptions 66 that can be independently scheduled and performed for processing each transaction 58 provided to the transaction processing system 50;
(d) a subtransaction scheduler 62 for scheduling the execution of each subtransaction output by the preprocessor and decomposer 54;
(e) a collection of databases 70 containing financial information for each of the one or more business enterprises. Note that the term “database” in the present context includes both the data therein as well as database management functional elements and data structure definitions.
Another illustration of the present invention is provided in FIG. 2. This figure is a block diagram providing both the processing components of FIG. 1, and additionally, greater detail is provided of the tables or files within the databases 70. However, to simplify the discussion hereinafter, the database terminology used will be that of a relational database. Accordingly, files may also be equivalently referred to as tables, records may also equivalently be referred to as rows, and record fields may also be equivalently referred to as columns. Thus, all the data storage symbols having the collective label of 70 are provided within the like numbered databases of FIG. 1. It is worth noting, however, that in one embodiment of the present invention, the data tables for distinct business enterprises may be provided in the same collection of tables such as those represented in FIG. 2. That is, it is an aspect of the present invention that the accounting and transaction processing of the present invention can use the same plurality of financial data tables for business enterprises having substantially different financial transactions and accounting categories. Thus, although FIG. 1 illustrates the databases 70 as being distinct for each business enterprise, many of these databases (if not most) may be combined into a single database having a plurality of data tables such as those labeled collectively “70” in FIG. 2, these tables being discussed in detail hereinafter.
Referring still to FIG. 2, a high level view of the processing performed when processing a transaction 58 is provided. In particular, the transaction processing controller 54 receives an input transaction 58 and invokes the preprocessor and decomposer 54. The preprocessor and decomposer 54 subsequently performs, for each transaction 58, the following functions:

- (a) determines, using input from the business enterprise databases 70, whether all necessary data for performing the transaction is available and otherwise rejects the transaction without performing any portion thereof. In particular, the transaction preprocessor and decomposer 54 determines that all data tables to be accessed are available;
- (b) retrieves the data needed to perform the transaction;
- (c) checks to determine that the transaction operation(s) requested is available, and that the transaction is legitimate to be performed on the data for the input transaction 58;
- (d) retrieves the subtransaction data descriptors for decomposing the input transaction 58 into subtransactions.
  Accordingly, the preprocessor and decomposer 54 retrieves into the working storage 72 (shown in FIG. 3) of a host computer (not shown), upon which the transaction processing system 50 is operating, substantially all data and table rows that are necessary to process the transaction 58. Additionally, note that as one skilled in the art will understand, if some portion of the required data to process the transaction is unavailable, then the preprocessor and decomposer 54 terminates processing and subsequently writes appropriate error messages and/or details of the transaction into the reject table 74 (FIG. 2).

Assuming that the preprocessor and decomposer 54 successfully performs the gathering of information for the decomposing of the transaction into subtransactions appropriately, then control is returned to the transaction processing controller 52, wherein this controller then writes the details of the transaction to the transaction journal 78 along with identification data uniquely identifying the transaction (e.g., a transaction sequence number and/or time and date stamp). Following this, the transaction processing controller 52 invokes the subtransaction scheduler 62 for scheduling the performance of each subtransaction by an invocation of the subtransaction processing module 64. Note that it is an important aspect of the present invention that since the subtransactions can be processed independently of one another for a given transaction, instantiations of the subtransaction processing module 64 can be executed in substantially any desired order. In particular, such instantiations of the subtransaction processing module 64 can be performed concurrently, thus providing a substantial increase in transaction processing efficiency when such concurrency is provided on a computer having a plurality of processors.
Given that a subtransaction is performed successfully by the subtransaction processing module 64, various accounting tables within the transaction processing system 50 are updated. In general, each subtransaction conceptually indicates a single operation of either plus or minus that is to be performed with two operands also indicated in the subtransaction. That is, the first operand indicates the data to be added or subtracted from a particular field or column of a table row identified by the second operand. Additionally, each subtransaction updates other tables within the transaction processing system 50 automatically in order to provide consistency among the data tables so that: (a) substantially on-line account balancing capabilities can be performed, and (b) full auditability of the records of the business enterprise providing the transaction can be facilitated by retaining history records of table updates, as will be discussed with reference to “master table transaction cluster processing” described hereinbelow. Accordingly, each subtransaction processed by an instantiation of the subtransaction processing module 64 may update a plurality of the data tables contained in the collectively labeled database 70. Note that for one skilled in the art of transaction data processing and accounting, the names provided to the tables are indicative of their information content and structure. However, for clarity, substantially all of the tables for the present invention will be discussed in detail and/or illustrated hereinbelow.
The subtransaction processing module 64 processes subtransactions derived from three general categories of transactions that may be input to the present invention. That is, there may be input transactions for each of the following types of financial transactions (1.1) through (1.3) hereinbelow.
(1.1) Transactions related to exchanges of funds such as cash debits and credits for accounts of a particular business enterprise are provided. At a high level, the tables related to this functionality include the account master table 84 (FIG. 2), the general ledger table 88, and the entity, attribute master table 92.
(1.2) Transactions related to additional or customized accounting for clients having accounts in the account master table 84 are provided. For example, in addition to providing the functionality of the transactions described in (1.1) immediately above, a customer income statement (income/expense) table 96 may be provided with client account and transaction information related to income and expenses for tax purposes. Additionally, a customer cash flow (receipts/disbursements) table 100 is also provided for recording any account transaction information related to receipts and disbursements in client accounts. Further, a customer performance measurement table 104 is also provided for retaining client account performance information related to the performance of client portfolios in comparison to investment indexes such as the Dow Jones Industrial Average, the S&P 500, etc. Note that these tables will be discussed and/or illustrated hereinbelow.
(1.3) When transactions are additionally related to financial instruments other than cash, debits and credits, such as portfolio management wherein there is buying and selling of equities, income derived from equities, and trade settlements related thereto. Further, note that these additional capabilities also provide the same degree of flexibility, adaptability and simplicity as provided in relation to the transaction processing capabilities discussed in (1.1) and (1.2) immediately above. That is, financial equity transactions of various types and for various business enterprises may be easily modified and/or added or removed from the transaction processing system 50 of the present invention, since these transactions are also described by transaction data descriptors consisting of a collection of subtransactions that are capable of being performed in substantially any order that is determined by the subtransaction scheduler 62.
Accordingly, in providing the functionality for the transactions related to portfolio management, the preprocessor and decomposer 54, upon being invoked by the transaction processing controller 52, also retrieves into working storage (as shown in FIG. 2) the necessary data for processing such portfolio maintenance transactions, this data including a subtransaction decomposition for the transaction. Subsequently, as discussed hereinabove, the subtransaction scheduler 62 invokes an instance of the subtransaction processing module 64. However, in addition to updating any appropriate rows of the tables 84, 88, 92, 96, 100 and 104, the subtransaction processing module 64 invokes a portfolio adjuster module 110 for capturing and/or updating detailed data of portfolio transactions that are not otherwise effectively captured for proper accounting and auditing. In particular, for a given subtransaction, the portfolio adjuster 110 invokes one of the following modules (2.1) through (2.4) hereinbelow.
(2.1) Original add module 114 for processing a subtransaction related to the addition of further financial instruments to a portfolio such as occurs when securities are bought and must be added to a given account.
(2.2) A reverse of add module 118 for reversing an addition of financial enterprises to a particular account portfolio. Note that this module is typically activated when financial enterprises are inadvertently added to an incorrect portfolio account.
(2.3) An original sell module 122 for processing subtransactions related to selling financial enterprises within a given account portfolio.
(2.4) A reversal of original sell module 126 for reversing the affects of an inadvertent sell of financial enterprises within an account portfolio.
These four modules 114-26 update the tables labeled collectively as 70B. In particular, the processing performed herein and the tables updated herein are described below.
Major Programs and Functionality
Major Programs
The N_gine transaction processing system contains four major programs. These are:

- (1) Transaction Processing controller 52
- (2) Transaction Preprocessor and Decomposer 54
- (3) Subtransaction Processing module 64
- (4) Subtransaction Scheduler 62
  Program Functionality

The purpose of the Transaction Processing controller 52

- (a) test for incoming transactions and once detected
- (b) execute the Transaction Preprocessor and Decomposer 54 and then
- (c) execute the Subtransaction Processing module 64 for each transaction.

The purpose of the Transaction Preprocessor and Decomposer 54 is to verify

- (a) that all information in the transaction is accurate
- (b) that all files and controls are available to properly process the transaction
- (c) that the specific subtransaction processing instructions are loaded into working storage.

The purpose of the Subtransaction Processing module 64 is to

- (a) execute all of the subtransactions that have been previously defined for a transaction
- (b) create auditability for every transaction.

The purpose of the Subtransaction Scheduler 62 is to

- (a) allocate a specific task to a specific processor
- (b) return processing to the Transaction Processing controller 52.

The present invention may be described as “Table-Driven Transaction Processing”. That is, the present invention permits the processing of virtually any type of user-definable transaction by defining the processing for such transactions as data descriptors that are interpreted in real time and dynamically as needed for processing corresponding transactions. Accordingly, the transaction data descriptors are denoted as “driving data” and are defined by the transaction processing master table and the transaction master table. That is, the transaction master table provides a first initial collection of data for identifying each transaction and the transaction processing table provides the remainder of the data including the subtransaction decompositions. Accordingly, each transaction processed updates an appropriate set of user-definable tables (known as the “driven” data) for completing the processing of the transaction. Since both the “driving” and the “driven” information is expressed as data rather that actual code, the entire functionality of the system can be changed in a straightforward manner.

In the description hereinbelow, the functional components of the present invention are also identified by other naming conventions from the description above. Accordingly, the following table shows the pairing of the functional component identifications above with those also used below:



ABOVE	BELOW

TRANSACTION PROCESSING	N_GINE COMMAND
CONTROLLER
52	PROCESSOR
TRANSACTION PREPROCESSOR	N_GINE EDIT PROCESSOR
AND DECOMPOSER 54
SUBTRANSACTION PROCESSING	N_GINE POSTING TO AM,
MODULE 64	EA AND GL
SUBTRANSACTION	N_GINE SCHEDULER
SCHEDULER
62
PORTFOLIO ADJUSTER 110	AORS
ORIGINAL ADD MODULE 114	ORIGINATE ADD
	PROCESSING
REVERSER OF ADD MODULE 118	REVERSE ADD PROCESSING
ORIGINAL SELL MODULE 122	ORIGINATE SELL ROUTINE
REVERSE OF ORIGINAL	REVERSER SUBTRACT
SELL MODULE 126	PROCESS

N_gine System Design Rules

A. The Magic Number in Software Design is 1. That is,

- store data once,
- program data once,
- process data once.

B. Design a total system with the fewest number of processing models. For example,

- One model for processing all adds (inserts), changes (updates), and deletes (deletes) for all Master (or Reference) Files (or tables).
- One model for processing all of simple transactions (such as debits and credits), including original and reversing entries.
- One model for processing all complex transactions (such as buys and sells), including original and reversing entries.
- One model for processing all adds (inserts), changes (updates), and deletes (deletes) for all Detail Record (or “driven”) Files (or tables).

C. Use the first and last models to process all files (or tables) in the entire system.
D. Include audit controls for every table in the system from the very outset of design.
E. For reasons of productivity assessment, include Production Statistics for every job.

- Namely,
  - Begin Time
  - Number of Transactions
  - Number of Acceptances
  - Number of Rejects
  - End Time.

These variables represent the only true means of measuring actual productivity.
F. For reasons of auditability, never overwrite any original information. Move all original information from data entry (cradle) to data warehouse (grave) without any changes.
G. For reasons of reliability and profitability, system designs should focus on a “large number of small programs” rather than a “small number of large programs”. The result is not only ease of maintenance but also the ability to spread the small programs across a number of simultaneous processors.
H. For reasons of manageability, all system designs should embrace one integrated enterprise-wide standard naming convention for all files (tables), records (rows), and fields (columns).
I. For reasons of portability, use the fewest number of language commands to code the system. Avoid vendor and/or language extensions.
J. For reasons of flexibility, never hard code what can be table-driven.
N_gine Design Concepts
A. Only 4 Processing Models for Financial Services and Telecommunications Applications

- 1. Schema
- 2. Units, Debit/Credit
- 3. Assets/Liabilities
- 4. File Maintenance Routine

B. Table-Driven Transaction Processing for maximum flexibility

- 1. Number of Transactions
- 2. Name of Each Transaction and Unique Details
- 3. Processing Algorithms (at least 1, up to 20 depending upon complexity)
- 4. Each algorithm has 3 components
  - a. Plus (P) or Minus (M)
  - b. Operand 1
  - c. Operand 2

C. 100% Auditability For Every Transaction by creating

- 1. a Detail Record containing all relevant data and
- 2. hash totals of three relevant fields in at least 3 other tables.

D. The 3 relevant fields for calculating all hash totals are:

- 1. Cash
- 2. Units
- 3. Cost Basis

E. Basic Relational Database Management System Processing Concepts

- 1. Commit/Rollback
- 2. Row Level Locking
- 3. Indexing, ROWID
- 4. Stored Procedures
- 5. Shared Memory

F. Some Financial Services Accounting Systems are not permitted to commingle funds. That is, separate accounting for both income and principal must be provided. Therefore, each account master must have a designated “income posting code” to define the proper processing. Such a code might be: (I) Income Only, (P) Principal Only, (B) Both Income and Principal.
N_gine's Basic Tables
Licensee Profile (The Licensee “Reference” or “Master” Tables)

LM The License Master table contains the necessary information to process any type of licensee using either single or multiprocessing computers.
LU The Licensee User Master identifies different users for the disparate systems that may be processed simultaneously.
LT The Licensee Account Type table contains the necessary information to process any type of account be it for a pension trust account, a communications account, or a corporate subsidiary.
LD The Licensee Default Definition table the default definitions for cash, units, and cost basis controls for total system control.
LL The Licensee General Ledger Definition is a list of all of the acceptable entries for the General Ledger. That is, it provides a framework for processing any type of accounting controls for any set of account types.
LS The Licensee Diversification Scheme contains a three level classification scheme for reporting an decision-making purposes for any set of assets and liabilities.
LP The Performance Measurement Group Master contains a three level classification scheme for measuring the performance of different investment groups.
LN The Licensee Summary Name Master contains a list of the entries on any type of Income Statement and Cash Flow Statement.
LW The Licensee Wholesaler Master contains name, address, sales volumes, etc. wholesalers of communications services.
LR The Licensee Reseller Master contains name, address, sales volumes, etc. for resellers of communications services.
Account Profile (The Customer “Reference” Tables)
AO The Account Objectives Table contains the different types of account objectives, such as income, growth, capital preservation, etc.
AL The Account Jurisdiction contains the different types of legal relationships, such as broker, agent, trustee, advisor, etc.
AJ The Account Jurisdiction contains the different types of legal jurisdiction, such as federal law, state law, foreign law, etc.
AR The Account Representatives Table houses the different representatives, their names and communication addresses.
AN The Account Registration Names is a list of legal names used in security settlement.
AM The Account Master table provides all of the necessary information to process any type of account by linking the Account Objective, Account Jurisdiction, Legal Capacity, Profit Center, Account Representative, and Registration tables plus other relevant data for reporting content and reporting cycles.
AC The Account Communications Links links the Account Number for Financial Services to the account numbers for communications services so that all information can be contained in one reporting scheme.
Transaction Profile (The “Driving” Tables)
TM The Transaction Master table provides all of the information to process any type of transaction, excepting the specific processing algorithms.
TP The Transaction Processing table provides all of the specific processing algorithms for any type of transaction master. The Transaction Master and Transaction Processing tables provide all of the necessary information to process any type of transaction.
TR The Transactions-Recurring Table (TR) contains the necessary information for automatically processing any type of transaction on a recurring basis.
Entity Profile (The Entity “Reference” Tables)
EM The Entity Master table provides all of the necessary information to process any type of financial entity.
EA The Entity Attribute table joins all relevant diversification (known as type, group, and class), general ledger (known as accounting control numbers), and performance group (known as type, group, and class) data into one table for only one access seek.
ET The Entity Transaction table links specific transactions to specific entities, such as BG (Buy Government) for a US Treasury Note, BF (Buy Tax-Free) for a tax-free bond, BE (Buy Equity) for common stocks, etc. Note: It is the correct assignment of such transactions to such entities that permits the proper accumulation of data for income tax purposes.
Licensee Status
SG The System General Ledger contains all of the information to process any type of institutional accounting control.
SJ The System Transaction Journal Table contains all of the transactions and all of the details for each transaction for a specific accounting period.
ST The System Trade Settlement Table contains all of the automatically generated offset transactions for Buys and Sells
SS The System Summary Table contains a record for each execution of the system with the Begin Time, End Time, Number of Total Records Read, Number of Accepts, Number of Rejects, etc.
SR The System Reject Table contains a list of all transactions rejected for whatever reason.
SC The System Transaction Count Table contains the number of each type of transaction processed on any given transaction.
Customer Status (The “Driven” Tables)
CS The Customer Income Statement contains all revenues, expenses, and profits or losses for all customer accounts.
CF The Customer Cash Flow Statement contains all receipts and disbursements for all customer accounts.
CB The Customer Balance Sheet table contains all assets and liabilities for all customer accounts.
CG The Customer Capital Gains table contains all of the realized capital gain details for all customer accounts.
CI The Pending Income table contains all of the pending income, such as interest or dividends, for all accounts.
CA The Pending Capital Adjustments table contains all of the pending capital adjustments, such as stock splits, stock dividends, mergers, acquisitions, etc., for all accounts.
CP The Performance Measurement contains all of the periodic performance records for all customer accounts.
The Control Tables (The “System Balance” Tables)

Since every transaction is recorded in a detail record plus hashed to three other control tables, the control values of cash, units, and cost basis are added to like values in the following control tables:

- Account Master, System General Ledger, and Entity Attribute tables.

For other reports such as the Income Statement and the Cash Flow Statements, the Performance Measurement table is used as a control table instead of the General Ledger.
The present invention includes four computational processing models (process models 1 through 4) for processing financial transactions and assuring full auditability and traceability.
The purpose of Process Model 1 (FIG. 5) is to create a single methodology for capturing, maintaining, and archiving the non-financial transaction data including a master table (reference table, or schema) data for 100% auditability within a single software system. This model provides:
A current database 300 (FIG. 5) (for additions, negations and corrections) and an archive database 304 (Read Only)
Eight tables (i.e. tables 312, 316, 320, 324, 328, 332, 336 and 340, of FIG. 5)
Number of Modifications
12 Control Fields per master table
A sequence number generator
A process flow methodology for add, change, and delete of data table rows.
The operation of Process Model 1 is as follows:

1) Normal Updating to current database 300



Write to	Write to	Move Master	Add to	Change	Delete
Reject	Accept	to History	Master	Master	Master

Add
IF Identifier Found	X
IF Identifier Not Found		X		X
Change
IF Identifier Not Found	X
IF Identifier Found		X	X		X
Delete
IF Identifier Not Found	X
IF Identifier Found		X	X			X

2) Periodic updating to the archive database 304 at the end of a pre-determined time period. That is,

- (a) archive snapshots of the archive master 312 in the current database 300 to the master in archive database 304;
- (b) archive the archive history 332 in the current database 300 to the master history 340 in the archive database 304;
- (c) purge the history table 332 in the current database 304.

The purpose of Process Model 2 (FIGS. 2A, 2B) is to create a single methodology for: capturing, maintaining, and archiving the financial transaction data including: units, and debit/credits for one or more disparate financial applications with 100% auditability, wherein the processing is performed by: (a) computing configurations containing any number of simultaneous processors, (b) decomposing each input financial transaction into separate and independent subcomponents, (c) allocating the subcomponents across any number of multiple processors.
The methodology of process model 2 utilizes a data-driven transaction processing strategy, wherein the manner in which a transaction is processed is determined by retrieving appropriate control data for processing a given input transaction. Thus, the present model provides the ability: (a) to process like systems (such as financial services systems) with different transaction definitions and accounting requirements (such as commercial banking, broker/dealers, mutual funds, insurance systems) and different debits and credits and/or (b) unlike systems (such as telecommunications systems) with disparate definitions (such as landline, wireless, satellite, cable systems) within the present invention at the same time.
The purpose of Process Model 3 (FIGS. 2A, 2B) is to create a single methodology for: capturing, maintaining, and archiving the financial transaction data including: units, debits/credits, financial instruments for one or more disparate financial applications with 100% auditability within a single software system on computing configurations containing any number of simultaneous processors, decomposing each disparate financial transaction into separate and independent subcomponents, allocating the subcomponents across any number of simultaneous processors, and processing the data with 100% auditability. The methodology of Model 3 provides:

- “Detail Record Maintenance”, that is, the ability to process transactions for similar business enterprises (such as portfolio management systems) relating to various financial instruments (such as disparate assets and liabilities) and/or transactions for dissimilar business enterprises (such as portfolio management systems, paying agencies, stock transfer systems) with disparate languages (such as English, Spanish, French, or German) and disparate definitions (such as management philosophy, accounting, and operating nomenclature) and unlike financial instruments (such as assets and liabilities) within the same software at the same time.
- The ability to decompose, allocate, process, and audit each financial instrument transactions with 100% auditability.
- The current databases 300 (for additions, negations and corrections) and the archive databases 304 (read only);
- Sixteen data tables (some of which are shown in FIGS. 2A-2B) plus a sequence generator;
- 12 control fields appended to the master tables for tracing master table changes;
- One transaction three hash totals (mostly using AM, EA, and PM tables);
- 4 currency fields;
- Sequence number generation;
- Reversing/reversed by detail;
- Processing flow for additions, negations, and corrections.

The purpose of Process Model 4 is to create a single methodology for performing file maintenance including: creating a record (row) containing the initial data in a file (table) or modifying the initial data within an existing record (row) within a file (table) or deleting a current record (row) from a file (table) in any software application on computing configurations using simultaneous processors. Where the term, “Details”, hereinbelow represents the identity of the specific financial transaction, the methodology of the process model 4 is provided by programs such as the following:

BEGIN

IF Trxn is “ADD” then

/* Test for Duplicate Add */

SELECT One or More Values from the Desired File (Table) into Working Storage

IF Error then

/* Add New Record */

INSERT INTO Reject Report

IF Error then

Message “INSERT Reject ADD”, Details

Goto Write Reject Table

ENDIF

ELSIF

/* Increment Existing Record */

Increment One or More Data Values

UPDATE SET, Details

IF Error then

Message “UPDATE Error ADD”, Details

Goto Write Reject Table

ENDIF

ENDIF

ELSIF Trxn is “SUBTRACT” then

/* Test for Valid Record */

SELECT One or More Value(s) from Existing Record

IF Error then

Message “SELECT Error SUBTRACT”, Details

Goto Write Reject Table

ENDIF

/* Test for Valid Amounts */

IF One or More Amounts > One or More Values from Existing Record then

INSERT INTO Reject Report

IF Error then

Message “INSERT Reject SUBTRACT”, Details

Goto Write Reject Table

ENDIF

/* Delete Existing Record */

ELSIF One or More Amounts = One or More Values from Existing Record

AND Special Deletion Criteria = TRUE then

DELETE Record

IF Error then

Message “DELETE Error”, Details

Goto Write Reject Table

ENDIF

ELSE

/* Decrement Existing Record */

Decrement One or More Values

UPDATE SET, Details

IF Error then

Message “UPDATE Error SUBTRACT”, Details

Goto Write Reject Table

ENDIF

ENDIF

ELSE

/* Invalid ADD or SUBTRACT Code */

INSERT INTO Reject Report

IF Error then

Message “INSERT Reject AORS”, Details

Goto Write Reject Table

ENDIF

ENDIF

Goto EOJ

<<Write Reject Report>>

ADD to Reject Table

IF Error then

Message “INSERT Reject Table Error”, Details

STOP

ENDIF

<<EOJ>>

Null

END

Accordingly, the methodology of process model 4 defines:

- (a) A current database (for additions, negations and corrections) and archive database (Read Only)
- (b) ADD or SUBTRACT;
- (c) Initial tests for values;
- (d) Special deletion criteria;
- (e) Tests for action;
  - INSERT or UPDATE;
  - DELETE or UPDATE;
  - INSERT INTO Reject Tables;
    Processing Model 1:

Processing model 1 is a method for processing changes to files (or tables) denoted as master or reference tables (files) wherein these tables retain fundamental information that is not derivable from other tables. In particular, processing model 1 processes changes to master tables in an automated manner without losing historical financial information. Accordingly, 100% auditability of all data changes is able to be achieved.
The method of achieving this goal uses an architecture denoted as “Master Transaction Cluster Processing” (MTCP). MTCP is based on the premise of creating a logical flow of all original information from data capture (data entry) to permanent data repository (data warehouse) by replacing single master files (or tables) with a cluster of files (or tables). Therefore, MTCP addresses the complete life cycle of all information relevant to organizational decision-making. MTCP is targeted for use in the automatic generation of program code for multiple large-scale real-time transaction processing applications (such as securities trading, telecommunications billing, and work management) on multi-processing computers (using 4, 8, 16, 32 processors), where control is not only an increasing complex issue but an absolute necessity for future competition.
The circumstances leading to the invention of Master Transaction Cluster Processing are:

- a) Prior art financial transaction software architecture lacks the ability to identify transactions by table, transaction date, transaction number, and the person authorizing the transaction.
- b) Prior art financial transaction systems typically use only one table to contain all Master Information (i.e., non-derivable information) and the data in this table is overwritten, thereby losing historical information. Cases in point would be a record of all of the past mailing addresses or processing instructions for a specific customer.
- c) Without 100% retention of an organization's vital information, management has no idea of the accuracy of the information being used for decision-making purposes.
- d) The Year 2000 problem, know as Y2K, is proving that past software applications designs have reached technological limits and current maintenance costs are inordinately expensive.
- e) Competitive pressures are mounting for higher quality software with lower software development and maintenance costs. Totally new architectures for applications software is in great demand.
- f) The ComputerWorld article, “Information: America's Favorite Investment,” by Paul Strassman, ComputerWorld Magazine, Aug. 5, 1996, states that over 1100 companies are spending more on automation annually than the net worths of their respective companies.
- g) The Standish Report as described in Development Patterns, InfoWorld Magazine, Feb. 3, 1997, p. 56, states that the success rate of Business Process Reengineering has increased from 16% in 1994 to only 27% in 1996.

Note, in the book “Oracle Design”, Ensor & Stevenson, O'Reilly Press, it is a recommended practice to compromise data retention rather than achieve 100% auditability. Today's hardware costs suggest otherwise.
The advantages of the present invention over the approaches discussed above are:

- to provide 100% auditability which offers business management the capability to exercise its fiduciary responsibility to its stockholders and Board of Directors,
- to capture, maintain, and ensure the integrity of all vital information for business enterprise decision-making purposes, and
- to preserve such information consistent with business enterprise-defined data retention cycles. Additionally, the present invention allows accountants to certify in business enterprise annual reports that all vital corporate data is being properly preserved.

A detailed description of Master Transaction Cluster Processing corresponding to model 1 (the first computational model of the present invention) is as follows.
MTCP Overview
Master Transaction Clustering, or MTCP, performs the following tasks:

- a) assigns a unique identifier based on (i) master table identification, (ii) transaction date, (iii) transaction number, and (iv) authorized user, to each transaction that causes a change in the state of a particular record of a master table. That is, if one or more data elements in the record change, then the previous record is written to history, and a new status is assigned to an identifier field used for tracking such changes;
- b) creates a logical flow of data as it is originally entered from its inception (data entry) to its repository (data warehouse). The unique architecture of MTCP replaces the Master File (or Table) within prior art systems with a cluster of Master Files (or Tables), known as a “Master Transaction Cluster”. This cluster is suitable for multiprocessing (or the use of simultaneous processors within a single computer to complete a common job). Hence, MTCP addresses 100% auditability via maintaining the total life cycle of information. Aged information may be deleted from the appropriate tables consistent with user-defined data retention policies;
- c) offers a standard for processing all Master Tables within a total application;
- d) provides a test bed for separately testing each Master Table Cluster under development and all Master Table Clusters in concert;
- e) permits management to report that it is successfully capturing, maintaining, and preserving all critical information for decision-making purposes.
  MTCP Scope

Master Transaction Cluster Processing utilizes the following (FIG. 5):

- a) two databases (i.e., the current data base 300 and the archive data base 304),
- b) sequencing generator 308 having: (i) two external sequence generators; (ii) two internal counters,
- c) eight tables (denoted master table 312, input table 316, summary table 320, reject table 324, accept table 328, history table 332, master archive table 336 and master history table 340), and
- d) twelve additional fields for every row in the master table 312.
  MTCP Independence

Master Transaction Cluster Processing of Model 1 is independent of any:

- a) application—such as accounts receivable, customer billing, etc.
- b) industry—such as financial services, telecommunication, or work management,
- c) hardware manufacturer—such as Compaq, Digital, HP, IBM, NCR, Unisys,
- d) operating system—such as MS-DOS, UNIX, OpenVMS, MVS, etc.
- e) network—such as Novell, Ethernet, etc.
- f) relational database management system—such as Oracle, Sybase, Microsoft SQL Server, Informix, etc., and
- g) computer language—such as SQL, COBOL, FORTRAN, PL/l, Java, etc.
  MTCP Architecture

The Master Transaction Cluster Processing (MTCP) architecture can be used for any application in any industry using any computer language. Within the typical structured processing scheme of input and process, the Master Transaction Cluster Processing focuses solely on the process function. Thus, the method permits users to define input screens and defined output reports.
MTCP Databases
Unlike prior art software system which contain only one table for each set of primary records, Master Transaction Cluster Processing uses eight related tables, or a cluster of tables, to track all information on a cradle to grave basis. The cradle being its point in inception (or data entry), and the grave being its permanent repository (or data warehouse). Consequently, the “Master Transaction Cluster” spans two different databases: one denoted the Current database 300 containing all relevant data for the current processing period and a second denoted the Archive database 304 containing all relevant data for all previous processing periods. The Current database 300 represents the area of high inquiry, and the Archive database 304 represents the area of low inquiry. Consequently, the Current database 300 is normally placed on high-speed internal disk drive and the Archive database 304 is normally placed on less expensive lower-speed CD-ROMs. Note that trailing information in the Archive database 304 may be destroyed consistent with defined data retention policies, statute of limitations, etc.
MTCP Tables
The six tables in the Current database 300 are the

- a.) Master Table 312 (M) that will contain all records to be maintained.
- b.) Input Table 316 (I) that will contain all records prior to updating.
- c.) Reject Table 324 (R) that will contain all records rejected during processing.
- d.) Accept Table 328 (A) that will contain all records accepted during processing.
- e.) History Table 332 (H) that contain a complete snapshot of all records prior to updating.
- f.) Summary Table 320 (S) that contains the results of a specific processing operation.
  and the two tables in the Archive database 304 are the:
- g.) Master Archive Table 336 that contains snapshots of the master table 312 at the end of each processing period.
- h.) Master History Table 340 that contains a history of the master table 312 changes during a current processing period.

Note that the Master Table (M), Input Table (I), Reject Table (R), the Accept Table (A), the History Table (H) in the same “Master Transaction Cluster” share the same number and order of data elements consisting of alphabetic, numeric, and date items. Alternatively, the Summary Table (S) contains the start time, end time, number of accepts, and number of rejects for each time a series of master table 312 modifications are provided.
MTCP Generator and Counters
The Generators 308 include two different external counters and two internal counters used in effecting 100% auditability. The two external counters are the Accept Sequence Number Generator and the Reject Sequence Number Generator. The two internal counters are the Total Records Read Counter and the Number of Modifications Counter. All are used only in the Current database 300, as the Archive database 304 is read-only in nature.
Regarding the external counters, the Accept Sequence Number Generator included in the Current database 300 automatically generates sequential numbers for the processing period (daily, weekly, monthly, etc.) starting with the number 1, and increments by 1, so that every transaction processed against the preceding (old) master table 312 will receive a specific transaction number, and accordingly, each transaction processed will be uniquely identifiable based on master table identity, transaction date, transaction number, and authorized user. Note that the transaction date is read off the internal system clock. The Reject Sequence Number Generator counts the number of rejects for the specific processing period. Its function is similar to the Accept Sequence Number Generator. Both the Accept Sequence Number Counter and the Reject Sequence Number Counter are “processing period” specific. That is, both are cleared to zero at, e.g., midnight on the end of the processing period so that each processing period may be separately identified and audited.
Regarding the internal counters, the Total Records Read Counter counts the number of transactions read during a specific processing performance. Since the Total Records Read Counter is “job execution” dependent, this counter is cleared to zero at the outset of every processing program execution. The Number of Modifications Counter counts the number of times a specific record has been changed. As this counter is “record” dependent, this counter is never cleared to zero, This specific counter should identify the number of individual records that may be retrieved, viewed, and verified from all of the tables in the specific Master Transaction Cluster to prove its auditability.
MTCP Archive Database 304
The Archive database 304 is read only. Within the Archive database 304, information contained in the Master Archive Table 336 represents a snapshot of information in the Master Table in the Current database 300 at a particular point in time such as the end of a month, quarter, or year. And, information in the History Archive Table 336 contains all of the transactions that have occurred from the beginning of the most recent processing period until the particular point in time, be it month, quarter, or year. For example, the Master Archive Table 336 contains the status of the Master Table 312 at the end of the first quarter, and the History Archive 340 contains all of the transaction modifications occurring since the end of the last quarter. In this fashion, any status of any Master Table 312 can be recreated for any point in time (say, month ends) by simply processing all transactions in the History Archive 340 for the desired period against the previous Master Archive Table 336, or the beginning of the period.
MTCP SQL Script Library Implications
To achieve 100% auditability of a complete system, every master file (or table in relational database management systems has a Master Transaction Cluster. Therefore, a total system containing 15 tables would require 15×8 or 120 tables to achieve full 100% auditability. Since each table will require at least 4 SQL scripts to (1) Create Table, (2) Select data from the table, (3) Delete data from the table, and (4) Drop the Table in the event of redefinition, the number of SQL scripts is 15×8×4, or 960 SQL Scripts. Then, each Master Transaction Cluster will require at least a Processing Program plus a Review, Reset, and Retest, or at least four more programs for each cluster, or 4×15, or 60, more SQL Scripts. All of the SQL scripts would be stored in one SQL Script Library on the computer for future reference and ease of maintenance.
MTCP Multi-Processing
The multi-processing of the Master Transaction Cluster occurs in the following manner:

- For additions (or Insertions in SQL) of data
  - The Insertions to the Master Table 312 and Insertions to the Accept Table 328 may be processed simultaneously.
- For changes (or Updates in SQL) of data
  - The Update of the Master Table 312 and the Insert to the Accept Table 328 may be processed simultaneously after the original record from the Master Table 312 has been copied to the History Table 332.
- For deletes (or Deletes in SQL) of data
  - The Deletion from the Master Table 312 and the Insertion to the Accept Table 328 may be processed simultaneously after the current record in the Master Table 312 has been updated for the transaction identifier and then copied to the History Table 332.
    MTCP Creation

Before processing any Master Transaction Cluster, the necessary databases and files (or tables) must be created. For each business enterprise utilizing the present invention, these databases and files are created only once in the following manner:



	(Begin Program)
	Create ”Current“ database
	Create ”Archive“ database
	in the ”Current“ database
	Create Master Table
	Create Input Table
	Create Reject Table
	Create Accept Table
	Create Second Accept Table (on separate
	disk unit, if desired)
	Create History Table
	Create Summary Table
	Create Sequence Number for Accepts
	Create Sequence Number for Rejects
	in the ”Archive“ database
	Create Master Archive
	Create History Archive
	(End of Program)

MTCP Processing

Processing of the “Master Transaction Cluster” then occurs in the following manner.

Step 1: All required information for processing a transaction is first captured on an Input Form.
Step 2: Once this information is edited by, e.g., an operator, an Enter Key can be pressed by an operator to write this information to the Input Table 316 for particular master transaction clusters.
Step 3: For each input table 316, a polling program notes that the Input Table is not empty and has a transaction action to be processed whereupon the action is processed by a process (denoted “process 1” in FIG. M1).
Step 4: The transaction processing program determines the type of file maintenance to perform; basically,
- (1) add a record (entitled Insert a Row in SQL),
- (2) change a record (entitled Update a Row in SQL), and
- (3) delete a record (entitled Delete a Row in SQL),
  which in turn determines the multi-processing potential as described above in the MTCP Multi-processing.

The normal daily processing flow to achieve 100% auditability in either real-time or batch mode is as follows:



(Begin Program)
Read System Clock to Store Begin Time
(Read Next Transaction)
If Last Transaction
Read System Clock to Store End Time
Write End Time, Begin Time, Number of Accepts, Number of Rejects,
and Total Records Read to Summary Table
Goto End of Program
Increment Total Records Read by 1
(Add a New Record)
If transaction is ”Add“ then
If record exists then
Process Addition Error
Goto Write Reject Table
********************************************************

* Select System Clock Date	into Insert - Transaction Date	*
* Increment Sequence Number	into Insert - Transaction Number	*
* Select User Name	into Insert - Transaction User	*
* Select Zero	into Update - Transaction Number	*
* Select Zero	into Delete - Transaction Number	*

*********************************************************

Insert to Master Table

Goto Write Accept Table

(Change an Existing Record)

If transaction is ”Change“ then

If record does not exist then

Process Change Error

Goto Write Reject Table

*********************************************************

* (Master Snapshot)	*
* Move Master Table Record to History Table	*

*********************************************************

* Select System Clock Date	into Update - Transaction Date	*
* Increment Sequence Number	into Update - Transaction Number	*
* Select User Name	into Update - Transaction User	*
* Select Zero	into Delete - Transaction Number	*

* Increment Master Table Number of Modifications by 1 *

*********************************************************

Update Master Table with New Data

Goto Write Accept Table

(Delete an Existing Record)

If transaction is ”Delete“ then

If record does not exist then

Process Drop Error

Goto Write Reject Table

*********************************************************

* Select System Clock Date	into Delete - Transaction Date *
* Increment Sequence Number	into Delete - Transaction Number *
* Select User Name	into Delete - Transaction User *

*********************************************************

* Update Master Table Record for Tran Date/Tran Num/User *

*********************************************************

* (Master Snapshot) *

* Move Master Table Record to History Table *

*********************************************************

Delete Master Table Record From Master Table

(Write MULTI-PROCESSED Accept Table)

****************************************

* Move ”Current“	into Archive - Status *
* Move ”System Date“	into Archive - Date *

****************************************

Increment Accept Counter

Insert to Accept Table

Insert Second Accept Table (on a separate disk drive, if desired)

Goto Loop to Next Transaction

(Write Reject Table)

Increment Reject Counter

Insert to Reject Table

(Loop to Next Transaction)

Goto Read Next Transaction

(End of Program)

End

Step 5: At the end of the “proofing period”, such as daily or weekly, when proof tallies are matched to computer tallies, the Accept Table can be deleted as follows:
- (Begin Program)
  - Delete All Records from the Accept Table
- (End Program)
Step 6: Backup all databases and tables before any information is purged as follows:
- (Begin Program)
  - Write All Tables in the “Current” database to backup
  - Write All Tables in the “Archive” database to backup
- (End of Program)

Step 7: At the end of a user-defined period, an archive and purge process occurs that



	(Begin Program)
	*************************************************
	* Move ”Archive“ to Archive Status
	* Move ”System Date“ to Archive Date
	*************************************************
	Move All Records in the Master Table to Master
	Archive.
	Move All Records in the History Table to the
	History Archive.
	(End Program)

Step 8: In the event that current records are wrongfully moved to the History Archive,
- they may be retrieved by
- (Begin Program)
  - Move Specific Records from the Master Archive to the Master Table
  - Move Specific Records from the History Archive to the History Table
- (End Program)
  This program should be executed only after Records have been moved from the Current database 300 to the Archive database 304. It should never be run after new transactions have been processed to the Current database 300.
  MTCP Backup/Recovery

If necessary, a recovery program can be utilized at any time in the event of hardware failure. Upon complete recovery, Step 7 and Step 8 will have to be re-executed to insure the correct status before the next day's processing is begun. The Accept Table can then be used to as a substitute Input Table to return the system to its previous processing point. Once this table is exhausted, data from the Input Table would supply the remaining data for the processing job.
MTCP Management
Once test data are defined and processed, a business enterprise may

- (a) Review lists of the contents of all Master Tables 312 for determining correctness.
- (b) Reset the contents of all Master Tables for performing the next test.
- (c) Retest.
  MTCP Auditability

Once auditabilty is achieved, the business enterprise may query:

- (a) When a Master Table Cluster was created.
- (b) When each record was added (or inserted) to the Master Table 312,
- (c) How many authorized changes (or updates) have been made to a record of the Master Table 312.
- (d) Prove the integrity of the master transaction cluster by producing a sequential list of all record changes, and if the record was deleted, where the record is stored.
  Accordingly, 100% auditability of every change, every day, for every application is possible.
  Multiprocessing Defined

Unlike serial processing which processes all jobs in sequential fashion, multiprocessing processes some of the same jobs simultaneously, or in parallel. While multiprocessing is not new, major computer manufacturers such as Compaq, Digital, Hewlett-Packard, IBM, NCR, Unisys, etc. have announced offerings of low-cost multiprocessing machines based on 2, 4, 8, and sixteen processors. These machines will rapidly increase the demand for multiprocessing software, which is known as “multithreaded” software. Multithreaded software permits the simultaneous execution of more than one jobs or job sequences.
Multiprocessing takes two forms, Symmetrical Multiprocessing (SMP) and Massively Parallel Processing (MPP), the difference being that symmetrical multiprocessing machines collectively have only one bus between the processors and the peripheral storage. For example, a symmetrical multiprocessing machine may have eight processors, one bus, and sixteen disk drives. In contrast, massive parallel processing machines has one bus for each processor. For example, a massively parallel machine may have eight processor, eight busses, and sixteen disk drives. Therefore, symmetrical multiprocessing machines are best suited for applications with a high processing content and a low input/out content. In contrast, massively parallel processing machines are best suited for applications that can be parallelized and have a high input/output requirement, as is the case with many commercial systems.
In either event, multiprocessing machines are best utilized when carefully tuned to avoid bottlenecks. This is likely to mean that all of the layers constituting a computing environment are multiprocessing-enabled. That is, the hardware, operating system, relational database management system, and the specific application are capable of multiprocessing. Some multiprocessing mainframes have been available for several years as well as some versions of the UNIX operating system. Only a few multiprocessing relational databases exist and even fewer multiprocessing applications. It is believed by some that the success of multiprocessing is solely dependent upon the “knowledge of the application” rather than “knowledge of the underlying tools,” the tools being the hardware, operating system, and relational database system.
Accordingly, it is believed that the limiting factors for the success of multiprocessing for financial systems depends on:

- (1) the lack of financial transaction application knowledge,
- (2) a lack of understanding of how multiprocessing can be used to effect 100% auditability, and
- (3) the lack of understanding as to how to decompose a financial transaction system into a series of small independent processes that may be performed simultaneously.
  MTPC Uniqueness

Approaching multiprocessing from the business enterprise perspective, there are several levels by which processing could be sub-divided. These are by:

- (1) application, wherein certain applications are capable of being performed in parallel, such as e.g., Accounts Receivable, Accounts Payable, etc.
- (2) function, wherein certain functions within an application are capable of being performed in parallel, such as, e.g., updating customer profiles, customer status, or performance.
- (3) process, wherein certain large tasks are capable of being decomposed into smaller tasks that can be performed in parallel, such as, e.g., by splitting a large Accounts Receivable process, such as billing, into subcomponents.
- (4) transaction, wherein transactions are decomposed into subtransactions that are capable of being performed in parallel.

The value of MTCP is that it addresses the last form of multiprocessing which is believed to be the most critical to delivering rapid response times for real-time financial transaction processing systems. That is, by dividing a transaction into subtransactions that can be spread across several multiprocessors, processing throughput may be faster. Plus, the large number of small programs make maintenance much easier and less expensive.

A first embodiment of the transaction processing controller 52 is provided in the flowchart of FIG. 6. Note that for simplicity, error handling and related validity checking steps have been omitted. However, the performance of such steps is within the scope of the present invention, as one skilled in the art will appreciate. A second pseudo-code embodiment of the transaction processing controller 52 follows.



Pseudo-Code for the Command Processor
(Transaction Processing Controller 52)

BEGIN
/* The following switches are global. They control both the activity of the system.	*/
/* The Processor Switches monitors the availability of an eight processor computer.	*/
/* The Process Switches monitors all of the jobs that are to be executed.	*/
/* These switches initialize the system, and then change throughout processing	*/
/* as the subcomponents of the system and the processors finish.	*/
/* The Processor Switches are turned ON as jobs are sent to specific processors.	*/
/* The Processor Switches are turned OFF after the jobs are completed.	*/

Set Processor 1 Switch = 0

Set Processor 2 Switch = 0

Set Processor 3 Switch = 0

Set Processor 4 Switch = 0

Set Processor 5 Switch = 0

Set Processor 6 Switch = 0

Set Processor 7 Switch = 0

Set Processor 8 Switch = 0

Read Begin Time from Systems Clock into Working Storage

Set Total Records Read = 0

Set Number Accepts = 0

Set Number Rejects = 0

/* The Command Programs reads the transaction input from the operator, then	*/
/* edits the transaction for validity and loads the transaction processing algorithms	*/
/* from the Transaction Processing table (or cache file) to a temporary table. It then	*/
/* walks down all of algorithms in the temporary table to process the total transaction	*/
/* with 100% auditability. Each algorithm may be passed to a separate processor.

/* Read operator instructions for starting and ending item in input stream */

/* For the purposes of restart in the event of mid-stream job failure	*/
/* For the purpose of omissions in processing.	*/
/* Operator may enter Begin .......................... End for all items	*/
/* Operator may enter Begin ..... End for a beginning list	*/
/* Operator may enter Begin ..... End for an intermediate list	*/
/* Operator may enter Begin ..... End for an ending list	*/

Read Beginning Item in Input Stream from Master Control Terminal

Read Ending Item in Input Stream from Master Control Terminal

Set Beginning Item to Next Transaction

Set Ending Item to End of List

Read System Clock for Begin Time

Add Record with Begin Time

IF Error then

Message “No System Table Record for Begin Time”, Details

ENDIF

<<Read Next Transaction>>

/* The Process Switches are turned ON as each transaction subcomponent is completed. */

/* The Process Switches are turned OFF after the total transaction is completed. */

Set Process 1 Switch = 0

Set Process 2 Switch = 0

Set Process 3 Switch = 0

Set Process 4 Switch = 0

Set Process 5 Switch = 0

Set Process 6 Switch = 0

Set Process 7 Switch = 0

Set Process 8 Switch = 0

Set Process 9 Switch = 0

Set Process 10 Switch = 0

Set Process 11 Switch = 0

Set Process 12 Switch = 0

Set Process 13 Switch = 0

Set Process 14 Switch = 0

Set Process 15 Switch = 0

Set Process 16 Switch = 0

Set Process 17 Switch = 0

Set Process 18 Switch = 0

Set Process 19 Switch = 0

Set Process 20 Switch = 0

Set Process 21 Switch = 0

Set Process 22 Switch = 0

Set Process 23 Switch = 0

Set Process 24 Switch = 0

Read Next Transaction into Working Storage

IF EOF then

Read End Time from Systems Clock into Working Storage

INSERT End-time, Begin Time

Total Records Read, Number Accepts, Number Rejects

into Summary Table

IF Error then

Message “INSERT ST Table”, Details

STOP

ENDIF

Goto EOJ

ENDIF

IF Next Transaction = End of List

Goto EOJ

ENDIF

Increment Total Records Read

<<Test Transaction Type>>

IF Transaction Type != ‘ ‘ then

/* Set Switches for Trade Offset and Settle Offset Processing */

Set Process 1 Switch = 0

Set Process 2 Switch = 1

Set Process 3 Switch = 1

Set Process 4 Switch = 1

Set Process 5 Switch = 1

Set Process 6 Switch = 0

Set Process 7 Switch = 1

Set Process 8 Switch = 1

Set Process 9 Switch = 1

Set Process 10 Switch = 1

Set Process 11 Switch = 0

Set Process 12 Switch = 1

Set Process 13 Switch = 1

Set Process 14 Switch = 1

Set Process 15 Switch = 1

Set Process 16 Switch = 1

Set Process 17 Switch = 0

Set Process 18 Switch = 0

Set Process 19 Switch = 1

Set Process 20 Switch = 1

Set Process 21 Switch = 1

Set Process 22 Switch = 1

Set Process 23 Switch = 1

Set Process 24 Switch = 0

ENDIF

<<Test OORR>>

IF OORR = ‘O’ then

*****************

CALL N_gine EDIT

*****************

IF Edit Error

Message “Edit Error”, Details

Goto Write Reject Table

ENDIF

IF Tran-Type != ‘Sell’

OR Tran-Type != ‘Withdraw’ then

INSERT into Transaction Journal Table

IF Error

Message “Insert TJ Error”, Details

Goto Write Reject Table

ENDIF

IF Correction Data then

DELETE from Reject Table

IF Error

Message “Delete Reject Error”, Details

Goto Write Reject Table

ENDIF

*********

CALL TT ie., execute the algorithms in the temporary table

*********

IF Temporary Table Error then

Message “Temporary Table Error”, Details

Goto Write Reject Table

ENDIF

Generate Sequence Number

ELSIF OORR = ‘R’

*****************

CALL N_gine EDIT

*****************

IF Edit Error

Message “Edit Error”, Details

Goto Write Reject Table

ENDIF

Assign Transaction Number = ‘000000’

AssignLOT Number = 1

<<Read Next Reversal>>

Read Transaction Journal Table for reversal number

IF “No Transaction Exists” where LOT = 1 then

Message “No Transaction Exists”, Details

Goto Write Reject Table

ENDIF

IF “No Transaction Exists” and LOT > 1 then

Goto Transaction Wrap-up

ENDIF

IF Previously Reversed

Message “Previously Reversed”, Details

Goto Write Reject Table

ENDIF

INSERT Reversing Transaction” to Transaction Journal Table

IF Error

Message “INSERT TJ Reversing Error”, Details

Goto Write Reject Table

ENDIF

UPDATE “Reversed” Transaction

IF Error

Message “”UPDATE TJ Reversed Error”, Details

Goto Write Reject Table

ENDIF

Increment the LOT Number

*********

CALL TT i.e., execute the algorithms in the temporary table

*********

IF Temporary Table Error then

Message “Temporary Table Error”, Details

Goto Write Reject Table

ENDIF

Goto Read Next Reversal

Generate Sequence Number

UPDATE “Reversed” Transaction, ALL ROWS with Reversing Data

IF Error then

Message “UPDATE TL Table Reversed”, Details

Goto Write Reject Report

ENDIF

UPDATE “Reversing” Transaction, ALL ROWS with Reversed Data

IF Error then

Message “UPDATE TL Table Reversing”, Details

Goto Write Reject Report

ENDIF

ELSE

INSERT into Reject Table “No Originate or Reverse Code”

IF Error then

Message “Insert Reject Table”, Details

Goto Write Reject Table

ENDIF

<<Transaction Wrap-up>>

INSERT INTO Transaction Count Table

Select Original-Count and Reversal Count from TC Table into Working Storage

IF Error then

INSERT INTO TC Table, Details

IF Error then

Goto Write Reject Table

ENDIF

ELSE

IF AORS = ‘O’ then

Increment Original-Count

ELSIF AORS = ‘R’

Increment Reversal-Count

ELSE

Message “Invalid AORS Code”, Details

STOP

ENDIF

<<Test Trade Settlement>>

IF Transaction Switch = 2

Goto Loop Next Transaction

ENDIF

IF Transaction Switch = 1

OR AORS = ‘ ‘ then

Goto Loop Next Transaction

ENDIF

/* COMMIT Work to Database */

COMMIT Original Transaction Before Offset Transaction

IF AORS = ‘A’ then

Insert Licensee Trade Offset Buy in Transaction Identifier

ELSIF AORS = ‘S’

Insert Licensee Trade Offset Sell in Transaction Identifier

ELSE

Message “Invalid AORS”, Details

ENDIF

/* Swap Account Numbers for Automatic Transaction */

Move Account Number to Working Storage Account Number

Move Buyer/Seller Number to Account Number

Move Working Storage Account Number to Account Number

Multiply the Net Amount by −1

Multiply the Amount Units by −1

Add Number of Settlement Days from Entity Master to Trade Date to determine Settlement Date

Add to Total Number of Accepts

UPDATE Row in System Table for Number of Accepts

IF Error then

Message “Update Error for Accepts”, Details

Goto Write Reject Record

ENDIF

Go to Test Transaction Type

<<Loop Next Transaction>>

/* COMMIT Work to Database */

COMMIT Original Transaction or Offset Transaction, if any

Goto Read Next Transaction

<<Write Reject Record>>

Add to Total Number of Rejects

UPDATE Row in System Table for Number of Rejects

IF Error then

Message “Update Error for Rejects”, Details

ENDIF

INSERT Into Reject Table, Details

IF Error

Message “Insert Command Reject Table”, Details

STOP

ENDIF

Move Incoming Licensee Identifier to Stored Licensee Identifier

Move Incoming Account Identifier to Stored Account Identifier

Move Incoming Transaction Identifier to Stored Transaction Identifier

Move Incoming Entity Identifier to Stored Entity Identifier

Goto Read Next Transaction

<<EOJ>>

Read System Clock for End Time

Add Record with End Time

IF Error then

Message “No System Table Record for End Time”, Details

ENDIF

END

A first embodiment of the transaction preprocessor and decomposer 54 is provided in the flowcharts of FIGS. 7-A through 7-D and FIGS. 8-A and 8-B. Note that for simplicity, error handling and related validity check steps have been omitted. However, the performance of such steps is within the scope of the present invention, as one skilled in the art will appreciate.
A second pseudo-code embodiment of the transaction preprocessor and decomposer 54 follows.
Process the Detail Records Maintenance Routine (AORS)

Note: Leave all switches=1 until the last routine is completed. This forces the processing to loop through each succeeding routine until completed. Then turn set all switches=0 so that the Scheduler will revert back to the Command Program to read another transaction.



	<<Originate ADD>>
	IF OORR = ‘O’ and
	AORS = ‘A’ then

	IF	Process 1 Switch = 0 then
		Set Process 1 Switch = 1
		Initiate Process BS
	ELSIF	Process 2 Switch = 0 then
		Set Process 2 Switch = 1
		Initiate Process PI/PA
	ELSIF	Process 3 Switch = 0 then
		Set Process 3 Switch = 1
		Initiate Process TS
	ELSIF	Process 4 Switch = 0 then
		Set Process 4 Switch = 1
		Initiate Process PM
	ELSE
		Set Process 1 Switch = 0
		Set Process 2 Switch = 0
		Set Process 3 Switch = 0
		Set Process 4 Switch = 0
	ENDIF

	<<Reverse ADD>>
	ELSIF OORR = ‘R’ and
	AORS = ‘A’ then

	IF	Process 5 Switch = 0 then
		Set Process 5 Switch = 1
		Initiate Process BS
	ELSIF	Process 6 Switch = 0 then
		Set Process 6 Switch = 1
		Initiate Process PI/PA
	ELSIF	Process 7 Switch = 0 then
		Set Process 7 Switch = 1
		Initiate Process TS
	ELSIF	Process 8 Switch = 0 then
		Set Process 8 Switch = 1
		Initiate Process PM
	ELSE
		Set Process 5 Switch = 0
		Set Process 6 Switch = 0
		Set Process 7 Switch = 0
		Set Process 8 Switch = 0
	ENDIF

	<<Originate SUB>>
	ELSIF OORR = ‘O’ and
	AORS = ‘S’ then

	IF	Process 9 Switch = 0 then
		Set Process 9 Switch = 1
		Initiate Process BS
	ELSIF	Process 10 Switch = 0 then
		Set Process 10 Switch = 1
		Initiate Process PI/PA
	ELSIF	Process 11 Switch = 0 then
		Set Process 11 Switch = 1
		Initiate Process TS
	ELSIF	Process 12 Switch = 0 then
		Set Process 12 Switch = 1
		Initiate Process CG
	ELSIF	Process 13 Switch = 0 then
		Set Process 13 Switch = 1
		Initiate Process PM
	ELSE
		Set Process 9 Switch = 0
		Set Process 10 Switch = 0
		Set Process 11 Switch = 0
		Set Process 12 Switch = 0
		Set Process 13 Switch = 0
	ENDIF

	<<Reverse SUB>>
	ELSIF OORR = ‘R’ and
	AORS = ‘S’ then

	IF	Process 14 Switch = 0 then
		Set Process 14 Switch = 1
		Initiate Process BS
	ELSIF	Process 15 Switch = 0 then
		Set Process 15 Switch = 1
		Initiate Process PI/PA
	ELSIF	Process 16 Switch = 0 then
		Set Process 16 Switch = 1
		Initiate Process TS
	ELSIF	Process 17 Switch = 0 then
		Set Process 17 Switch = 1
		Initiate Process CG
	ELSIF	Process 18 Switch = 0 then
		Set Process 18 Switch = 1
		Initiate Process PM
	ELSE
		Set Process 14 Switch = 0
		Set Process 15 Switch = 0
		Set Process 16 Switch = 0
		Set Process 17 Switch = 0
		Set Process 18 Switch = 0
	ENDIF
	ENDIF

A first embodiment of the processing for the subtransaction processing module 64 is provided in the flowcharts of FIGS. 9-A through 9-B, FIGS. 10, 11, 12, 13 and 14. Note that for simplicity, error handling and related validity checking steps have been omitted. However, the performance of such steps is within the scope of the present invention, as one skilled in the art will appreciate.

A second pseudo-code embodiment of the transaction processing controller 52 follows.



Pseudo-Code for Processing for the Subtransaction Processing Module 64

BEGIN

DO WHILE List of Subtransactions in the TT Table is Valid

Select Next Row of Operator, Operand 1, and Operand 2 from TT into Working Storage

/*	To choose the specific input field (or column)	*/
IF	Operand 1 = ‘N’
	Set Value = Net Amount	from Input String
ELSIF	Operand 1 = ‘I’
	Set Value = Interest	from Input String
ELSIF	Operand 1 = ‘P’
	Set Value = Principal	from Input String
ELSIF	Operand 1 = ‘H’
	Set Value = Amount Units	from Input String
ELSIF	Operand 1 = ‘U’
	Set Value = Amount Units	from Input String
ELSIF	Operand 1 = ‘C’
	Set Value = Cost Basis	from Input String
ELSIF	Operand 1 = ‘V’
	Set Value = Amount Units * Curr Price	from Input String
ELSIF	Operand 1 = ‘F’

Set Value = Federal Taxes from Input String

ELSIF	Operand 1 = ‘S’
	Set Value = State Taxes	from Input String
ELSIF	Operand 1 = ‘L’
	Set Value = Local Taxes	from Input String
ELSIF	Operand 1 = ‘M’
	Set Value = Management Fees	from Input String
ELSE
	Message “Invalid Operand 1”, Details
ENDIF
/*	To ADjust for Plus or Minus	*/
IF	Operator = ‘P’ then
	Set Multiplier = +1
ELSIF	Operator = ‘M’ then
	Set Multiplier = −1
ENDIF
/*	To Adjust for Originate or Reversal	*/
IF	OORR = ‘O’ then
	Set Multiplier = Multiplier * +1
ELSIF	OORR = ‘R’
	Set Multiplier = Multiplier * −1
ENDIF

/* Test for Total Unit Changes

*/

	IF	Operand 2 = ‘TU’ then
		Add Value to AM - Total Units
		Add Value to EA - Total Units

/* Test for Income Cash Changes

*/

IF	Operand 2 = ‘IC’ then
	/* Add to First Controls - Account Master	*/
	Add Value to AM - Income Cash
	Add Value to AM - Units

	/* Add to Second Controls - Entity Attribute	*/
	Add Value to EA - Invested Income
	Add Value to EA - Units

/* Add to Third Controls - General Ledger

*/

	IF	Number of Entries = 1 then
		Add Value to GL - Income Cash
	ELSIF	Number of Entries = 2 then

IF

Value > 0 then

	IF	ICD >= 0 then
		Add Value	to GL - Income Cash Demand

ELSE

ICD < 0

		Add (Value - ICO)	to GL - Income Cash Demand
		Set Zero	to GL - Income Cash Overdraft

ENDIF

ELSIF

Value <= 0 then

IF	ICD < 0 then
	Add Value	to GL - Income Cash Overdraft
ELSE	ICD >= 0 then

	Add (Value - PCD)	to GL - Principal Cash Overdraft
	Set Zero	to GL - Principal Cash Demand

ENDIF

ELSE

Message “Invalid Value”, Details

	ENDIF
	- Add Value to Uninvested Principal

ELSE

Message “Invalid Number Entries”, Details

ENDIF

	/* Test for Principal Cash Changes	*/
	ELSIF Operand 2 = ‘PC’ then

	/* Add to First Controls - Account Master	*/
	Add Value to AM - Principal Cash
	Add Value to AM - Units

	/* Add to Second Controls - Entity Attribute	*/
	Add Value to EA - Invested Principal
	Add Value to EA - Units

/* Add to Third Controls - General Ledger

*/

	IF	Number of Entries = 1 then
		Add Value to GL - Principal Cash
	ELSIF	Number of Entries = 2 then

IF

Value > 0 then

IF	PCD >= 0 then
	Add Value	to GL - Principal Cash Demand
ELSE	PCD < 0
	Add Value	to GL - Principal Cash Demand
	Set Zero	to GL - Principal Cash Overdraft
ENDIF

ELSIF

Value <= 0 then

IF	PCD < 0 then
	Add Value	to GL - Principal Cash Overdraft
ELSE	PCD >= 0 then
	Add (Value - PCD)	to GL - Principal Cash Overdraft
	Set Zero	to GL - Principal Cash Demand
ENDIF

ELSE

Message “Invalid Value”, Details

ENDIF

ELSE

Message “Invalid Number Entries”, Details

	ENDIF
	Add Value to Uninvested Principal

/* Test for Invested Income Changes

*/

ELSIF

Operand 2 = ‘II’ then

	/* Add to First Controls - Account Master	*/
	Add Value to AM - Invested Income

	/* Add to Second Controls - Entity Attribute	*/
	Add Value to EA - Invested Income

/* Add to Third Controls - General Ledger

*/

/*

Update Assets

*/

Add Value to ACN- Assets

/*

Update Liabilities

*/

	IF	ACN-Liab = ‘ ‘ then
		Add Value to Invested Income
	ELSE
		Add Value to ACN_Liabilities
	ENDIF

/*	Test for Invested Principal Changes	*/
ELSE	Operand 2 = ‘IP’ then
	/* Add to First Controls - Account Master	*/
	Add Value to AM - Principal Cash

	/* Add to Second Controls - Entity Attribute	*/
	Add Value to EA - Invested Principal

/*

Add to Third Controls - General Ledger

*/

/*

Update Assets

*/

Add Value to ACN - Assets

/*	Update Liabilities	*/
IF	ACN_Liab = ‘ ‘ then
	Add Value to Invested Principal
ELSE
	Add Value to ACN_Liabilities
ENDIF

/* Test for Other Customized Reporting Changes

*/

	ELSIF	Operand 2 = ‘I’ and Report Request = ‘Y’
	OR	Operand 2 = ‘E’ and Report Request = ‘Y’ then

	(IEE)	Process IE
	(PME)	Process PM

	ELSIF	Operand 2 = ‘R’ and Report Request = ‘Y’
	OR	Operand 2 = ‘D’ and Report Request = ‘Y’ then

	(IEC)	Process RD
	(PMC)	Process PM

/* Test for other Performance Measurement Data

*/

ELSIF

Operand 2 = ‘PM’ and Report Request = ‘Y’ then

(PMP)

Process PM

	ELSIF	Operand 2 = ‘CN’
	OR	Operand 2 = ‘DN’ then

(CDC)

Process PM

ELSIF

Operand 2 = ‘MF’ then

(PMM)

Process PM

ELSIF

Operand 2 = ‘CM’ then

(PCM)

Process PM

ELSIF

Operand 2 = ‘FT’ then

(PMF)

Process PM

ELSIF

Operand 2 = ‘ST’ then

(PMS)

Process PM

ELSE

Message “Invalid Operand 2”, Details

ENDIF

/* Test for Detail Record Maintenance of Financial Instruments

*/

	IF	AORS != ‘ ‘ then
		***********
		CALL PORTFOLIO ADJUSTER 110
		***********

ENDIF

ENDDO

END



Pseudo-Code for Performance Measurement (PM)
Processing related to the Licensee
Performance Measurement Table 104

BEGIN

IF Trxn = ‘A’ and Type = ‘O’ OR Trxn = ‘S’ and

Type = ‘R’ (which means ADD)

SELECT Data into Working Storage from PM Record

IF Error then

INSERT INTO PM Record, Details

IF Error then

Message “INSERT PM Error”, Details

Goto Write Reject Report

ENDIF

ELSE

Increment Units by amount to be increased

UPDATE Data to Table / Row

IF Error

Message “UPDATE PM Error 1”, Details

Goto Write Report Error

ENDIF

ELSIF Trxn = ‘A’ and Type = ‘R’ OR Trxn = ‘S’ and Type = ‘O’

(which means SUBTRACT)

SELECT Data into Working Storage from PM Record

IF Error then

Message “ SELECT PM Error 2”, Details

Goto Write Report Error

ENDIF

IF Units = ‘ALL”

and All Other Balances in the Row are Zero then

DELETE from Table / Row

IF Error

Message “DELETE PM Error”, Details

Goto Write Report Error

ENDIF

ELSE

Decrement Units by Amount to be reduced

UPDATE PI SET Details

IF Error then

Message “UPDATE PM Error 2”, Details

Goto Write Report Writer

ENDIF

ELSE

Null

ENDIF

Goto EOJ

<<Write Reject Report>>

INSERT into Reject Table, Details

IF Error

STOP

ENDIF

<<EOJ>>

Null

END



Pseudo-Code for Income/Expense Processing (IE)
Processing related to the Customer Income Statement
(Income/Expense) Table 96

BEGIN

IF Trxn = ‘Debit’ and Type = ‘O’

(which means ADD)

OR Trxn = ‘Credit’ and Type = ‘O’ then

SELECT Data into Working Storage from IE Record

IF Error then

INSERT INTO IE Table, Details

IF Error then

Message “INSERT IE Error 1”, Details

Goto Write Report Error

ENDIF

ELSE

Increment Units by amount to be increased

UPDATE Data to Table/Row

IF Error then

Message “UPDATE IE Error 1”, Details

Goto Write Report Error

ENDIF

ELSIF Trxn = ‘Debit’ and Type = ‘R’

(which means SUBTRACT)

OR Trxn = ‘Credit’ and Type = ‘R’ then

SELECT Data into Working Storage from IE Record

IF Error then

Message “ SELECT IE Error 2”, Details

Goto Write Report Error

ENDIF

IF Units =‘ALL” then

DELETE from Table/Row

IF Error then

Message “DELETE IE Error”, Details

Goto Write Report Error

ENDIF

ELSE

Decrement Units by Amount to be reduced

UPDATE IE SET Details

IF Error then

Message “UPDATE IE Error 2”, Details

Goto Write Report Writer

ENDIF

ELSE

Null

ENDIF

Goto EOJ

<<Write Reject Report>>

INSERT into Reject Table, Details

IF Error then

STOP

ENDIF

<<EOJ>>

Null

END



Pseudo-Code for AORS Processing
(Portfolio Adjuster 110 Processing)

BEGIN

/* The End AORS Switch is a global switch that signals the end of all AORS processing	*/
/* otherwise known as the Detail Record (or Row) Maintenance Processing.	*/
/* The switch is originally set = 0. Each called routine ends by setting the switch = 1.	*/
Set End AORL Switch = 0
DO WHILE End AORS Switch = 0
IF Trxn = “ADD” then
IF Type = ‘O’ then
************

CALL Original Add Module 114	(Originate Add)
************
IF Error
Message “No OADD Routine”
Goto Write Reject Report
ENDIF
ELSIF Type = ‘R’ then
***********
CALL Reverse Add Module 118	(Reverse Add)
***********
IF Error
Message “NO RADD Routine”
Goto Write Reject Routine
ENDIF
ELSE

Message “Invalid O OR R Code for ADD”, Details

Goto Write Reject Report

ENDIF

ELSIF Trxn = ‘SUBTRACT’ then

IF Type = ‘O’ then

***********

CALL Original Sell Module 122	(Originate Subtract)
***********
IF Error then

Message “No OSUB Routine”, Details

Goto Write Reject Report

ENDIF

ELSIF Type = ‘R’ then

***********

CALL Reverse Sell Module 126	(Reverse Subtract)
***********
IF Error then

Message “No RSUB Routine, Details

Goto Write Reject Report

ENDIF

ELSE

Message “Invalid O OR R for SUBTRACT”, Details

Goto Write Reject Report

ENDIF

ELSE

Message “Invalid Transaction”, Details

Goto Write Reject Report

ENDIF

Goto EOJ

<<Write Reject Report>>

INSERT into Reject Table

IF Error then

STOP

ENDIF

Set End AORL Switch = 1

<<EOJ>>

Null

ENDDO

END

A first embodiment of the processing for the balance sheet table 130 is provided in the flowchart of Fig. BAL-SHT. Note that for simplicity, error handling and related validity checking steps have been omitted. However, the performance of such steps is within the scope of the present invention, as one skilled in the art will appreciate.

A second pseudo-code embodiment of the processing for the balance sheet table 130 follows.



N_gine File (or Table) Structure and
Likely Order of Creation
corresponding with FIGS. 4-A through 4-E

Institutional Profile		Data Source
LM	Licensee Master	User-Definable
LU	Licensee Users	User-Definable
LT	Licensee Account Type	User-Definable
LD	Licensee Default Definitions	User-Definable
LL	Licensee General Ledger Definitions	User-Definable
LS	Licensee Diversification Scheme	User-Definable
LP	Licensee Performance Group	User-Definable
LN	Licensee Summary Names	User-Definable
LW	Licensee Service Wholesalers	User-Definable
LR	Licensee Service Resellers	User-Definable
Customer Profile
AO	Account Objective	User-Definable
AL	Account Legal Capacity	User-Definable
AJ	Account Jurisdiction	User-Definable
AR	Account Representatives	User-Definable
AN	Account Registration Names	User-Definable
AM*	Account Master	User-Definable
AC	Account Communication Links	User-Definable
Transaction Profile
TM**	Transaction Master	User-Definable “Driving” File
TP**	Transaction Processor	User-Definable “Driving” File
TR	Transactions - Recurring	User-Definable “Driving” File
Entity Profile
EM	Entity Master	Public Market Data
EA*	Entity Attribute	User-Definable
ET	Entity Transaction	User-Definable
Licensee Status
SG*	System General Ledger	User-Definable
SJ*	System Transaction Journal	System Defined “Driven” File
ST	System Trade Settlement	System Defined “Driven” File
SS	System Summary Table	System Defined
SR	System Reject Table	System Defined
SC	System Transaction Count	System Defined
Customer Status
CS	Customer Income Statement (Income/Expense)	System Defined “Driven” File
CF	Customer Cash Flow (Receipts/Disbursements)	System Defined “Driven” File
CB*	Customer Balance Sheet	System Defined “Driven” File
CG	Customer Capital Gain	System Defined “Driven” File
CI	Customer Pending Income	System Defined “Driven” File
CA	Customer Pending Capital Adjustments	System Defined “Driven” File
CP*	Customer Performance Measurement	System Defined “Driven” File

Notes: * denotes Primary Control Tables

** denotes “Driving Tables”

TABLE DATA DESCRIPTIONS WITH EXAMPLES

(LM) Licensee Master

Primary Data consisting of

Licensee Identifier

Licensee Description

Trade Settlement Data consisting of

Licensee Trade Settlement Switch

Trade Offset Buy Identifier

Trade Offset Sell Identifier

Settle Offset Buy Identifier

Settle Offset Sell Identifier

+

Other Details

+

Audit Fields consisting of Processing Model 1

Add Date

Add Sequence Number

Add User Identifier

Change Date

Change Sequence Number

Change User Identifier

Delete Date

Delete Sequence Number

Delete User Identifier

Number of Modifications

Archive Status

Archive Date

Example:

Licensee	Licensee	Other Licensee	Licensee
Identifier	Description	Address	City/State/ZIP

LICN1	First Licensee Name	Main Street	Denver, CO
LICN2	Second Licensee Name	Broadway	New York, NY
LICN3	Third Licensee Name	Michigan Ave.	Chicago, IL

(LU) Licensee Users

Primary Date consisting of

Licensee Identifier

User Identifier

User Description

+

Other Details

+

Audit Fields consisting of Processing Model 1

Add Date

Add Sequence Number

Add User Identifier

Change Date

Change Sequence Number

Change User Identifier

Delete Date

Delete Sequence Number

Delete User Identifier

Number of Modifications

Archive Status

Archive Date

Example:

Licensee	User	User	Other User	User
Identifier	Identifier	Description	Address	City/State/ZIP

LICN1	FUN	First User Name	Lincoln Ave	Denver, CO
LICN2	SUN	Second User Name	Park Ave	New York, NY
LICN3	TUN	Third User Name	Montgomery	San Francisco, CA

(LT) Licensee Account Type

Primary Data consisting of

Licensee Identifier

Account Type Identifier

Account Type Description

+

Other Details

+

Audit Fields consisting of Processing Model 1

Add Date

Add Sequence Number

Add User Identifier

Change Date

Change Sequence Number

Change User Identifier

Delete Date

Delete Sequence Number

Delete User Identifier

Number of Modifications

Archive Status

Archive Date

Example:

Licensee	Account	Account
Identifier	Type Number	Type Name

LICN1	100	Pension Trust
LICN1	200	Investment Advisory
LICN1	300	Estates
LICN1	400	Settlements - Buy
LICN1	500	Settlements - Sell
LICN2	1000	Wireless Communications
LICN2	2000	Landline Communications
LICN2	3000	Satellite Broadcast
LICN3	9000	Domestic Subsidiary
LICN3	10000	Foreign Subsidiary

(LD) Licensee Default Definitions

Primary Data consisting of

Licensee Identifier

Default Class

Demand or Overdraft

Accounting Control Number

Accounting Control Number Description

Cash Record Pointer in EA Table

+

Other Details

+

Audit Fields consisting of Processing Model 1

Add Date

Add Sequence Number

Add User Identifier

Change Date

Change Sequence Number

Change User Identifier

Delete Date

Delete Sequence Number

Delete User Identifier

Number of Modifications

Archive Status

Archive Date

Example:

Licensee	Class	Sub-Class	Accounting	Accounting
Identifier	Iden	Iden	Control Number	Control Name

LICN1	IC	D	A01	Income Cash Demand
LICN1	IC	O	A02	Income Cash Overdraft
LICN1	IC	D	A03	Principal Cash Demand
LICN1	IC	O	A04	Principal Cash Overdraft
LICN1	UI		L05	Uninvested Income
LICN1	UP		L10	Uninvested Principal
LICN1	II		L15	Invested Income
LICN1	IP		L20	Invested Principal

(LL) Licensee General Ledger Definition

Primary Data consisting of

Licensee Identifier

Asset or Liability

Account Type Identifier

Account Type Description

+

Other Details

+

Audit Fields consisting of Processing Model 1

Add Date

Add Sequence Number

Add User Identifier

Change Date

Change Sequence Number

Change User Identifier

Delete Date

Delete Sequence Number

Delete User Identifier

Number of Modifications

Archive Status

Archive Date

(See Details Provided)

(LS) Licensee Diversification Scheme

Primary Data consisting of

Licensee Identifier

Diversification Type Identifier

Diversification Group Identifier

Diversification Class Identifier

Diversification Description

+

Other Details

+

Audit Fields consisting of Processing Model 1

Add Date

Add Sequence Number

Add User Identifier

Change Date

Change Sequence Number

Change User Identifier

Delete Date

Delete Sequence Number

Delete User Identifier

Number of Modifications

Archive Status

Archive Date

Example:

Licensee	Diversification	Diversification	Diversification	Diversification
Identifier	Type	Group	Class	Name

LICN1	100	000	000	Money Market Instruments
LICN1	100	100	000	US Govt Bills
LICN1	100	200	000	US Govt Notes
LICN1	100	300	000	Par Notes
LICN1	100	400	000	Discount Notes
LICN1	200	000	000	Fixed Income Securities
LICN1	200	100	000	US Govt Bonds
LICN1	200	200	000	Municipal Bonds
LICN1	200	300	000	Corporate Bonds
LICN1	200	400	000	Bond Funds
LICN1	300	000	000	Equities
LICN1	300	100	000	Preferred Stock
LICN1	300	200	000	Convertible Preferred
LICN1	300	300	000	Common Stock
LICN1	300	300	100	Automotive
LICN1	300	300	200	Building
LICN1	300	300	300	Chemical
LICN1	300	300	400	Drug
LICN1	300	400	000	Oil Partnerships
LICN1	300	500	000	Real Estate Partnerships
LICN2	100	000	000	Communication Services
LICN2	100	100	000	Wireless Communication
LICN2	100	200	000	Landline Communication
LICN2	100	300	000	Direct Satellite
LICN3	100	100	000	Cash
LICN3	100	200	000	Other Current Assets
LICN3	100	300	000	Fixed Assets
LICN3	100	400	000	Depreciation
LICN3	100	500	000	Other Tangible Assets
LICN3	100	600	000	Other Intangible Assets
LICN3	100	700	000	Current Liabilities
LICN3	100	800	000	Deferred Taxes
LICN3	100	900	000	Long-Term Debt
LICN3	100	1000	000	Net Worth

(LP) Licensee Performance Group

Primary Data consisting of

	Licensee Identifier
	Performance Type Identifier
	Performance Group Identifier
	Performance Class Identifier
	Performance Description
	+

Other Details

+

Audit Fields consisting of Processing Model 1

	Add Date
	Add Sequence Number
	Add User Identifier
	Change Date
	Change Sequence Number
	Change User Identifier
	Delete Date
	Delete Sequence Number
	Delete User Identifier
	Number of Modifications
	Archive Status
	Archive Date

Example:

Licensee	Perf Meas	Perf Meas	Perf Meas	Perf Meas
Identifier	Type	Group	Class	Name

LICN1	100	000	000	Money Market
LICN1	100	100	000	US Notes
LICN1	100	100	9710	Maturing October 1997
LICN1	100	100	9711	Maturing November 1997
LICN1	100	200	000	Par Notes
LICN1	100	200	9711	Maturing November 1997
LICN1	100	200	9712	Maturing December 1997
LICN1	200	000	000	Municipal Bonds
LICN1	200	AAA	000	Rated AAA
LICN1	200	AAA	9803	Maturing March 1998
LICN1	200	AAA	9806	Maturing June 1998
LICN1	300	000	000	Common Stock
LICN1	300	100	000	Durables
LICN1	300	100	100	Autos
LICN1	300	100	200	Appl
LICN1	300	200	000	Consumer Goods
LICN1	300	200	100	Food
LICN1	300	200	200	Beverage

(LN) Licensee Summary Names

Primary Data consisting of

	Licensee Identifier
	Summary Type Identifier
	Summary Number
	Summary Description
	+

Other Details

+

Audit Fields consisting of Processing Model 1

Example:

Licensee	Type	Group	Class	Summary Item
Identifier	Code	Code	Code	Name

LICN1	I	0001		Dividends - Ordinary
LICN1	I	0002		Dividends - Partially Tax-Exempt
LICN1	I	0003		Dividends - Tax-Free
LICN1	E	0001		Management Fees
LICN1	E	0004		Legal Expenses
LICN1	R	0001	I	Dividends
LICN1	R	0002	I	Interest - Net
LICN1	R	0007	P	Principal Contributions
LICN1	R	0008	P	Principal Sale Proceeds
LICN1	D	0001	I	Management Fees
LICN1	D	0009	P	Principal Disbursements

(LW) Licensee Service Wholesalers

Primary Data consisting of

	Licensee Identifier
	Wholesaler Identifier
	Wholesaler Address
	Number of Calls
	Value of Call
	+

Other Details

+

Audit Fields consisting of Processing Model 1

Example:

Licensee	Wholesaler	Wholesaler	Wholesaler	City/State/ZIP
Identifier	Identifier	Name	Address	Codes

LICN1	ABCD	AB Cellular Dealer	100 Main Street	Denver, CO
LICN1	RSTU	RS Telephone Utility	230 Broadway	NY, NY

(LR) Licensee Resellers

	Licensee Identifier
	Wholesaler Identifier
	Reseller Identifier
	Reseller Address
	+

Other Details

+

Audit Fields consisting of Processing Model 1

Example:

Licensee	Wholesaler	Reseller	Reseller	Reseller	City/State/ZIP
Identifier	Identifier	Identifier	Name	Address	Codes

LICN1	ABCD	123	123 Reseller	200 Oak	Tulsa, OK
LICN1	ABCD	234	234 Reseller	500 Elm	Okla City, OK
LICN1	RSTU	678	678 Reseller	300 Pine	Fresno, CA
LICN1	STUV	789	789 Reseller	700 Cedar	Pittsburgh, PA

(AO) Account Objective

Primary Data consisting of

	Licensee Identifier
	Objective Identifier
	Objective Description
	+

Other Details

+

Audit Fields consisting of Processing Model 1

Example:

Licensee	Objective	Objective
Identifier	Identifier	Name

LICN1	0100	Growth
LICN1	0200	Income
LICN1	0300	Growth with Income
LICN1	0400	Capital Preservation
LICN1	0500	High-Risk

(AL) Account Legal Capacity

Primary Data consisting of

	Licensee Identifier
	Legal Capacity Identifier
	Legal Capacity Description
	+

Other Details

+

Audit Fields consisting of Processing Model 1

Example:

Licensee	Legal Capacity	Legal Capacity
Identifier	Number	Name

LICN1	010	Trustee
LICN1	020	Broker
LICN1	030	Advisor
LICN1	040	Agent
LICN1	050	Escrow
LICN1	060	Executor
LICN1	070	Administrator

(AJ) Account Jurisdiction

Primary Data consisting of

	Licensee Identifier
	Jurisdiction Identifier
	Jurisdiction Description
	+

Other Details

+

Audit Fields consisting of Processing Model 1

Example:

Licensee	Jurisdiction	Jurisdiction
Identifier	Identifier	Name

LICN1	CA	California
LICN1	PA	Pennsylvania
LICN1	VI	Virgin Islands
LICN1	NA	Netherlands Antilles

(AR) Account Representative

Primary Data consisting of

	Licensee Identifier
	Account Representative Identifier
	Account Representative Name
	+

Other Details

+

Audit Fields consisting of Processing Model 1

Example:

Licensee	Representative	Representative
Identifier	Identifier	Name

LICN1	RR	Rhonda Red
LICN1	WW	Wanda White
LICN1	BB	Bill Brown
LICN	GG	Glenn Green

(AN) Account Registration Name

Primary Data consisting of

	Licensee Identifier
	Registration Identifier
	Registration Description
	+

Other Details

+

Audit Fields consisting of Processing Model 1

Example:

Licensee	Registration	Registration
Identifier	Identifier	Name

LICN1	AA	Able & Company
LICN1	BB	Baker & Company
LICN1	CC	Charlie & Company

(AM) Account Master

Primary Data consisting of

	Licensee Identifier
	Account Identifier
	Account Description
	Account Address
	Account Fiscal Year - MM
	Account Fiscal Year - DD
	Account Fiscal Year - Number of Periods
	Income Posting Code
	Account Type
	Account Objective
	Account Legal Capacity
	Account Jurisdiction
	Account Representative
	Account Registration Name
	Income/Expense Switch
	Receipts/Disbursement Switch
	Performance Measurement Switch
	Licensee Wholesaler
	Licensee Reseller
	Account Settlement Switch
	+

Other Details

+

System Control Data consisting of

	Income Cash
	Principal Cash
	Invested Income
	Invested Principal
	Total Units - Assets
	Liabilities
	Total Units - Liabilities
	+

Capital Gain Control Fields consisting of

	Total Units
	Total Cost Basis

System Control Fields consisting of

	Total Income
	Total Expense
	Total Receipts
	Total Disbursements
	+

Pending Income consisting of

	Total Units
	Total Cost Basis
	Total Pending Income
	+

Pending Cap Adj Out consisting of

	Cap Adj Out - Units
	Cap Adj Out - Cost Basis
	Cap Adj In - Units
	Cap Adj In - Cost Basis
	+

Audit Fields consisting of Processing Model 1

(AC) Account Communication Links

Primary Data consisting of

	Account Identifier
	Communications Number
	+

Other Details

+

Audit Fields consisting of Processing Model 1

Example:

Licensee	Account	Communications
Identifier	Identifier	Identifier

LICN1	123456	ATT-001
LICN1	123456	TCI-345
LICN1	234567	US-West
LICN1	234567	ATT-002
LICN1	234567	MCI
LICN1	456789	Sprint

(TM) Transaction Master

Primary Data consisting of

	Licensee Identifier
	Transaction Identifier
	Income Posting Code
	Transaction Description
	Add or Subtract Switch
	Settlement Transaction Identifier
	Terminate Settlement Switch
	+

Other Details

+

Audit Fields consisting of Processing Model 1

Example:

Licensee	Transaction	Income	Transaction
Identifier	Identifier	Posting Code	Name

LICN1	D01	I	Paid Management Fee
LICN1	D01	I	Paid Management Fee
LICN1	D01	I	Paid Management Fee
LICN1	SE	I	Sell Equity
LICN1	SE	P	Sell Equity
LICN1	SE	B	Sell Equity
LICN2	D01	P	Cellular Charge
LICN2	D02	P	Landline Charge
LICN2	D03	P	Direct Satellite Charge
LICN2	D04	P	America On-Line Charge

(TP) Transaction Processor

Primary Data consisting of

	Licensee Identifier
	Transaction Identifier
	Transaction Income Posting Code
	Transaction Process Description
	+

Other Details

+

Audit Fields consisting of Processing Model 1

	Add Date
	Add Sequence Number
	Add User Identifler
	Change Date
	Change Sequence Number
	Change User Identifier
	Delete Date
	Delete Sequence Number
	Delete User Identifier
	Number of Modifications
	Archive Status
	Archive Date

Example:

Licensee
Identifier	Transaction	Income
Suffix	Identifier	Posting Code	Operator	Operand 1	Operand 2

(TR) Transactions - Recurring

Primary Data consisting of

	Licensee Identifier
	Account Identifier
	Transaction Identifier
	Transaction Amount
	Begin Paying
	End Paying
	User Identifier
	+

Other Details

+

Audit Fields consisting of Processing Model 1

Example:

Licensee	Account	Transaction	Transaction	Begin	End	User
Identifier	Identifier	Identifier	Amount	Date	Date	Identifier

(EM) Entity Master

Primary Data consisting of

Entity Identifier

Entity Description

Asset or Liability Code

Settlement Days

+

Income Collection Data consisting of

Income Rate

Income Ex-Date

Income Record Date

Income Payment Date

+

Capital Adjustment Data consisting of

Capital Adjustment Rate

Capital Adjustment Ex-Date

Capital Adjustment Record Date

Capital Adjustment Payment Date

Capital Adjustment New Entity

+

Other Details

+

Audit Fields consisting of Processing Model 1

Add Date

Add Sequence Number

Add User Identifier

Change Date

Change Sequence Number

Change User Identifier

Delete Date

Delete Sequence Number

Delete User Identifier

Number of Modifications

Archive Status

Archive Date

(EA) Entity Attribute

Primary Data consisting of

Licensee Identifier

Entity Identifier

+

Management Decision-Making Data consisting of

Diversification Type

Diversification Group

Diversification Class

+

Performance Measurement Data consisting of

Performance Type

Performance Group

Performance Class

+

Accounting Data consisting of

Accounting Control Number - Asset

Accounting Control Number - Liability

+

System Control Data consisting of

Invested Income

Invested Principal

Total Units - Assets

Liabilities

Total Units - Liabilities

+

Settlement Data consisting of

Buy - In Units

Buy - Out Cost Basis

Sell - In Proceeds

Sell - Out Units

+

Other Details

+

Audit Fields consisting of Processing Model 1

Add Date

Add Sequence Number

Add User Identifier

Change Date

Change Sequence Number

Change User Identifier

Delete Date

Delete Sequence Number

Delete User Identifier

Number of Modifications

Archive Status

Archive Date

(ET) Entity Transaction

Primary Data consisting of

Licensee Identifier

Entity Identifier

Transaction Identifier

+

Other Details

+

Audit Fields consisting of Processing Model 1

Add Date

Add Sequence Number

Add User Identifier

Change Date

Change Sequence Number

Change User Identifier

Delete Date

Delete Sequence Number

Delete User Identifier

Number of Modifications

Archive Status

Archive Date

Example:

Licensee	Entity	Transaction
Identifier	Identifier	Identifier

LICN1	GM	BE
LICN1	GM	XO
LICN1	GM	XI

(SG) System General Ledger

Primary Data consisting of

Licensee Identifier

+

Control Fields consisting of

Asset or Liability

Account Type Identifier

Accounting Control Number

Account Balance

+

Other Details

+

Audit Fields consisting of Processing Model 1

Add Date

Add Sequence Number

Add User Identifier

Change Date

Change Sequence Number

Change User Identifier

Delete Date

Delete Sequence Number

Delete User Identifier

Number of Modifications

Archive Status

Archive Date

Example:

(See Details provided)

(SJ) System Transaction Journal

Primary Data consisting of

Licensee Identifier

Account Identifier

Transaction Identifier and either

Buys/Sells	or	Debits/Credits
Entity Identifier		Entity Identifier (if any)
Purchase Date		Principal
Amount Units		Income
Net Amount		Net Amount
Cost Basis (if Sell)

+

Other Details

+

Currency Fields consisting of

Currency Rate

Currency From

Currency To

Currency Date

+

Sell Data consisting of

Sell Date

Sell Price

Sell Proceeds

Sell Transaction Date

Sell Transaction Sequence Number

Sell Transaction Lot

Sell To

Capital Gain Amount

Capital Gain Period

+

Sell Currency Data consisting of

Sell Currency Rate

Sell Currency From

Sell Currency To

Sell Currency Date

+

Audit Fields consisting of Processing Model 2

Transaction Date

Transaction Sequence Number

Transaction Lot

Reversing Transaction Date

Reversing Sequence Number

Reversing Transaction Lot

Reversed By Transaction Date

Reversed By Transaction Sequence Number

Reversed By Transaction Lot

Trade Date

Archive Status

Archive Date

(ST) System Trade Settlement

Primary Data consisting of

Licensee Identifier

Account Identifier

Entity Identifier

Purchase Date

Amount Units

Cost Basis

Buyer/Seller

Trade Settlement Date

+

Currency Fields consisting of

Currency Ratio

Currency From

Currency To

Currency Date

+

Other Details

+

Transaction Date

Transaction Sequence Number

Transaction Lot

+

Audit Data consisting of

Add Date

Add User Identifier

Archive Status

Archive Date

(SS) System Summary Table

Primary Data consisting of

Licensee Identifier

Job Number

Job Name

Begin Time

End Time

Number of Accepts

Number of Rejects

Total Items

+

Audit Data consisting of

Add Date

Add User Identifier

Archive Status

Archive Date

Example:

Licensee	Job	Job	Begin	End	Total	Number	Number
Identifier	Number	Name	Time	Time	Transactions	Accepts	Rejects

(SR) System Reject Table

Primary Data consisting of

Licensee Identifier

Licensee Record

+

Audit Data consisting of

Add Date

Add User Identifier

Archive Status

Archive Date

Example:

License	Transaction
Identifier	Record

(SC) System Transaction Count

Primary Data consisting of

Licensee Identifier

Today's Date

Transaction Identifier

Transaction Count - Originate

Transaction Count - Reversal

+

Audit Data consisting of

Add Date

Add User Identifier

Archive Status

Archive Date

Example:

License	Transaction	Transaction	Transaction	Transaction
Identifier	Date	Identifier	Count - Orig	Count - Rev

(CS) Customer Income Statement (Income/Expense)

Primary Data consisting of

Licensee Identifier

Account Identifier

Fiscal Year - YYYY

Fiscal Year - Period

Income/Expense

Income/Expense Number

Income/Expense Balance

+

Audit Fields consisting of

Add Date

Add User Identifier

Archive Status

Archive Date

Example:

Licensee	Account	Fiscal	Fiscal	Inc/Exp	Inc/Exp	Inc/Exp
Identifier	Identifier	Year	Period	Identifier	Number	Balance

LICN1

(CF) Customer Cash Flow (Receipts/Disbursements)

Primary Data consisting of

Licensee Identifier

Account Identifier

Fiscal Year - YYYY

Fiscal Year - Period

Receipt/Disbursement

Receipt/Disbursement Number

Receipt/Disbursement Balance

+

Audit Fields consisting of

Add Date

Add User Identifier

Archive Status

Archive Date

Example:

Licensee	Account	Fiscal	Fiscal	Rec/Dis	Rec/Dis	Rec/Dis
Identifier	Identifier	Year	Period	Identifier	Number	Balance

LICN1

(CB) Customer Balance Sheet

Primary Data consisting of

Licensee Identifier

Account Identifier

Entity Identifier

Purchase Date

Amount Units

Cost Basis

+

Currency Data consisting of

Currency Rate

Currency From

Currency To

Currency Date

+

Other Details

+

Transaction Identification consisting of

Transaction Date

Transaction Sequence Number

Transaction Lot

+

Audit Fields consisting of

Add Date

Add User Identifier

Archive Status

Archive Date

(CG) Customer Capital Gains

Primary Data consisting of

Licensee Identifier

Account Identifier

Entity Identifier

Purchase Date

Amount Units

Cost Basis

Purchase Price

Buy From

+

Transaction Identification consisting of

Transaction Date

Transaction Sequence Number

Transaction Lot

+

Buy Currency Fields consisting of

Current Rate

Currency From

Currency To

Currency Date

+

Sell Data consisting of

Sell Date

Sell Price

Sell Proceeds

Sell Transaction Date

Sell Transaction Sequence Number

Sell Transaction Lot

Sell To

Capital Gain Amount

Capital Gain Period

+

Sell Currency Data consisting of

Sell Currency Rate

Sell Currency From

Sell Currency To

Sell Currency Date

+

Audit Fields consisting of

Add Date

Add User Identifier

Archive Status

Archive Date

(CI) Customer Pending Income

Primary Data consisting of

Licensee Identifier

Account Identifier

Entity Identifier

Purchase Date

Amount Units

Cost Basis

Purchase Price

+

Transaction Identification consisting of

Transaction Date

Transaction Sequence Number

Transaction Lot

+

Payment Date Data consisting of

Income - Ex-Date

Income - Record Date

Income - Payment Date

+

Audit Fields consisting of

Add Date

Add User Identifier

Archive Status

Archive Date

(CA) Pending Capital Adjustment

Primary Data consisting of

Licensee Identifier

Account Identifier

+

Pending Out Data consisting of

Entity Identifier (Old Entity)

Purchase Date

Transaction Identifier (Exchange Out)

Amount Units (Old Amount)

Cost Basis

Purchase Price

+

Transaction Identification consisting of

Transaction Date

Transaction Sequence Number

Transaction Lot

+

Pending In Data consisting of

Transaction Identifier (Exchange In)

Entity Identifier (New Entity)

Amount Units (New Amount)

+

Payment Date Data consisting of

Capital Adjustment - Ex-Date

Capital Adjustment - Record Date

Capital Adjustment - Payment Date

+

Audit Fields consisting of

Add Date

Add User Identifier

Archive Status

Archive Date

(CP) Customer Performance Measurement

Primary Data consisting of

Licensee Identifier

Account Identifier

Fiscal Year - YYYY

Fiscal Year - Period

Performance Measurement - Type

Performance Measurement - Group

Performance Measurement - Class

Beginning Value

Beginning Units

Contributions

Distributions

Income

Expenses

Management Fees

Commissions

Federal Taxes

State Taxes

Local Taxes

Ending Value

Ending Units

Ending Net Asset Value

+

Capital Gain Control Fields consisting of

Total Units

Total Cost Basis

System Control Fields consisting of

Total Income

Total Expense

Total Receipts

Total Disbursements

+

Pending Income consisting of

Total Units

Total Cost Basis

Total Pending Income

+

Pending Cap Adj Out consisting of

Cap Adj Out - Units

Cap Adj Out - Cost Basis

Cap Adj In - Units

Cap Adj In - Cost Basis

+

Audit Fields consisting of

Add Date

Add User Identifier

Archive Status

Archive Date

SAMPLE DATA FOR LICENSE GENERAL LEDGER

DEFINITION TABLE (LL)

Licensee	Asset	Accounting	Accounting
Identifier	or Liab	Control Number	Name

LICN1	A	A05	Municipal Bonds
LICN1	A	A07	Corporate Bonds
LICN1	A	A10	Common Stocks
LICN1	A	A12	Mutual Funds
LICN1	A	A13	International Currencies
LICN1	A	A15	Oil Partnerships
LICN1	A	A20	Real Estate Partnerships
LICN1	A	A30	Foreign Equities
LICN1	A	A35	Objects of Art
LICN1	A	A40	Jewelry
LICN1	A	A45	Homes
LICN	A	A50	Automobiles
LICN	A	A90	Derivatives
LICN2	A	W10	MSA/RSA - North
LICN2	A	W20	MSA/RSA - East
LICN2	A	W30	MSA/RSA - South
LICN2	A	W40	MSA/RSA - West
LICN2	A	L10	Alabama
LICN2	A	L20	Alaska
.		.	.
.		.	.
.		.	.
LICN2	A	L500	Wyoming
LICN2	A	S10	Major Market	1
LICN2	A	S20	Major Market	2
LICN2	A	S30	Major Market	3
.		.	.
.		.	.
.		.	.
LICN2	A	S1000	Major Market N
LICN3	A	C10	Cash
LICN3	A	C20	Other Current Assets
LICN3	A	C30	Fixed Assets
LICN3	A	C40	Depreciation
LICN3	A	C50	Intangible Assets
LICN1	L	L05	Uninvested Income
LICN1	L	L10	Invested Income
LICN1	L	L15	Uninvested Principal
LICN1	L	L20	Invested Principal
LICN1	L	L30	Personal Notes
LICN1	L	L40	Mortgages
LICN1	L	L90	Income
LICN1	L	L60	Short-Term Liabilities
LICN1	L	L65	Deferred Taxes
LICN1	L	L70	Long-Term Liabilities
LICN1	L	L75	Net Worth

SAMPLE DATA FOR SYSTEM GENERAL LEDGER TABLE

	Asset		Accounting
Licensee	or	Account	Control	Accounting
Master	Liab	Type	Number	Name

LICN1	A	000	000	Financial Services Assets
LICN1	A	100	000	Pension Trust
LICN1	A	100	A01	Income Cash Demand
LICN1	A	100	A02	Income Cash Overdraft
LICN1	A	100	A03	Principal Cash Demand
LICN1	A	100	A04	Principal Cash Overdraft
LICN1	A	100	A07	Corporate Bonds
LICN1	A	100	A10	Common Stocks
LICN1	A	100	A15	Oil Partnerships
LICN1	A	100	A20	Real Estate Partnerships
LICN1	A	100	A30	Foreign Equities
LICN1	A	200	000	Investment Advisory
LICN1	A	200	A01	Income Cash Demand
LICN1	A	200	A02	Income Cash Overdraft
LICN1	A	200	A03	Principal Cash Demand
LICN1	A	200	A04	Principal Cash Overdraft
LICN1	A	200	A05	Municipal Bonds
LICN1	A	200	A07	Municipal Bonds
LICN1	A	200	A10	Common Stocks
LICN1	A	200	A12	Mutual Funds
LICN1	A	200	A13	International Currencies
LICN1	A	200	A15	Oil Partnerships
LICN1	A	200	A20	Real Estate Partnerships
LICN1	A	100	A30	Foreign Equities
LICN1	A	100	A90	Financial Derivatives
LICN1	A	300	000	Estates
LICN1	A	300	A01	Income Cash Demand
LICN1	A	300	A02	Income Cash Overdraft
LICN1	A	300	A03	Principal Cash Demand
LICN1	A	300	A04	Principal Cash Overdraft
LICN1	A	300	A05	Municipal Bonds
LICN1	A	300	A07	Corporate Bonds
LICN1	A	300	A10	Common Stocks
LICN1	A	300	A12	Mutual Funds
LICN1	A	300	A15	Oil Partnerships
LICN1	A	300	A20	Real Estate Partnerships
LICN1	A	300	A30	Foreign Equities
LICN1	A	300	A35	Objects of Art
LICN1	A	300	A40	Jewelry
LICN1	A	300	A40	Homes
LICN1	A	300	A50	Automobiles
LICN1	A	400	000	Settlement Accounts - Buy
LICN1	A	400	A01	Income Cash Demand
LICN1	A	400	A02	Income Cash Overdraft
LICN1	A	400	A03	Principal Cash Demand
LICN1	A	400	A04	Principal Cash Overdraft
LICN1	A	400	A05	Corporate Bonds
LICN1	A	400	A07	Municipal Bonds
LICN1	A	400	A10	Common Stocks
LICN1	A	400	A15	Oil Partnerships
LICN1	A	400	A20	Real Estate Partnerships
LICN1	A	400	A30	Foreign Equities
LICN1	A	500	000	Settlement Accounts - Sell
LICN1	A	500	A01	Income Cash Demand
LICN1	A	500	A02	Income Cash Overdraft
LICN1	A	500	A03	Principal Cash Demand
LICN1	A	500	A04	Principal Cash Overdraft
LICN1	A	500	A05	Corporate Bonds
LICN1	A	500	A07	Municipal Bonds
LICN1	A	500	A10	Common Stocks
LICN1	A	500	A15	Oil Partnerships
LICN1	A	500	A20	Real Estate Partnerships
LICN1	A	500	A30	Foreign Equities
			(AND/OR)
LICN2	A	1000	000	Communication Assets
LICN2	A	1000	W00	Wireless Communications
LICN2	A	1000	W10	MSA/RSA - North
LICN2	A	1000	W20	MSA/RSA - East
LICN2	A	1000	W30	MSA/RSA - South
LICN2	A	1000	W40	MSA/RSA - West
LICN2	A	2000	L00	Landline Communications
LICN2	A	2000	L10	Alabama
LICN2	A	2000	L20	Alaska
.				.
.				.
.				.
LICN2	A	2000	L500	Wyoming
LICN2	A	3000	S00	Satellite Broadcast
LICN2	A	3000	S10	Major Market	1
LICN2	A	3000	S20	Major Market	2
LICN2	A	3000	S30	Major Market	3
.				.
.				.
.				.
LICN2	A	3000	S1000	Major Market 4
			(AND/OR)
LICN3	A	0000	000	Corporate Assets
LICN3	A	9000	000	Domestic Subsidiary
LICN3	A	9000	C10	Cash
LICN3	A	9000	C20	Other Current Assets
LICN3	A	9000	C30	Fixed Assets
LICN3	A	9000	C40	Depreciation
LICN3	A	9000	C50	Intangible Assets
LICN3	A	9000	000	Foreign Subsidiary
LICN3	A	9000	C10	Cash
LICN3	A	9000	C20	Other Current Assets
LICN3	A	9000	C30	Fixed Assets
LICN3	A	9000	C40	Depreciation
LICN3	A	9000	C50	Intangible Assets
LICN1	L	000	000	Financial Services Liabilities
LICN1	L	100	000	Pension Trust
LICN1	L	100	L15	Uninvested Principal
LICN1	L	100	L20	Invested Principal
LICN1	L	200	000	Investment Advisory
LICN1	L	200	L05	Uninvested Income
LICN1	L	200	L10	Invested Income
LICN1	L	200	L15	Uninvested Principal
LICN1	L	200	L20	Invested Principal
LICN1	L	300	000	Estates
LICN1	L	300	L05	Uninvested Income
LICN1	L	300	L10	Invested Income
LICN1	L	300	L15	Uninvested Principal
LICN1	L	300	L20	Invested Principal
LICN1	L	300	L30	Personal Notes
LICN1	L	300	L40	Mortgages
LICN1	L	400	000	Settlement - Buy
LICN1	L	400	L15	Uninvested Principal
LICN1	L	400	L20	Invested Principal
LICN1	L	500	000	Settlement - Buy
LICN1	L	500	L15	Uninvested Principal
LICN1	L	500	L20	Invested Principal
			(AND/OR)
LICN2	L	1000	000	Communications
LICN2	L	1000	000	Wireless
LICN2	L	1000	L90	Income
LICN2	L	2000	000	Landline
LICN2	L	2000	L90	Income
LICN2	L	3000	000	Satellite Broadcast
LICN2	L	3000	L90	Income
			(AND/OR)
LICN3	L	9000	000	Domestic Subsidiary
LICN3	L	9000	L60	Short-Term Liabilities
LICN3	L	9000	L65	Deferred Taxes
LICN3	L	9000	L70	Long-Term Liabilities
LICN3	L	9000	L75	Net Worth
LICN3	L	9000	000	Foreign Subsidiary
LICN3	L	9000	L60	Short-Term Liabilities
LICN3	L	9000	L65	Deferred Taxes
LICN3	L	9000	L70	Long-Term Liabilities
LICN3	L	9000	L75	Net Worth

A Standardized Method for Naming the Programs (or SQL Scripts) and Data Elements of Real-time

Multiprocessed Automated Applications

The specific invention is a standardized file naming convention to be used in the automatic generation of program code for multiple large-scale transaction processing applications (such as securities trading, telecommunications billing, and work management) on multi-processing computers (using 4, 8, 16, 32 processors) with 100% auditability of user-defined controls. The standardized file naming convention is totally independent of any specific
a.) application such as accounts receivable, customer billing, etc.,
b.) industry such as financial services, telecommunications, or work management,
c.) hardware manufacturer such as Compaq, Digital, HP, IBM, NCR, Unisys,
d.) operating system such as MS-DOS, UNIX, OpenVMS, MVS, etc.,
e.) relational database management system such as Oracle, Sybase, MS-SQL Server,
f.) computer language such as SQL, COBOL, Fortran, PL/l, etc.
The standard naming convention contains the fewest number of characters in any naming conventions; namely, eleven characters used by MS-DOS. The naming convention of MS-DOS uses eight characters as a file name and three characters as a file extension wherein the user may define a file name using the alphabet and selected other characters. While this flexibility is suitable for home use are a small number of files and users, it is not acceptable for large-scale enterprise-wide applications with large number of files and large number of supporting technicians. Hence, the need for enterprise-wide standards.
The standard file naming convention contains six elements that permit the technician to readily identify the functionality of the specific script (or program) without looking at its contents. Using ANSI Standard structured Query Language as an example language, the six elements are:

a.) a 2-character mnemonic for the SQL commands such as:



Mnemonic	ANSI Standard SQL Commands

CT	Create Table
SF	Select From Table
DF	Delete From
DT	Drop Table
II	Insert Into
SI	Select Into
CS	Create Sequence
DS	Drop Sequence
CI	Create Index
DI	Drop Index
RV	Review
RT	Retest
RS	Reset, etc.

b.) a 2-character mnemonic for the application name such as

Mnemonic User Defined Application Name Examples

ST Securities Trading

TC Telecommunications Billing

WM Work Management, etc.
c.) a 2-character mnemonic for the table (or file name) such as

Mnemonic User-Defined Table Name Examples

AM Account Master Name/Address/Etc.

SM Securities Master

DC Detail Calls

XB External Billing, etc.
d.) a 1-character mnemonic for the table cluster role such as

Mnemonic Standard Table Roles

M Master

I Input

A Accepts

R Rejects

H History

S Summary

1 Master History

2 Accepts History

O Output
e.) a 1-character mnemonic for the table cluster type such as

Mnemonic Standard Table Types

M Master

J Journal

T Temporary

1-9 Index Numbers

f.) a 3-character extension is then added to the file name depending upon
the type of operating system being used such as MS-DOS, UNIX, OpenVMS, etc. and
whether or not the file is a source file for programmer use or a compiled file (or stored procedure) for machine use.
Hence, script name examples are:
CTXBMDMM.SQL—Create Table for the External Billing System, Master Definition Table Cluster, Master Table, and Master Role for SQL use.
DTXBDCOJ.SQL—Drop Table for the External Billing System, Detail Call Cluster, Output Table, and Journal Role for SQL use.
Circumstances Leading to the Invention
The circumstances leading to the invention of a standard SQL script naming convention are:
a.) one programmer will rarely adhere to the same naming conventions over time and unless an acceptable standard is defined each succeeding programmer added to the job will only complicate the issue by bringing their own standards. Hence, software maintenance becomes a matter of knowing which programmer wrote which program at what time.
b.) without a naming standard any programmer has no idea of what functions the programming is performing without opening the program and examining the program code. This process produces create inefficient maintenance by existing programmers and inefficient training for new programmers.
c.) Competitive pressures are mounting for the efficient of software maintenance.

ADVANTAGE OF THE INVENTION

Because no duplicate script names are permitted the name of each SQL Script should
a.) convey to the user the precise use of each SQL Script and
b.) permit the storage of all SQL scripts in a one SQL Script Library, or directory.
A standard naming convention also permits the user to determine what scripts may be automatically executed in sequence by use of a SQL command script, which is a single SQL-script containing a list of SQL scripts to be executed in sequence. Hence, any single SQL scripts contained in the SQL Library can be reused in many different SQL command scripts.
Although any standard naming convention represents a unique entity separate and apart from the other technologies described immediately above, this particular naming convention is unique in that it embraces all of the logical information necessary to readily identify the role of the script in the total system.

DETAILED DESCRIPTION OF INVENTION

std_name is a standard naming convention that constructs names for programs (or SQL Scripts), system tables, table clusters, and data elements. The seven basic elements are:



1.)	org_name	Organization		2
2.)	com_name	SQL Command		2
3.)	app_name	Application		2
4.)	tab_name	Table	2
5.)	rol_name	Table Role		1
6.)	typ_name	Table Type		1
7.)	col_name	Column (or Field)	4

std_name defines both “external” names used by the operating system and “internal” names used by the specific program.
The “external” resulting names are:

1.) clu_name Cluster Name 4

2.) sys_name System Table Name 6

3.) ext_name Extension Name 3

4.) sql_name SQL Script Name 11

(8 name plus 3 extension)
where the SQL Script Names are used by the operating systems.
The “internal” resulting names are:

1.) tab_iden Table Iden Name 4

2.) col_name Column (or Field) Name 4

3.) dat_name Data Element Name 8 or more, in

increments of 4
where the Data Element Names are used by the programs (or SQL Scripts).

External Names used by the operating system in identifying programs (or SQL Scripts) are created by employing the following naming components:



	com_name SQL Command Mnemonic
	app_name Application Name Mnemonic
	tab_name Table Name Mnemonic
	rol_name Table Role Name Mnemonic
	tab_name Table Type Name Mnemonic
	ext_name Extension Mnemonic

1

2

3

4

5

6

7

8

.

9

10

11

Examples:

C

T

X

B

M

D

M

.

S

Q

L

S

F

X

B

M

D

M

.

S

Q

L

	clu_name
	tab_iden
	sys_name ext_name
	sql_name

Internal Names used by the program (or SQL Script) in processing the data elements are created by employing the following naming components:



5	6	7	8

tab_name

Table Name Mnemonic

rol_name

Role Name Mnemonic

typ_name

Type Name Mnemonic

col_name

Column Name

Examples:	M	D	M	M	LNAM	. . . for last name
	M	D	M	M	FNAM	. . . for first name
	M	D	M	M	MNAM	. . . for middle name
	M	D	M	M	ADR1	. . . address - 1st line
	M	D	M	M	ADR2	. . . address - 2cd line.
	M	D	M	M	CITY	. . . city
	M	D	M	M	STAT	. . . state
	M	D	M	M	ZIPC	. . . zip code

	dat_name

Data Tracing

By addressing both the external names for the operating system and the internal names for a specific program, the naming convention is global in nature. In the event that one data element derives its source of input from another table rather than its own specific input screen, then the data name is extended by placing the table identifier of the table supplying the data between the first four and second four characters of the intended data name. Should the data be derived from another table that also derived its data from another table, then eight characters are placed between the first four characters and the last four characters of the intended data name. In the fashion, the data name points backwards through all of the preceding tables to the original source of data and its input form. This process is called “data tracing”, and it provides benefits to programmers in the testing and debugging stages of software development by identifying the original source of data. Thus, “data tracing” provides the programmer with thorough documentation of the data flow throughout an entire system.
Standard naming conventions do not apply to certain language extensions such as the script footings that, for example, specify the size of the table to be created in a “Create Table” script.
The foregoing discussion of the invention has been presented for purposes of illustration and description. Further, comments and description is not intended to limit the invention to the form disclosed herein. Consequently, variation and modification commensurate with the above teachings, and within the skill and knowledge of the relevant art, are within the scope of the present invention. The embodiment described herein above is further intended to explain the best mode presently known of practicing the invention and to enable others skilled in the art to utilize the invention as such, or in other embodiments, and with the various modifications required by their particular application or uses of the invention. It is intended that the appended claims be construed to include alternative embodiments to the extent permitted by the prior art.

Claims

1-26. (canceled)

27. A method for processing a financial transaction on a computing system using a plurality of processors comprising:

retrieving, in response to a request to perform a financial transaction having a transaction identifier and input values, a unique subset of user-defined algorithms from a set of user-defined algorithms, wherein the unique subset is associated with the transaction identifier via a user-defined transaction processing table, each user-defined algorithm, when executed by a processor on the input values, creates or changes a data record such that the unique subset of user-defined algorithms associated with the transaction identifier, when executed using the input values, creates or changes data records stored in a database as necessary to process the financial transaction;

executing each of the user-defined algorithms of the unique subset on the input values;

wherein the unique subset of algorithms are executed concurrently on different processors and the financial transaction is considered processed when all algorithms in the unique subset of user-defined algorithms have been executed on the input values.

28. The method of claim 27, wherein each request further includes a licensee identifier and the set of user-defined algorithms is further associated with the licensee identifier.

29. The method of claim 27, wherein executing each of the user-defined algorithms of the unique subset on the input values comprises:

executing a user-defined algorithm that creates a data record in a transaction journal file; executing a user-defined algorithm that changes a data record in a general ledger master table;

executing a user-defined algorithm that changes a data record in an account master table; and

executing a user-defined algorithm that changes a data record in an entity attribute master table.

30. The method of claim 27 further comprising:

generating a transaction sequence number for the retrieved request to perform a financial transaction.

31. The method of claim 29, wherein executing each of the user-defined algorithms of the unique subset on the input values comprises:

executing a user-defined algorithm that creates, changes or deletes a data record in a cash flow table;

executing a user-defined algorithm creates, changes or deletes a data record in an income statement table;

executing a user-defined algorithm that creates, changes or deletes a data record in a capital gains table;

executing a user-defined algorithm that creates, changes or deletes a data record in a balance sheet table; and

executing a user-defined algorithm that creates, changes or deletes a data record in a performance measurement table.

32. The method of claim 27, further comprising:

if the transaction identifier is not associated with a unique subset of user-defined algorithms from the set of user-defined algorithms, writing the request to perform the financial transaction to a system reject table.

33. The method of claim 27 further comprising:

if one of the algorithms fails to execute,

reversing all algorithms of the unique subset that did execute; and

writing the request to perform the financial transaction to a system reject table.

34. The method of claim 27 wherein each of the unique subset of algorithms is executed concurrently on a different one of the plurality of processors.

35. The method of claim 27 wherein at least one of the unique subset of algorithms is executed on a first processor concurrently with the execution of at least one algorithm of a different unique subset of algorithms on a different processor.

36. The method of claim 27 wherein at least one of the unique subset of algorithms is executed on a first processor concurrently with the execution of at least two algorithms of different unique subsets of algorithms on different processors.

37. A method for processing financial transactions on a multiprocessing machine having a plurality of processors, each financial transaction having financial transaction data, the method comprising:

maintaining a set of user-defined algorithms, each user-defined algorithm being independently and simultaneously processable by anyone of the plurality of processors in the multiprocessing machine and each user-defined algorithm when processed on financial data adds, changes or deletes only one financial data record based on the financial data;

receiving a first financial transaction having a first user-defined financial transaction type and first financial data;

identifying, for the first financial transaction, a first unique subset of user-defined algorithms from a set of user-defined algorithms based on the first user-defined financial transaction type;

processing each user-defined algorithm in the first unique subset of user-defined algorithms on the first financial data;

receiving a second financial transaction having a second user-defined financial transaction type and second financial data;

identifying, for the second financial transaction, a second unique subset of user-defined algorithms from the set of user-defined algorithms based on the second user-defined financial transaction type;

processing each user-defined algorithm in the second unique subset of user-defined algorithms on the second financial data; and

wherein all the user-defined algorithms in the first unique subset of user-defined algorithms on the first financial data and at least one of the second unique subset of user-defined algorithms are concurrently processed.

38. The method of claim 37, wherein each user-defined algorithm changes only one financial data record in only one user-defined financial report and includes an operator, a first operand that identifies input data from the financial transaction data, and a second operand that identifies the only one data record.

39. The method of claim 37 further comprising:

maintaining a user-defined transaction processing table that associates each user-defined transaction type with a unique subset of the set of user-defined algorithms including associating the first unique subset of user-defined algorithms with the first user-defined financial transaction type and the second unique subset of user-defined algorithms with the second user-defined financial transaction type.

40. The method of claim 37, wherein processing each unique subset of the set of user-defined algorithms associated with a user-defined transaction type comprises:

executing a user-defined algorithm on a first processor that creates a data record in a transaction journal file;

concurrently executing a user-defined algorithm on a second processor that changes a data record in a general ledger master table;

concurrently executing a user-defined algorithm on a third processor that changes a data record in an account master table; and

concurrently executing a user-defined algorithm on a fourth processor that changes a data record in an entity attribute master table.

41. The method of claim 37 further comprising:

wherein at least one of the second unique subset of user-defined algorithms is completed prior to completion of processing all the user-defined algorithms in the first unique subset of user-defined algorithms.

42. The method of claim 37 further comprising:

receiving the second financial transaction after receiving the first financial transaction; and

completing processing of all of the user-defined algorithms in the second unique subset of user-defined algorithms prior to completing the processing of all of the user-defined algorithms in the first unique subset of user-defined algorithms.

43. A financial transaction multiprocessing system for an enterprise, each financial transaction having a financial transaction type and financial transaction data, comprising:

a multiprocessing computer having a plurality of processors;

a financial record database storing financial data records;

a database manager for creating, changing and deleting financial data records;

a queue for receiving financial transactions for processing, wherein each financial transaction when processed results in adding, changing or deleting to at least one financial data record and wherein each financial transaction is associated with one of a plurality of user-defined financial transaction types and includes financial transaction data;

an algorithm database storing a set of user-defined algorithms, each user-defined algorithm capable of being processed concurrently and independently with any other user-defined algorithm and each user-defined algorithm when processed by anyone of the plurality of processors causing the database manager to add, change or delete a financial data record; and

a transaction processing table that associates each user-defined transaction type with a unique subset of the set of user-defined algorithms such that processing a first financial transaction having a first financial transaction type and first financial transaction data is achieved by processing a first unique subset of user-defined algorithms associated with the first financial transaction type on the first financial transaction data.

44. The financial transaction multiprocessing system of claim 43 further comprising:

a set of control tables;

a set of user-defined control algorithms, each user-defined control algorithm when processed causing the database manager to add, change or delete one or more data records in one or more control tables; and

wherein the transaction processing table further associates one or more user-defined control algorithms with each user-defined financial transaction type.

45. The system of claim 43 further comprising:

a processor queue for user-defined algorithms, the processor queue distributing queued user-defined algorithms to processors as the processors become available.

46. The system of claim 43, wherein each user-defined algorithm includes only one operator and only a first operand and a second operand, the first operand identifying input data from the financial transaction data of the financial transaction to be processed, and the second operand identifying the only one data record.