WO2010096859A1

WO2010096859A1 - Method and system for providing financial advice

Info

Publication number: WO2010096859A1
Application number: PCT/AU2010/000168
Authority: WO
Inventors: Andrew Blair; Nikesh Lalchandani; Ranadeva Peries
Original assignee: Smart Wealth Tips Pty Ltd
Priority date: 2009-02-26
Filing date: 2010-02-17
Publication date: 2010-09-02

Abstract

A computer-implemented method and system for providing financial advice and the like using recommendation centric analysis, progressive data collection, and recommendation based parameterised expressions to common equations that calculate financial benefit. The present invention addresses some challenges faced in the financial industry with the process of providing advice, particularly providing efficient, accessible, quality advice without excessive upfront data capture. By taking a recommendation centric approach to the calculation and analysis of benefit, progressive data capture, and other techniques, the present invention in one aspect is able to reduce the amount of data capture required upfront. In another aspect, a generalised way of expressing potential recommendations simplifies extending and maintaining the advice process, and a greater range of financial advice can be offered. Potential recommendations share a standard set of equations which can be applied to financial instruments/products. In a further aspect, calculating and presenting the output as self contained recommendation units provides an interactive model that can be used directly by parties seeking financial advice.

Description

Description Title of Invention: METHOD AND SYSTEM FOR PROVIDING

FINANCIAL ADVICE

Summary of the Invention

[1] The present invention provides a computer-implemented method of:

1. collecting data from a party for whom financial advice is to be provided,

2. applying potential recommendations to said data,

3. simulating the calculated benefit of potential recommendations through application of said data, and

4. displaying the recommendations that have the optimal benefit to the party as output.

[2] One aspect of the present invention is that many of the potential recommendations are expressed in a standard form, and act on the profile of the party. Potential recommendations share a standard set of equations which can be applied to financial instruments/products. By associating most of the validation rules, attributes and parameters of calculation with the recommendation (rather than with a central process), each recommendation becomes substantially self contained. This makes it easy to create and modify potential recommendations, and easier for a party to try or reject a potential recommendation. Some of the potential recommendations have calculations that may be applied by using a specific algorithm, all of the potential recommendations include qualification rules (rules that enable a recommendation to be presented for the party), and information content - additional information about recommendations.

[3] Another aspect of the present invention is that potential recommendations may be grouped and nested. A particular financial instrument for example may be provided by several providers - these may have their own rules and would behave differently from the others, but could all be nested under a parent potential recommendation. The party is able to select and refine recommendations based on personal decisions. The profile may be enhanced progressively by the party to provide more (or alternative) information and the simulation may be re-run. Technical Field

[4] The present invention relates to a computer- implemented method and system for providing financial advice to various parties. Disclosure of Invention Technical- Problem

[5] An efficient implementation of the financial advice process would be impaired by issues including: 1. The quality of advice requires that a great deal of information about the party be known,

2. The advice is difficult for the party to understand,

3. There is limited feedback to the party, it is difficult or inconvenient to alter or represent options, and

4. The number of options or potential recommendations is increasing, this is due to new products, changing government (and taxation) laws and policy, and changing markets - this renders a system obsolete unless it is quickly and easily changed.

Technical- Solution

[6] The present invention endeavours to address the technical problems in providing financial advice by measures including:

1. Providing advice on a minimal amount of information, and progressively improving said advice by obtaining more data as recommendations are presented, and interactions increase,

2. Grouping the result as recommendations and comparing the recommendations with each other, so that the party is able to understand the comparative benefits,

3. Allowing the presentation of options to be accepted or rejected, and presented in a manner that facilitates the interaction of the party, and

4. A system that isolates each potential recommendation from others, so that they can be added and maintained separately, also by providing a standard way of expressing the benefit of different recommendations, it is easier to update a system.

Background of Invention

[7] Financial advice involves providing suggestions to a party (an individual, couple, family or other financial unit or entity) so that a course of action is taken by the party being advised which ultimately improves their financial position.

[8] The course of action suggested in financial advice, is referred to in this paper as one or more recommendations (or financial 'tips'). A recommendation may be to invest money in a savings account. A recommendation may be more specific, invest money in a particular savings account type with a specific bank. A recommendation may also be to change arrangement, e.g. in the case of an expense that would otherwise be paid for by personal assets, to claim this expense from an employer, or to claim a deduction of taxation in relation to this expense. A financial recommendation may be for a non- financial product that has a financial impact.

[9] A potential recommendation is a financial advice option that has not been fully qualified based on the profile of the party. For example, a poster on a building says Invest in Bonds!'. This is a potential recommendation that has been offered to members of the public, without knowledge of their situation. As their situation is more understood, for example, by understanding that the party has sufficient money, and that investing in bonds would be a better way to invest the money than other methods the party may employ and that the money is not required until a distant maturity date, this potential recommendation becomes more qualified. In some countries or states, it is not legal to offer unqualified advice without suggesting to or conducting a more thorough analysis of a party's situation. This process is called in the present invention the financial advice process.

[10] A party's profile is the information that describes their financial and life situation. It is made up of income and expenses, assets and liabilities, cash flow information, marital status, working status, needs, wants etc., and the details thereof. For example, it is important to know a party's salary as this contributes to the amount of funds available, and in many countries and states impacts the taxation rate, which could impact the financial advice offered. It is also used to describe current product selections and arrangements. It is used to describe a party's appetite for risk and investments. For example, some may view offshore equity investments as too risky, or may not want to invest in tobacco companies as a personal value judgement. It is used to describe a party's goals - for example, to build up long term wealth with enough money to retire comfortably, or to achieve a short term objective of a holiday.

[11] Traditionally, the provision of financial advice has been a very manual and tedious exercise or an exercise that is lacking in quality and depth. The quality of the advice is limited to the knowledge of the individuals providing that advice and limited by the amount of analysis conducted, and the recipient of the advice had limited insight into the options available. Computers, and information technology has resulted in numerous worthy attempts to solve this problem, however many of the original problems remain, and these are:

1. The quality of advice requires that a great deal of information about the party be known,

2. The advice is difficult for the party to understand,

[12] Financial advice recommendations differ from other attempts at providing recom- mendations in other industries. For example, media recommendations (books, movies etc.) are based on matching preferences being genre preferences, author preferences or the like to obtain a recommendation based on personal likes and dislikes. Medical diagnosis systems are often based on matching the indicators of a particular ailment with the symptoms of a patient. A financial advice recommendation may offer recommendations that are contrary to past behaviour and preferences. The recommendation is not so much to remove a problem, but to alter behaviour to achieve a higher financial benefit. Financial recommendations may be combined with other fields where the recommendation has a financial impact, e.g. to purchase a less expensive paperback edition of a book and ensure it is claimed as a work related expense, or to seek a government benefit in relation to a medical expense. Description of Drawings

[13] In order that the present invention may be more readily understood, preferred embodiments of it are described with reference to the drawings in which:

1. Figure 1 shows the high level process of the method and system to provide advice to a party.

2. Figure 2 shows the parameters and a generic formula that may be used for some of the potential recommendations.

3. Figure 3 shows a sample of how a categorisation of the potential recommendations is presented to the party.

4. Figure 4 shows a sample of the use of personas, and how it is used visually to access the process.

5. Figure 5 shows a sample of product based simulated recommendation.

6. Figure 6 shows a sample output of the simulated recommendations.

7. Figure 7 shows a sample of how simulated recommendations may be compared.

8. Figure 8 shows the components of a potential recommendation.

9. Figure 9 shows a simple network based implementation.

10. Figure 10 shows an alternative to figure 9, a multiple server/multiple provider based implementation.

Description of Preferred Embodiments of the Invention

[14] Before an operating process can commence, initial preparation is the set up and configuration of potential recommendations. Potential recommendations are recommendations to pursue a course of action that has not yet been qualified by applying the circumstances of the party. In the context of the present invention, this course of action substantially has a financial impact. The preparation is conducted by experts and/or technicians with knowledge of the financial impact and rules associated with each potential recommendation. Figure 8 illustrates these potential recommendations 8001 are made up of 8002 qualifications and rules that make a potential recommendation active for given values of profile data, potential recommendation specific calculation logic and data 8003 expressed in a form similar to that mentioned in Figure 2. Also included is information content in text and graphics 8004 used to present the potential or simulated recommendation, discussion and feedback of the potential recommendation 8005, instances of the potential recommendation 8006 or sub classes that may be provided by other entities, and child potential recommendations 8007 that are other potential recommendations that are related to the potential recommendation in focus.

[15] Once set up is complete, the operation process can commence, Figure 1, 1001, Party, is an individual, a couple, family or financial entity for whom financial advice is sought.

[16] Data collection means is one or more of an input device, a data interface to another system, and/or a database and is direct, or inferred. An example of direct data collection is an interview form with specific questions - e.g. salary, age, occupation. Inferred data collection is an indirect method of collection, for example, an advertisement on an undergraduate student medical journal for financial assistance; it can be inferred (with a moderate degree of certainty) that a respondent to this advertisement is a student, has little or no income, and is much younger than retirement age. The technique of inference is supported by three concepts - default values, personas and specific inference. Default values are data which may be applicable to everyone - e.g. perceived future inflation rate of 2% per annum. A persona is one of a categorised set of pre-defined hypothetical profiles that superficially matches the party - e.g. the persona of a "Young Student" can be assumed to be 18-25 years old, a "Retiree", is 65 years +, a "Young Worker" is assumed to be 20-30 years old. Specific inference is based on data specific to the interaction e.g. the medical student example above, or another example is someone referred to the site from a first home buyer's magazine can be assumed to not have a home, and to have a goal of purchasing a home. Alternatively, a financial institution may know some information based on a party's interaction with them e.g. they have a large sum of money in an account not earning much interest. Inferred data is often less accurate, however it allows the exercise of financial advice to commence without the barrier of intense interviewing. Through inference, and/or through a method of direct data collection, the profile information is collected, 1002, this includes but is not limited to general profile data, such as salary, family profile and other information 1004, life events 1003, such as starting work or retiring, prior pro-forma persona data 1005 such as single, have children, wealthy, etc. as illustrated in Figure 4, 4001. The profile also includes goals 1006 - such as taking a holiday, buying a house, or buying a car.

[17] A set of potential recommendations is applied 1007. Each potential recommendation

1008 is pre-populated with content, rules, calculations, and parameters such as 2001. These potential recommendations may be classified, and may be directly invoked by the party as shown in Figure 3, 3001 into investment recommendations, benefit recommendations, expense reduction recommendations or best buy recommendations. Potential investment recommendations may be set up through a set of parameters 2001 in Figure 2 to a standard formula. Each potential recommend has a set of rules that is applied to the party based on the profile, and validity of these rules.

[18] The potential recommendations are simulated 1009 against the profile of the party.

The simulation involves applying formulas and rules of the potential recommendation such as 2002, to obtain a result, or set of results. Additional results such as the perceived risk benefit may also be added. Once the best or better simulated recommendations are established, the remaining potential recommendations are simulated based on the best simulated recommendations having been executed. For example if there are 5 potential recommendations, A,B,C,D and E, with C being simulated as the best recommendation, A,B,D and E are executed against a profile that assumes C has been enacted. In this manner the cycle continues until all beneficial recommendations have been established. In theory there appear to be N! (N factorial) simulations that need to run, where N is the number of potential recommendations. In practice there are efficient ways of establishing the best recommendations without necessarily cycling through all the potential recommendations. For example, potential recommendations that reduce expenses (e.g. cheaper phone plan) may be run as a group before potential recommendations that provide how to invest the money. Also the grouping of potential recommendations into mutually exclusive sets provides further efficiency.

[19] The results from 1009 are ranked based on a set of benefit results (such as net rate of return or net saving) this output of simulated recommendations with results 1011 is provided as output to the party (or other intermediary) through the process 1010. The output may be provided in a form similar to Figure 6, 6001. Not all benefits are measured on the same scale, for example, one benefit has a high net return on investment, another saves a large amount of money upfront. The priority of the output is not a single list, rather it is a set of predefined multiple lists that provide simulated recommendations in different categories of benefit. Some simulated recommendations may not be prioritised, and in such cases, the unsuccessful simulated recommendation may be presented, with notes or reasons as to why it was not suggested. An interactive process follows where potential or simulated recommendations are accepted or declined by the party or intermediary of the party. As recommendations are presented, more specific data may be required, in these cases, the party or intermediary is asked for more data. This additive process is the progressive nature of data collection, where each refinement continues through the loop 1012 and extends the profile data.

[20] Recommendations may be general, relating to a family of products e.g. "invest in bonds", or relate to specific products offered by specific providers e.g. "invest in secured bonds for company X at an interest rate of 5%, maturing in 5 years applying through broker Y taking a 1% commission", and may be selected by the party or intermediary through a process, as illustrated in Figure 5, 5001. Different recommendations may be compared by the party or intermediary through a process, as illustrated in Figure 7, 7001 to 7002.

[21] In the output process of 1010, the party may execute a recommendation, this would lead to a change in the profile of that party, a purchase of a specific product or service, a claim or application for a benefit or similar. The profile and output can be shared with third parties 1013 such as financial advisers, other calculation systems, or friends to enable further analysis or commentary on the data and results.

[22] As potential recommendations are added or changed (1008) or the profile of the party changes (1002), the process may be re-executed and the output, 1010, re-presented to the party.

[23] A computer-implemented system and method as is illustrated in figure 9, with the main processes executed and/or stored on a central server 9001, a client device 9003 accessing the system over a network 9002, such as the Internet. The output made available on some type of display output device like a monitor 9005, or printer 9004, so that a party or intermediary of the party 9006 may access the process and information.

[24] An alternative embodiment is a network of computers, with multiple providers providing parts of the service to the client device mentioned in 9003. Figure 10 illustrates these multiple providers, and how the server processes of 9001 can be broken down into: a transaction server 10001 with information about financial transactions performed by the party 10001, advice server 10002 which provides the recommendation centric analysis, a product server 10003 which provides particular product information, origination services and fulfilment services for particular products, and a profile server that stores and maintains information about a party 10004. These all service the client device of 9003, represented in figure 10 as 10005, over an interconnected network of computers 10006 such as the Internet.

Claims

[Claim 1] A computer-implemented method for providing financial advice, the method comprising the steps of: a. data collection means for receiving a data profile for a party, b. applying a plurality of potential recommendations to said data profile, potential recommendations each comprising of rules associated with their validity against a profile, applying these rules, and discounting those potential recommendations for which the rules of validity fail against said profile, c. simulating said potential recommendations with reference to the profile, where the potential recommendations each calculate a financial effect taking as input, data information from the party's profile, the effect of each potential recommendation is weighed against others using a weighing means, by comparing the net benefit of the potential recommendation, being one of return on investment; or size of monetary savings; or positive financial impact, and prioritising those potential recommendations with the highest benefit above lower benefit potential recommendations, and d. displaying a plurality of potential recommendations as output, whereby said party is able to receive financial advice.

[Claim 2] A method claimed in claim 1, wherein the profile of the party is based on a predetermined minimum amount of direct information, with additional indirect information that has been inferred through application of default data, use of one or more personas, and/or information that has been assumed based on the interaction of the party with the process.

[Claim 3] A method claimed in claim 2, wherein said minimum information is then added to progressively by indirectly or directly requesting the information from the party, and steps outlined in claim 1 are re-executed.

[Claim 4] A method claimed in claim 1, wherein the potential recommendations are expressed as parameters to a plurality of standard formulae, each being a formula that is common to more than one potential recommendation.

[Claim 5] A method claimed in claim 4, wherein the parameters are those contained in the formula expressed in 2002 in Figure 2.

[Claim 6] A method claimed in claim 1, wherein said benefit calculated in said simulation includes an assessment means of increased or decreased exposure to one or more types of risk.

[Claim 7] A method claimed in claim 1, wherein the simulation step of claim 1, a copy of the profile of the party is altered, providing a potential future profile that is used to communicate benefit to the party in the final step of claim 1.

[Claim 8] A method claimed in claim 7, wherein the simulation step of claim 1, the simulation is executed a plurality of times against the new potential profile until all suitable potential recommendations are executed.

[Claim 9] A method claimed in claim 8, wherein the simulation step has means for processing efficiency, including execution of mutually exclusive potential recommendations independently, and through grouping of related potential recommendations.

[Claim 10] A method claimed in claim 1, wherein the profile is stored, and the steps outlined in claim 1 are re-executed at a later point in time, under changed conditions including new potential recommendations and changed profile data.

[Claim 11] A method claimed in claim 10, wherein the party is notified of the results of the output.

[Claim 12] A method claimed in claim 1, wherein the potential recommendations are grouped in logical units, with a parent potential recommendation providing a general or sample rules and calculations about a plurality of child potential recommendations, with each member of the group being themselves potential recommendations providing more specific calculations and rules.

[Claim 13] A method claimed in claim 1, wherein a user selects a particular potential recommendation, that has not been simulated as there is insufficient data available, or it is not a recommendation that has been prioritised in the output, or it is a child potential recommendation of a parent simulated recommendation that has been prioritised, the user selects a particular potential recommendation, and then the simulation step occurs as if this was a recommendation with a high priority.

[Claim 14] A method claimed in claim 1, wherein a potential recommendation may require additional data, that data is sought from the party and the process of claim 1 is re-executed.

[Claim 15] A method claimed in claim 1, wherein a potential recommendation is not applicable, due to the failure of rules associated with that potential recommendation when they were applied against a profile, or the benefit of that potential recommendation is not deemed to be positive, based on the calculation of that potential recommendation when it was applied against the profile, the reasons why it was not recommended are provided as output.

[Claim 16] A method claimed in claim 1, wherein the profile information includes life events, these life events being a pre-defined categorisation of significant milestones of financial impact encountered by parties.

[Claim 17] A method claimed in claim 1, wherein the profile information of a party includes goals being financial, commercial, social or personal objectives.

[Claim 18] A method claimed in claim 1, wherein the profile information includes financial portfolio data including income, expenses, assets, liabilities, cash flow and the particulars thereof.

[Claim 19] A method claimed in claim 1, wherein the final step includes execution, application or purchase of a specific product, and interfaces with product providers to affect such execution.

[Claim 20] A method claimed in claim 1, wherein the profile information includes the party's tolerance to and preferences for financial risk and attraction to various markets, investment or products.

[Claim 21] A method claimed in claim 1, wherein the profile information includes the party's assessment of future financial performance.

[Claim 22] A method claimed in claim 1, wherein a potential recommendation has textual and graphical information, and various parties are able to share and discuss feedback about the recommendations.

[Claim 23] A method claimed in claim 1, wherein the profile and/or recommendations is exchanged between parties.

[Claim 24] A method claimed in claim 1, wherein the steps of claim 1 include periodic benefits of potential recommendations, and these benefits are assessed in the simulation and output.

[Claim 25] A method claimed in claim 1, wherein the profile and output is provided to a third party.

[Claim 26] A method claimed in claim 1, wherein elements of the process are provided by separate providers.

[Claim 27] A computer system with instructions stored in memory that determines financial advice by implementing the steps comprising of: a. data collection means for receiving a data profile for a party, b. applying a plurality of potential recommendations to said data profile, potential recommendations each comprising of rules associated with their validity against a profile, applying these rules, and discounting those potential recommendations for which the rules of validity fail against said profile, c. simulating said potential recommendations with reference to the profile, where the potential recommendations each calculate a financial effect taking as input, data information from the party's profile, the effect of each potential recommendation is weighed against others using a weighing means, by comparing the net benefit of the potential recommendation, being one of return on investment; or size of monetary savings; or positive financial impact, and prioritising those potential recommendations with the highest benefit above lower benefit potential recommendations, and d. displaying a plurality of potential recommendations as output, whereby said party is able to receive financial advice.

[Claim 28] A system claimed in claim 27, wherein the profile of the party is based on a predetermined minimum amount of direct information, with additional indirect information that has been inferred through application of default data, use of one or more personas, and/or information that has been assumed based on the interaction of the party with the process.

[Claim 29] A system claimed in claim 28, wherein said minimum information is then added to progressively by indirectly or directly requesting the information from the party, and steps outlined in claim 27 are re- executed.

[Claim 30] A system claimed in claim 27, wherein the potential recommendations are expressed as parameters to a plurality of standard formulae, each being a formula that is common to more than one potential recommendation.

[Claim 31] A system claimed in claim 30, wherein the parameters are those contained in the formula expressed in 2002 in Figure 2.

[Claim 32] A system claimed in claim 27, wherein said benefit calculated in said simulation includes an assessment means of increased or decreased exposure to one or more types of risk.

[Claim 33] A system claimed in claim 27, wherein the simulation step of claim 27, a copy of the profile of the party is altered, providing a potential future profile that is used to communicate benefit to the party in the final step of claim 27.

[Claim 34] A system claimed in claim 33, wherein the simulation step of claim 27, the simulation is executed a plurality of times against the new potential profile until all suitable potential recommendations are executed.

[Claim 35] A system claimed in claim 34, wherein the simulation step has means for processing efficiency, including execution of mutually exclusive potential recommendations independently, and through grouping of related potential recommendations.

[Claim 36] A system claimed in claim 27, wherein the profile is stored, and the steps outlined in claim 27 are re-executed at a later point in time, under changed conditions including new potential recommendations and changed profile data.

[Claim 37] A system claimed in claim 36, wherein the party is notified of the results of the output.

[Claim 38] A system claimed in claim 27, wherein the potential recommendations are grouped in logical units, with a parent potential recommendation providing a general or sample rules and calculations about a plurality of child potential recommendations, with each member of the group being themselves potential recommendations providing more specific calculations and rules.

[Claim 39] A system claimed in claim 27, wherein a user selects a particular potential recommendation, that has not been simulated as there is insufficient data available, or it is not a recommendation that has been prioritised in the output, or it is a child potential recommendation of a parent simulated recommendation that has been prioritised, the user selects a particular potential recommendation, and then the simulation step occurs as if this was a recommendation with a high priority.

[Claim 40] A system claimed in claim 27, wherein a potential recommendation may require additional data, that data is sought from the party and the process of claim 27 is re-executed.

[Claim 41] A system claimed in claim 27, wherein a potential recommendation is not applicable, due to the failure of rules associated with that potential recommendation when they were applied against a profile, or the benefit of that potential recommendation is not deemed to be positive, based on the calculation of that potential recommendation when it was applied against the profile, the reasons why it was not recommended are provided as output.

[Claim 42] A system claimed in claim 27, wherein the profile information includes life events, these life events being a pre-defined categorisation of significant milestones of financial impact encountered by parties.

[Claim 43] A system claimed in claim 27, wherein the profile information of a party includes goals being financial, commercial, social or personal objectives.

[Claim 44] A system claimed in claim 27, wherein the profile information includes financial portfolio data including income, expenses, assets, liabilities, cash flow and the particulars thereof.

[Claim 45] A system claimed in claim 27, wherein the final step includes execution, application or purchase of a specific product, and interfaces with product providers to affect such execution.

[Claim 46] A system claimed in claim 27, wherein the profile information includes the party's tolerance to and preferences for financial risk and attraction to various markets, investment or products.

[Claim 47] A system claimed in claim 27, wherein the profile information includes the party's assessment of future financial performance.

[Claim 48] A system claimed in claim 27, wherein a potential recommendation has textual and graphical information, and various parties are able to share and discuss feedback about the recommendations.

[Claim 49] A system claimed in claim 27, wherein the profile and/or recommendations is exchanged between parties.

[Claim 50] A system claimed in claim 27, wherein the steps of claim 27 include periodic benefits of potential recommendations, and these benefits are assessed in the simulation and output.

[Claim 51] A system claimed in claim 27, wherein the profile and output is provided to a third party. [Claim 52] A system claimed in claim 27, wherein elements of the process are provided by separate providers. [Claim 53] A system as claimed in claim 27, wherein one or more components of the system are provided by one or more parties, and exist across a network of computers being the Internet network or another network.