WO2023148790A1

WO2023148790A1 - Method and system for calculating optimal product purchasing choices

Info

Publication number: WO2023148790A1
Application number: PCT/IT2022/000007
Authority: WO
Inventors: Matteo TEMPORIN
Original assignee: Mind Over Money S.R.L.
Priority date: 2022-02-03
Filing date: 2022-02-03
Publication date: 2023-08-10

Abstract

A method for calculating optimal product purchase choices by means of at least one user interface device (3), operated by a user (2), at least one remote application device (4), and at least one remote calculation device (5), connected and in communication via a telematic communication network, each device (3, 4, 5) being provided with an electronic control unit, a memory, and a transceiver, comprising the steps that consist in: automatically creating (20) a life cycle plan based on the age of the user (2) and optionally other sociodemographic data of the user (2), by virtue of an automatic profiling module (83) of the remote application device (4); analyzing (40) the sustainability of the life cycle plan of the user (2), by means of a choice optimization module (92) and a scenario simulation module (94) of the remote calculation device (5), representing the results of the analysis in the form of simulated scenarios; and providing (50) to the user (2) a set of sustainable products, retrieved from a product database (82) of the remote application device (4), previously calculated by the choice optimization module (92) of the remote calculation device (5) according to the life cycle plan of the user (2), by means of a product offer module (73) of the user interface device (3).

Description

METHOD AND SYSTEM FOR CALCULATING OPTIMAL PRODUCT PURCHASING CHOICES

The present invention relates to a method and a system for calculating optimal product purchase choices, where the term “products” means durable goods, financial products, insurance products and/or credit products. In particular, this method and this system are useful and practical in the field of the economic life cycle planning of an economic entity.

The economic entity is any economic structure having decisionmaking autonomy and legal ownership of material and financial resources. For example, it can be a family that shares economic resources and durable goods over time, or a private, public or non-profit company that collects resources to allocate them to a specific activity or project.

The financial products are the choices of the economic entity of the liquid economic resources made available to a certain activity, i.e., products characterized by the property of yielding returns that are a percentage of the economic resources. For example, they may be investments in the case of a family or the amount of net working capital in the case of a company.

The insurance products are the choices of the economic entity that allow to receive economic resources upon the occurrence of uncertain events in exchange for a premium.

The credit products are the choices of the economic entity to receive economic resources from a credit company in exchange for the payment of a certain interest rate and a certain repayment schedule for the credit received. It is a choice of a multiplicative type which necessarily occurs when the liquid resources available to the company are negative or would become negative if credit were not accessed.

The goals are the economic resources that are necessary to the economic entity in a certain period for the purposes that characterize it, or the economic resources that are necessary to other economic entities linked by economic ties to the first economic entity. The life cycle plan is the set of goals over time of an economic entity, the initial economic resources, and the economic resources that are added at each period. All of these elements of the plan are uncertain variables defined by a probability distribution.

The optimal purchase choices are the types of durable goods and financial, credit, and insurance products that increase the probability of achieving as a whole all the current and future goals of an economic entity, i.e., the sustainability of the life cycle plan up to the maximum possible level within the scope of the available choices. Sustainability decreases due to the lack of wealth for meeting goals, the occurrence of damaging events or the lack of possibility to repay a credit.

The wealth is the liquid economic resources, i.e., the resources available without constraints for meeting goals, for financial products, for the repayment of credits or the payment of interest rates, for insurance premiums.

The saving is the economic resources arising from the income of the economic entity that are made available for future goals and to increase the probability that they will be achieved. In the case of a family, saving is the difference between incomes and consumptions of non-durable goods; in the case of a generic economic entity, it is the portion of profits that is not distributed in dividends to partners or shareholders.

Background of the invention

How can one plan accurately and precisely an economic life cycle of an economic entity so as to make choices that increase the probability of achieving all the goals of the life cycle and the goals of the economic entities to which the economic entity is linked?

Currently, life cycle planning tools are known which allow optimal choices of a single type (financial or credit or insurance) based on individual goals, for example for householders the home, pension, car, education of children, inheritance, etcetera (but never all together). This is due to the fact that the consulting tools are usually provided by the companies that sell or broker the financial products. Even when the same company provides insurance and credit products, each company, for organizational reasons, deal with the offer of its products with separate production and commercial silos. No company seeks to achieve concretely a holistic view of the client and of all its goals, and to equip itself with tools suitable to represent the client accurately and as a whole.

While in other industrial fields this organization by production silos can increase the efficiency of the production and marketing of products, with advantages for the client in terms of product cost, in the case of the production and sale of financial, insurance and credit products the inaccuracy of the assessment of the overall needs of the clients renders the individual products sold inadequate.

Therefore, the current proposal is not precise and most of all is not accurate, since it does not consider the other products in other production silos. The term accuracy means the avoidance of systematic errors in one’s own calculations on which one’s own business proposals are based.

The seriousness of the lack of accuracy is enormous, because offer evaluations are made considering just one aspect, thus leading to a choice of resource allocation that may cause serious errors in the management of the other choices of different types of product. For example, a financial investment choice leaves no room for protection insurance policies in the event of predecease or damage to the assets or health of the family members. For example, a shorter-term mortgage affects the possibility to invest prudently a portion of the remaining liquidity that would allow to manage saving uncertainties that might reduce the probability of paying mortgage installments.

The economic and financial sustainability of the economic entity is, in fact, a unitary and holistic problem. Each choice influences the others and the present invention helps to understand this and to find choices that make all aspects optimal. However, as mentioned, there are no tools that allow to make optimal choices in the simultaneous presence of many goals distributed over time.

In addition, there are no tools that allow to assess the impact of insurance coverage choices made over time, even though they may be economically relevant with respect to saving and wealth and its investment. Above all, there is a lack of tools that allow to analyze the sustainability effect of multiple insurance coverages paid together and which is the set of coverages that allows to increase the probability of achieving the goals.

Moreover, there are no tools that allow to evaluate the impact of credit choices (for example, a fixed-rate or variable-rate mortgage) with respect to the uncertain saving capacity of an economic entity to pay the debt over time in a manner compatible with the goals in general and not only the one for which credit is accessed.

Furthermore, there are no tools that allow to represent and evaluate the saving, i.e., the resources that are added or left available for the goals, that is not a set amount.

In short, tools of a known type for planning the life cycle of an economic entity do not allow:

1. the simultaneous evaluation of all goals of the economic entity;

2. the simultaneous choice of all the financial, credit and insurance products that provide the highest probability of achieving the goals; and

3. the prediction of decisions to change saving activities as a function of the change of the distribution of probability of achieving the goals.

Definition of the invention

The aim of the present invention is to overcome the limitations of the background art described above, devising a method and a system for calculating optimal product purchase choices that allow to obtain better effects than those obtainable with known solutions and/or similar effects at lower cost and with higher performance. Within the scope of this aim, an object of the present invention is to devise a method and a system for calculating optimal product purchase choices that allow to evaluate in a simple, robust and accurate manner the choices of financial, insurance and credit products, at a certain point of the economic life cycle of an economic entity, for example a family or a company, simultaneously taking into consideration: all the future goals of the economic entity, all the main risk factors that will arise, and all the other financial, insurance and credit choices at future points of the economic life cycle.

Another object of the present invention is to devise a method and a system for calculating optimal product purchase choices that allow to increase the precision and accuracy of the prediction of the probability of achieving all the goals of the life cycle of an economic entity. In particular, that allow to increase the precision and accuracy of the calculation of:

1. the economic resources necessary in each period to achieve future goals with certain levels of probability using certain financial, credit and insurance tools;

2. the choice of the optimal configuration of the tools that with those resources increases the level of probability given certain economic resources; and

3. the possible economic scenarios that will arise in the future by adopting the optimal choices found.

Another object of the present invention is to conceive a method and a system for calculating optimal product purchase choices that allow to provide a realistic representation of the trend of the economic life cycle of an economic entity, for example a family or a company, taking into consideration all the uncertainties to which it is subjected: the uncertainty of incomes, the uncertainty of expenses, the uncertainty of savings, the uncertainty of investment results, the uncertainty of risks, the uncertainty of credit rates, the uncertainty of the value of its own real estate or business assets, the uncertainty of the needs of the network of related economic entities, for example children, parents, related businesses, etcetera.

Another object of the present invention is to devise a method and a system for calculating optimal product purchase choices that allow an advisor of an economic entity to define all of the goals of the economic entity, to provide sustainable and appropriate products, starting from these goals, to develop an assistance that is durable, and to also explain in advance which products will be suggested as various scenarios occur.

Moreover, an object of the present invention is to devise a method and a system for calculating optimal product purchase choices that allow to comply with the requirements that the regulations of the financial, insurance and credit sectors (in the EU see MIFID2, IDD and Basel 2) impose on financial, credit and insurance companies.

Not least object of the present invention is to provide a method and a system for calculating optimal product purchase choices that are highly reliable, relatively easy to provide and economically competitive if compared with the background art.

This aim and these and other objects which will become better apparent hereinafter are achieved by a method for calculating optimal product purchase choices by means of at least one user interface device, operated by a user, at least one remote application device, and at least one remote calculation device, connected and in communication via a telematic communication network, each device being provided with an electronic control unit, a memory, and a transceiver, comprising the steps that consist in:

- automatically creating a life cycle plan based on the age of said user and optionally other sociodemographic data of said user, by virtue of an automatic profiling module of said remote application device;

- analyzing the sustainability of said life cycle plan of said user, by means of a choice optimization module and a scenario simulation module of said remote calculation device, representing the results of said analysis in the form of simulated scenarios; and

- providing said user with a set of sustainable products, retrieved from a product database of said remote application device, previously calculated by said choice optimization module of said remote calculation device on the basis of said life cycle plan of said user, by means of a product offer module of said user interface device.

This aim and the intended objects are also achieved by a system for calculating optimal product purchase choices, comprising at least one user interface device, operated by a user, at least one remote application device, and at least one remote calculation device, connected and in communication via a telematic communication network, each device being provided with an electronic control unit, a memory, and a transceiver; said remote application device comprises an automatic profiling module configured to create automatically a life cycle plan based on the age of said user and optionally on other sociodemographic data of said user; said remote calculation device comprises a choice optimization module and a scenario simulation module which are configured to analyze the sustainability of said life cycle plan of said user, representing the results of said analysis in the form of simulated scenarios; and said user interface device comprises a product offer module configured to provide said user with a set of sustainable products, retrieved from a product database of said remote application device, previously calculated by said choice optimization module of said remote calculation device based on said life cycle plan of said user.

Brief description of drawings

Further characteristics and advantages of the invention will become better apparent from the description of a preferred but not exclusive embodiment, of the method and the system for calculating optimal product purchase choices according to the invention, illustrated by way of non- limiting example with the aid of the accompanying drawings, wherein:

Figure 1 is a block diagram that shows schematically an embodiment of the system for calculating optimal product purchase choices, according to the present invention;

Figure 2 is a block diagram that shows in detail the modules comprised in the embodiment of the system for calculating optimal product purchase choices shown in Figure 1;

Figure 3 is a flowchart that shows schematically an embodiment of the method for calculating optimal product purchase choices, according to the present invention;

Figures 3a to 3f are flowcharts that show in detail the steps comprised in the embodiment of the method for calculating optimal product purchase choices shown in Figure 3.

Detailed description of the invention

1. System

With reference to Figures 1 and 2, the system for calculating optimal product purchase choices according to the present invention, generally designated by the reference numeral 1, comprises substantially: at least one user interface device 3, operated by a user 2; at least one remote application device 4, or in short an application server 4; and at least one remote calculation device 5, or in short a calculation server 5.

The user interface device 3, the application server 4 and the calculation server 5 are sequentially connected and in communication via a telematic communication network, such as for example the Internet, advantageously by means of an API RESTful protocol and corresponding HTTPS requests and HTTPS responses.

The user interface device 3 is any processing device that can be operated by the user 2, provided with any operating system and suitable to run any HTTPS Internet browser. The user interface device 3 comprises an electronic control unit, display and selection means, for example a touchscreen or a screen and a keyboard, a memory, conveniently sized and comprising suitable instructions, and a transceiver. For example, the user interface device 3 can be a desktop PC, a laptop PC, a tablet or a smartphone.

Preferably, the user interface device 3 further comprises a user access module 71 configured to verify the identity of the user 2 and, if said verification has a positive outcome, authorize the entry of said user 2 in the system 1.

In particular, in one embodiment, the user access module 71 is configured to: enter an identifier of the user 2; enter a password of the user 2; verify the identity of the user 2 based on the identifier and the password entered by said user 2 and, in case of positive outcome, authorize entry; optionally, signal one or more notifications to the user 2; finally, choose between creating a new life cycle plan, by means of the automatic profiling module 83 of the application server 4, or select, by means of the plan search module 72 of the user interface device 3, a life cycle plan to be customized, by means of the plan customization module 75 of the user interface device 3.

Preferably, the user interface device 3 further comprises a plan search module 72 configured to search, select and retrieve a specific life cycle plan comprised in a plurality of life cycle plans stored in the plan database 81 of the application server 4.

The user interface device 3 further comprises a product offer module 73 configured to provide the user 2 with a set, retrieved from the product database 82 of the application server 4, of sustainable products, i.e., the optimal product purchase choices previously calculated by the choice optimization module 92 of the calculation server 5 according to the life cycle plan, in present and future wealth scenarios.

In particular, in one embodiment, the product offer module 73 is configured to: provide sustainable durable goods, for example the car model that optimizes the sustainability of the plan, the best house that it is possible to purchase, the level of education for the children that it is possible to sustain, etcetera; provide sustainable financial products in which to invest wealth, for example the portfolio of investment products defined on an efficient frontier of products that are appropriate for the risk profile; provide sustainable insurance products with which to protect oneself from damage risks in a sustainable manner; provide sustainable credit products with which to make it possible to purchase durable goods without sufficient wealth; finally, provide a relationship with other life cycle plans, for example optimal supplementary life and pension insurance with which to make these plans and the current plan equally sustainable.

The user interface device 3 further comprises a graphic representation module 74 configured to display the graphical user interfaces, particularly the corresponding charts, of the system 1, so as to render the information and the data produced by said system 1 intelligible to the user 2.

Advantageously, the graphic representation module 74 is configured to display a chart representing wealth scenarios over time; advantageously, the graphic representation module 74 is configured to display a chart representing damage risk scenarios covered or not covered by insurance policies; finally, advantageously, the graphic representation module 74 is configured to display a chart representing credit default risk scenarios.

Preferably, the user interface device 3 further comprises a plan customization module 75 configured to modify a specific existing life cycle plan, searched and selected by the user 2 by means of the plan search module 72 of said user interface device 3 and retrieved from the plan database 81 of the application server 4. The life cycle plan was created previously by the automatic profiling module 83 of the application server 4. The life cycle plan can be modified in any moment.

In particular, in one embodiment, the plan customization module 75 is configured to: modify the goals of the user 2 for the purchase of durable goods, for example a home, car, children’s education, etcetera; modify the financial risk profile of the user 2, particularly allowing the selection of only suitable financial products; modify the insurance risk profile of the user 2, particularly allowing the modification of the damage insurance requirements, for example home, accident, third party liability, etcetera; modify the credit profile of the user 2, particularly allowing the selection of only credit products which the user can access, for example mortgages, consumer credit, etcetera; finally, indicate the relationships with other life cycle plans, for example, the plan for management of income loss due to predecease or serious illness (life insurance), or the work retirement plan (supplementary pension).

The application server 4 is a processing device provided with appropriate capabilities for calculation and interfacing. The application server 4 comprises an electronic control unit, a memory which is conveniently sized and comprises suitable instructions, and a transceiver.

The application server 4 further comprises a plan database 81 configured to store information and data related to a plurality of life cycle plans created previously.

The application server 4 further comprises a product database 82 configured to store information and data related to a plurality of products, particularly durable goods, financial products, insurance products and/or credit products.

The application server 4 further comprises an automatic profiling module 83 configured to create automatically a new life cycle plan based necessarily on the age of the user 2 and optionally on other sociodemographic data of said user 2, for example zone of residence, level of education, etcetera.

In particular, in one embodiment, the automatic profiling module 83 is configured to: select the age of the user 2; optionally, select other sociodemographic data of the user 2; infer a net income (modifiable if necessary) based on the age and the other sociodemographic data of the user 2; infer statistically an average saving and its uncertainty (modifiable if necessary) based on the net income; finally, infer a life cycle plan of the user 2 with his goals, based on the saving.

The application server 4 further comprises a scenario management module 84 configured to generate charts corresponding to the scenarios simulated by the scenario simulation module 94 of the calculation server 5.

Advantageously, the scenario management module 84 is configured to generate a chart representing the wealth scenarios over time; advantageously, the scenario management module 84 is configured to generate a chart representing damage risk scenarios covered or not covered by insurance policies; finally advantageously, the scenario management module 84 is configured to generate a chart representing credit default risk scenarios.

Preferably, the application server 4 further comprises a criteria optimization module 85 configured to define the goals and the criteria to be optimized and, consequently, those to be penalized within the life cycle plan of the user 2. The criteria can be defined as sense goals of the life cycle plan, such as for example financial prudence, probability of achieving the goals, social, environmental or gender-related sustainability. In general, only one goal/criterion can be optimized and only one goal/criterion can be penalized; all the other goals/criteria are maintained equal or are disregarded.

In particular, in one embodiment, the criteria optimization module 85 is configured to: select a goal/criterion to be optimized, for example sustainability; select a goal/criterion to be penalized, or rather of which one accepts a penalization, for example financial prudence; select other goals/criteria to be disregarded; calculate the optimization of the goals/criteria based on the previous selections; finally, advantageously, infer an intelligible history of the life cycle plan, i.e., the written representation of the sense of the plan, of its purpose and of its meaning for the life of the user 2, based on the preceding selections.

Finally, the calculation server 5 is a processing device provided with appropriate capabilities for calculation and interfacing. The calculation server 5 comprises an electronic control unit, a memory, which is conveniently sized and comprises suitable instructions, and a transceiver.

The calculation server 5 further comprises a choice optimization module 92 configured to analyze the sustainability of the life cycle plan of the user 2, created by the automatic profiling module 83 of the application server 4 and optionally modified by the plan customization module 75 of the user interface device 3.

In particular, the choice optimization module 92 is configured to calculate the optimization of the product purchase choices, particularly durable goods, financial products, insurance products and/or credit products, of the user 2 on the basis of the life cycle plan.

The calculation server 5 further comprises a scenario simulation module 94 configured to represent the results of the analysis performed by the choice optimization module 92 in the form of simulated scenarios.

In particular, the scenario simulation module 94 is configured to calculate the simulation of the results over time of the optimal purchase choices, particularly in relation to wealth over time, to the risk of damage covered or not covered by insurance policies, and to the credit default risk.

2. Method

With reference to Figure 3 and to Figures 3a to 3f, the method for calculating optimal product purchase choices according to the present invention substantially comprises the steps described hereinafter.

Preferably, in step 10, the user access module 71 of the user interface device 3 verifies the identity of the user 2 and, if the verification has a positive outcome, authorizes the entry of said user 2 in the system 1.

With particular reference to Figure 3a, in one embodiment, the step 10 mentioned above comprises the following substeps: in step 11, the user access module 71 of the user interface device 3 allows to enter an identifier of the user 2; in step 12, the user access module 71 allows to enter a password of the user 2; in step 13, the user access module 71 verifies the identity of the user 2 based on the identifier and the password entered by said user 2 and, in case of positive outcome, authorizes his entry; optionally, in step 14, the user access module 71 signals one or more notifications to the user 2; finally, in step 15, the user access module 71 allows to choose between creating a new life cycle plan, by means of the automatic profiling module 83 of the application server 4, or selecting, by means of the plan search module 72 of the user interface device 3, a life cycle plan to be customized, by means of the plan customization module 75 of the user interface device 3.

In step 20, the automatic profiling module 83 of the application server 4 creates automatically a new life cycle plan based necessarily on the age of the user 2 and optionally on other sociodemographic data of said user 2, for example zone of residence, level of education, etcetera.

With particular reference to Figure 3b, in one embodiment the step 20 mentioned above comprises the following substeps: in step 21, the automatic profiling module 83 of the application server 4 allows to select the age of the user 2; optionally in step 22, the automatic profiling module 83 allows to select other sociodemographic data of the user 2; in step 23, the automatic profiling module 83 infers a net income (modifiable if necessary) based on the age and the other sociodemographic data of the user 2; in step 24, the automatic profiling module 83 infers statistically an average saving and its uncertainty (modifiable if necessary) based on the net income; finally, in step 25, the automatic profiling module 83 infers a life cycle plan of the user 2 with his goals, based on the saving.

Preferably, in step 30, the plan customization module 75 of the user interface device 3 modifies a specific existing life cycle plan, searched and selected by the user 2 by means of the plan search module 72 of said user interface device 3 and retrieved from the plan database 81 of the application server 4. The life cycle plan was created previously by the automatic profiling module 83 of the application server 4. The life cycle plan can be modified in any moment.

With particular reference to Figure 3c, in one embodiment the step 30 mentioned above comprises one or more of the following substeps: in step 31, the plan customization module 75 of the user interface device 3 allows to modify the goals of the user 2 for the purchase of durable goods, for example a home, car, children’s education, etcetera; in step 32, the plan customization module 75 allows to modify the financial risk profile of the user 2, particularly allowing the selection of only suitable financial products; in step 33, the plan customization module 75 allows to modify the insurance risk profile of the user 2, particularly allowing modification of the damage insurance needs, for example home, accident, third-party liability, etcetera; in step 34, the plan customization module 75 allows to modify the credit profile of the user 2, particularly allowing the selection of only credit products which the user can access, for example mortgages, consumer credit, etcetera; finally, in step 35, the plan customization module 75 allows to indicate the relationship with other life cycle plans, for example, the management plan for income loss due to predecease or serious illness (life insurance), or the working retirement plan (supplementary pension).

In step 40, the choice optimization module 92 and the scenario simulation module 94 of the calculation server 5 analyze the sustainability of the life cycle plan of the user 2, created by the automatic profiling module 83 of the application server 4 and optionally modified by the plan customization module 75 of the user interface device 3, representing the results of the analysis in the form of simulated scenarios.

With particular reference to Figure 3d, in one embodiment the step 40 mentioned above comprises the following substeps: in step 41, the choice optimization module 92 of the calculation server 5 calculates the optimization of the product purchase choices, particularly durable goods, financial products, insurance products and/or credit products, of the user 2 on the basis of the life cycle plan; in step 42, the scenario simulation module 94 of the calculation server 5 calculates the simulation of the results over time of these purchase choices, particularly in relation to wealth over time, to the risk of damage covered or not covered by insurance policies, and to the credit default risk; advantageously, in step 43 the scenario management module 84 of the application server 4 generates, and the graphic representation module 74 of the user interface device 3 displays, a chart that represents the wealth scenarios over time; advantageously, in step 44 the scenario management module 84 generates, and the graphic representation module 74 displays, a chart that represents the damage risk scenarios covered or not covered by insurance policies; finally, advantageously in step 45 the scenario management module 84 generates, and the graphic representation module 74 displays, a chart that represents the credit default risk scenarios.

In step 50, the product offer module 73 of the user interface device 3 provides the user 2 with a set, retrieved from the product database 82 of the application server 4, of sustainable products, i.e., the optimal product purchase choices previously calculated by the choice optimization module 92 of the calculation server 5 on the basis of the life cycle plan, in the present and future wealth scenarios.

With particular reference to Figure 3e, in one embodiment the step 50 mentioned above comprises one or more of the following substeps: in step 51, the product offer module 73 of the user interface device 3 provides sustainable durable goods, for example the car model that optimizes the sustainability of the plan, the best home that it is possible to purchase, the level of education of the children that it is possible to support, etcetera; in step 52, the product offer module 73 provides sustainable financial products in which to invest wealth, for example the portfolio of investment products defined on an efficient frontier of products suitable for the risk profile; in step 53, the product offer module 73 provides sustainable insurance products with which to protect oneself from damage risks in a sustainable manner; in step 54, the product offer module 73 provides sustainable credit products with which to make it possible to purchase durable goods in the absence of sufficient wealth; finally, in step 55 the product offer module 73 provides products for relationship with other life cycle plans, for example optimal supplementary life and pension insurance with which to make these plans and the current plan equally sustainable.

Preferably, in step 60 the criteria optimization module 85 of the application server 4 defines the goals and the criteria to be optimized and, consequently, those to be penalized within the scope of the life cycle plan of the user 2. The criteria can be defined as sense goals of the life cycle plan, such as for example financial prudence, probability of achieving the goals, social, environmental or gender-related sustainability. In general, only one goal/criterion can be optimized and only one goal/criterion can be penalized; all the other goals/criteria are maintained equal or are disregarded.

With particular reference to Figure 3f, in one embodiment the step 60 mentioned above comprises the following substeps: in step 61, the criteria optimization module 85 of the application server 4 allows to select a goal/criterion to be optimized, for example sustainability; in step 62, the criteria optimization module 85 allows to select a goal/criterion to be penalized, or rather of which one accepts a penalization, for example financial prudence; in step 63, the criteria optimization module 85 allows to select other goals/criteria to be disregarded; in step 64, the criteria optimization module 85 calculates the outcome of the optimization of the goals/criteria based on the selections in the preceding steps 61 to 63; finally, in step 65 the criteria optimization module 85 advantageously infers an intelligible history of the life cycle plan, i.e., the written representation of the sense of the plan, of its purpose and of its meaning for the life of the user 2 on the basis of the selections in the preceding steps 61 to 63.

3. Choice optimization

The invention, particularly the choice optimization module 92 of the calculation server 5, uses a calculation technique based on the Fast Fourier Transform (FFT). In particular, the calculation technique used applies the convolution theorem that states that the convolution of two functions, as in the sum of two random variables, is equal to the inverse Fourier transform of the product of the transforms of the two functions.

In general, the use of convolutions, calculated with Fourier transforms, with uncertain phenomena that are endogenous to the economic entity (saving) lead to greater precision and accuracy in the evolution of wealth scenarios than the simple evolution of exogenous uncertain factors (financial returns).

Furthermore, the invention, particularly the choice optimization module 92 of the calculation server 5, uses the backward induction technique to solve the Bellman equation underlying the problem of the choice of financial, credit and insurance products that increase the probability of achieving the goals of the economic entity.

The invention allows the calculation of the following stochastic differential equation:

X(t) = (X(t-l) - O(x,t-l))*I(x,t-l) + R(t-l)

Following the normal convention, capital letters represent random variables with a known or calculated probability distribution, where:

- X(t) is the evolution of the final wealth available at the beginning in the various periods t (comprised between 0 and p);

- O(x,t-1) are the goals of durable goods expenditure of the period t-1, which are also a function of the level of wealth available at the beginning of the period t-1; - I(x,t-1) is the form of investment (or debt if x is negative) of the period t-1, which are also a function of the level of wealth available at the beginning of the period t-1; and

- R(t-l) is the saving (understood as difference between net incomes and current expenses) produced in the period t-1.

The outcome that the invention optimizes, particularly the choice optimization module 92 of the calculation server 5, is the probability that X(p) is > 0, i.e., that one reaches the last period of the life cycle plan without debt.

Optimization occurs automatically by applying the Bellman equation by varying, in a set of choices available as a function of the wealth level x and of the various periods t, the goals and the form of investment/debt.

The inputs of the calculation process are:

1. The probability distributions of the saving R(t) in the various periods, which represent the ratio between sociodemographic factors and saving. The values of these distributions are obtained as a function of the surveys on the wealth of families that are conducted in all OECD countries. As an alternative, the value of these distributions can be obtained by analyzing the income and expenditure flows of the economic entity that one intends to manage;

2. The probability distributions of the logarithms of the returns on investments and debts available for a choice, representing the risk/retum characteristics of the investments. For example, those accessible on the financial or credit markets, typically in the case of investments are portfolios of financial products on an efficient frontier, i.e., that portfolio of investments that reduces volatility for an equal return; and

3. The probability distributions of achieving the goal as a function of the resources transferred to the goal. A goal is the sum of the various types of goal that one intends to achieve in a certain period. If the goal is the recovery of a damage, the probability of achieving it with a certain premium is inferred from the multiplication of two factors: the ratio between the premium and the reimbursement deductible from the tariffs of the company and the value of the reimbursement that allows to achieve the damage recovery goal with the set probability. By their nature, goals can be summed in value for an equal probability of achieving them.

In general, the inputs are provided as probability distributions associated with a monetary value. If the distributions are provided as discrete distributions over a set of values, a definition domain is defined within which all probabilities of the phenomenon are defined minus a PMIN probability. The PMIN parameter defines the precision of the calculation process.

3.1 Backward step

As mentioned, the solution of the optimization problem is calculated by the invention by backward induction starting from the period p, which is the final period of the plan and could be for example the retirement period for a person or might be a future period in which a certain resource condition is desired for a company.

Typically, the periods represent years, but the method can be applied to shorter periods, for example months.

In the period p the probability of having x(p) > 0 is 100% if x(p) > 0 or 0% if x(p) <=0. This is a particular probability distribution known as Heaviside Step Function.

If the final period of the plan is the retirement period H(p) coincides with a different probability distribution. It will be defined by the probability that with a certain wealth h(p) one can achieve the goals during the plan that one has defined for the step of the life cycle related to retirement.

For the sake of simplicity, we will call H(p) the random variable h with which the probability of having the wealth X(p) > 0 is associated. The probability of having X(p) > 0 is referred to, in the remainder of the description, as sustainability of wealth available in the various periods. Backward 1 : uncertain effect of savings

At the end of the period p-1, the saving R(p-l) is subtracted from H(p) and we obtain the probability distribution H'(p-l) of having wealth X(p) > 0 with the addition of the saving: H'(p-l) = H(p) - R(p-l)

Backward 2: choice of the optimal form of investment/debt

At this point we calculate H"(p-1) the following random variable:

It represents for each level h the probability that the wealth X(p) > 0 as a function of the form of investment/debt I(h",t).

I(x,t) is the uncertain return/credit rate of a certain wealth x at the time t+1.

For example, the probability distribution of a typical investment is expressed in lognormal form, i.e., the distribution of the natural logarithm of the ratio between the final wealth and the initial wealth of an investment/debt is normal.

Therefore the result of the division is obtained by subtraction of the random variables obtained from the probability distributions of the logarithm of the domain variable: ln(H"(p-l)) = ln(H'(p-l)) - ln(I(h",p-l))

Since the domain of H'(p-l) might be negative, the calculation is divided into two parts: positive wealth (form of investment), negative wealth (forms of debt).

In this step the type of investment/debt that provides the maximum probability that X(p) > 0 is chosen for each level of the domain h". This is done by performing the convolution for each type of investment/debt and choosing for each level h" the one that produces the highest cumulative probability.

Backward 3: choice of optimal goals

The next step is to calculate the random variable H(t-l) which is the result of summing the random variable of the goals: H(t-1) = H"(t) + O(h"(t),t)

In this step, the value of the goal that for each level of the domain h" has the same sustainability that the wealth h"(t-l) has is chosen.

This is done by performing the following transform of the distribution H"(t) for each value

P = F(h”(t)) (h”(t))

F^A-l(h(t))(p) = h"(t) + F^A-l(o(t))(p)

Where p = F(X)(x) is the cumulative distribution of the random variable x and yields the probability that the random variable X is smaller than x. x = F^A-l(X)(p) is the inverse function of the distribution which, starting from the cumulative probability, yields the value x for which the probability value p is achieved.

The method proceeds backwards up to the initial period where H(t=0) represents the probability that for that level of wealth h the X(p) is greater than 0.

3.2 Forward step

In order to obtain the effect of the various optimal choices performed, one proceeds by applying the stochastic differential equation to the known initial wealth X(0) = x

Where O(x,l) is the value of the goal in the first period for that initial level of wealth. This value is obtained starting from the sustainability of the value x for the goal O(x,l) obtained in the backward step.

I(x",l) represents the optimal form of investment/debt for the wealth level x" obtained by subtraction from the initial wealth of the goals. It too was calculated in the backward step.

In this forward step as well, multiplication by the form of investment/debt is performed by working on the logarithm of the domain of the random variables and performing a convolution of the sum of the two random variables.

Finally, in the forward step of this period, the uncertain saving R(l) is summed in convolutional terms.

For each step of the forward process one obtains X(t) which indicates the probability distribution of the various levels of wealth x.

The value of the probability that X(p) > 0 coincides with that of H(0) for the value of h = x.

This allows to keep under control the precision of the calculation and if the values calculated in the backward step and those of the forward step deviate beyond a certain value, an automatic adjustment of the calculation parameter PMIN is made.

Currently, there are no alternative forms that could reasonably lead to the same result produced by the present invention or to a comparable result in terms of precision and accuracy in calculating optimal choices for the purchase of durable goods, investment products, insurance coverages, forms of credit within the life cycle of a family or the life cycle of a generic private economic entity such as a company or a project thereof or the life cycle of a social entity such as an association or a public non-profit institution.

* * * *

In practice it has been found that the invention fully achieves the intended aim and objects. In particular, it has been shown how the method and the system for calculating optimal product purchase choices thus conceived allow to overcome the qualitative limitations of the background art, since they allow to obtain better effects than those obtainable with known solutions and/or similar effects at lower cost and with higher performance.

An advantage of the method and the system for calculating optimal product purchase choices according to the present invention resides in that they allow to evaluate in a simple, robust and accurate manner the choices of financial, insurance and credit products, at a certain point of the economic life cycle of an economic entity, for example a family or a company, simultaneously taking into consideration: all the future goals of the economic entity, all the main risk factors that will arise, and all the other choices of the financial, insurance and credit type at future points of the economic life cycle.

Another advantage of the method and the system for calculating optimal product purchase choices according to the present invention resides in that they allow to increase the precision and accuracy of the prediction of the probabilities of achieving all the goals of the life cycle of an economic entity. In particular, they allow to increase the precision and accuracy of the calculation of:

An additional advantage of the method and the system for calculating optimal product purchase choices according to the present invention resides in that they allow to give a realistic representation of the trend of the economic life cycle of an economic entity, for example a family or a company, taking into consideration all the uncertainties to which it is subject: the uncertainty of incomes, the uncertainty of expenses, the uncertainty of savings, the uncertainty of investment results, the uncertainty of risks, the uncertainty of credit rates, the uncertainty of the value of its real estate or business assets, the uncertainty of the needs of the network of connected economic entities, for example children, parents, connected companies, et cetera.

Another advantage of the method and the system for calculating optimal product purchase choices according to the present invention resides in that they allow a consultant of an economic entity to define all of the goals of the economic entity, to provide sustainable and appropriate products, starting from these goals, to develop durable assistance over time, and to also explain in advance which products will be suggested as various scenarios arise.

Moreover, an advantage of the method and the system for calculating optimal product purchase choices according to the present invention resides in that they allow to comply with the requirements that the regulations of the financial, insurance and credit sectors (in the EU see MIFID2, IDD and Basel 2) impose on the financial, credit and insurance companies.

The invention leads to the optimization of the financial, insurance and credit choices that maximize the probability that the economic entity will achieve its goals over time of use of its own resources, and to the simulation of the consequences of these choices on the scenarios over time of wealth and of the level of achievement of the goals.

The results of the invention make it possible to indicate in a simple and immediate way the medium, positive and negative scenarios that may occur, allowing the variation of the goals of the economic entity and of the limitations put on current financial, insurance and credit choices.

The present invention allows to simulate the economic consequences of damaging events, such as for example the predecease of one of the income producers of the economic entity, highlighting the resources needed to guarantee in any case the same sustainability, i.e., the same probability of achieving the objectives of the surviving members through the most appropriate insurance coverage.

The present invention allows to provide new models of volatility/return management of financial products to allow the achievement, with the greatest possible certainty, of the maximum value of goals preferred by the client (for example, the maximum retirement yield in the presence of insurance and credit goals throughout the productive life of the person).

The present invention allows to define the potential offer to a set of economic entities of optimal products based on automatic profiling obtained starting from socio-demographic databases from which it is possible to extract the variables of the model representing the economic entity (wealth, saving, goals over time).

The present invention allows to provide a series of new consumercompany touchpoint applications on individual products starting from automatic profiling in order to enhance it more and more with the goals of the customers progressively collected. For example, one touchpoint might be the sale of real estate mortgages, which can start from an automatic profiling of customer goals and then collect the actual goals. These actual goals collected can be used in additional touchpoints for the sale of insurance policies or forms of investment. Ultimately, the company and the client will have established a complete picture of the life cycle plan and will be able to evolve it over time with optimal offerings.

The present invention defines the data structures necessary to allow the client to describe his goals to many possible suppliers of durable goods (in the purchase of a home or car) and of financial, insurance and credit services, making them compete against each other to obtain favorable conditions that increase the probability of achieving his goals. The data will always be owned by the user and can be refined in the various touchpoints and rendered portable to subsequent touchpoints even of different companies.

The present invention can be used in financial consulting systems to highlight the evolution of the investment by taking into account the many goals in the life cycle, including insurance goals. The present invention can be used in consulting systems to evaluate insurance instruments by highlighting not only the effect of the reimbursement in the event of a damage and the value of the premium required for this reimbursement, but also the impact of premiums on available wealth in the life cycle.

The present invention can be used in credit counseling systems by highlighting not only the economic impact of debt repayments but by verifying the compatibility of these repayments with respect to the goals of the economic entity and the uncertainties of the saving and of the financial activities which precede the time of access to credit.

The present invention can be used in consulting systems for the economic sustainability analysis of a company or a business project, allowing the representation of financial flows over time (for example, on a monthly basis) in terms which are uncertain and not simply predetermined arbitrarily. The scenarios that will be produced allow an evaluation of the probabilities of success of the initiative and the automatic choice of the production management models.

The present invention can be used in credit counseling systems for companies by highlighting not only the economic impact of debt repayments or accrued interests, but by verifying the compatibility of these repayments with the goals of the economic entity and the uncertainties of the financial flows that characterize the production activity.

The present invention can be used in financial control systems of groups of companies or of a set of projects by allowing the representation of financial flows over time (for example, by integrating the flows of the individual production entities) in terms that are uncertain and not simply predetermined arbitrarily. The scenarios that will be produced allow an assessment of the overall probability of risks of loss of profitability, liquidity and credit of the group and the optimization of the distribution of resources among the various entities in order to reduce these risks. The invention can be used in various forms and with various graphical interfaces directly by individual citizens and by families, by financial managers of private and public companies, by economic entity consultants, and by companies providing durable goods and financial, credit and insurance products to evaluate the products or the optimal choices of product offer to the economic entities that are their clients, both for operational and educational purposes.

The invention thus conceived is susceptible of numerous modifications and variations, all of which are within the scope of the appended claims. All the details may furthermore be replaced with other technically equivalent elements.

In practice, the materials used, so long as they are compatible with the specific use, as well as the contingent shapes and dimensions, may be any according to the requirements and the state of the art.

To conclude, the scope of the protection of the claims must not be limited by the illustrations or by the preferred embodiments illustrated in the description as examples, but rather the claims must comprise all the characteristics of patentable novelty that reside in the present invention, including all the characteristics that would be treated as equivalents by the person skilled in the art.

Where technical features mentioned in any claim are followed by reference signs, those reference signs have been included for the sole purpose of increasing the intelligibility of the claims and accordingly such reference signs do not have any limiting effect on the interpretation of each element identified by way of example by such reference signs.

Claims

1. A method for calculating optimal product purchase choices by means of at least one user interface device (3), operated by a user (2), at least one remote application device (4), and at least one remote calculation device (5), connected and in communication via a telematic communication network, each device (3, 4, 5) being provided with an electronic control unit, a memory, and a transceiver, comprising the steps that consist in:

- automatically creating (20) a life cycle plan based on the age of said user (2) and optionally other sociodemographic data of said user (2), by virtue of an automatic profiling module (83) of said remote application device (4);

- analyzing (40) the sustainability of said life cycle plan of said user (2), by means of a choice optimization module (92) and a scenario simulation module (94) of said remote calculation device (5), representing the results of said analysis in the form of simulated scenarios; and

- providing (50) said user (2) with a set of sustainable products, retrieved from a product database (82) of said remote application device (4), previously calculated by said choice optimization module (92) of said remote calculation device (5) according to said life cycle plan of said user

(2), by means of a product offer module (73) of said user interface device

(3).

2. The method for calculating optimal product purchase choices according to claim 1, wherein said creation step (20), performed by said automatic profiling module (83), comprises the steps consisting in: selecting (21) the age of said user (2); optionally, selecting (22) other sociodemographic data of said user (2); inferring (23) a net income based on the age and other sociodemographic data of said user (2); statistically inferring (24) an average saving and its uncertainty based on said net income; and inferring (25) said life cycle plan of said user (2) based on said saving.

3. The method for calculating optimal product purchase choices according to claim 1 or 2, wherein said analysis step (40), performed by said choice optimization module (92) and said scenario simulation module (94), comprises the steps consisting in: calculating (41) the optimization of said product purchase choices based on said life cycle plan of said user (2); and calculating (42) the simulation of the results over time of said product purchase choices.

4. The method for calculating optimal product purchase choices according to any one of the preceding claims, wherein said analysis step (40), performed by said choice optimization module (92) and said scenario simulation module (94), further comprises one or more of the steps that consist in: generating and displaying (43) a chart representing wealth scenarios over time; generating and displaying (44) a chart representing the damage risk scenarios covered or not covered by insurance policies; and generating and displaying (45) a chart representing credit default risk scenarios, by means of a scenario management module (84) of said remote application device (4) and a graphic representation module (74) of said user interface device (3).

5. The method for calculating optimal product purchase choices according to any one of the preceding claims, wherein said proposal step (50), performed by said product offer module (73), further comprises one or more of the steps that consist in: providing (51) sustainable durable goods; providing (52) sustainable financial products; providing (53) sustainable insurance products; providing (54) sustainable credit products; and providing (55) products for relationship with other life cycle plans.

6. The method for calculating optimal product purchase choices according to any one of the preceding claims, further comprising the step that consists in verifying (10) the identity of said user (2) and, in case of positive outcome of said verification, authorizing (10) the entry of said user (2) in said system (1) by means of a user access module (71) of said user interface device (3).

7. The method for calculating optimal product purchase choices according to claim 6, wherein said verification and authorization step (10), performed by said user access module (71), comprises the steps that consist in: entering (11) an identifier of said user (2); entering (12) a password of said user (2); verifying (13) the identity of said user (2) based on said identifier and said password entered by said user (2) and, in case of positive outcome, authorizing (13) entry; and choosing (15) between creating a new life cycle plan or selecting a life cycle plan to be customized.

8. The method for calculating optimal product purchase choices according to claim 6 or 7, wherein said verification and authorization step (10), performed by said user access module (71), further comprises the step that consists in signaling (14) one or more notifications to said user (2).

9. The method for calculating optimal product purchase choices according to any one of the preceding claims, further comprising the step that consists in modifying (30) an existing life cycle plan, searched and selected by said user (2) by means of a plan search module (72) of said user interface device (3) and retrieved from a plan database (81) of said remote application device (4), by means of a plan customization module (75) of said user interface device (3).

10. The method for calculating optimal product purchase choices according to claim 9, wherein said modification step (30), performed by said plan customization module (75), comprises one or more of the steps that consists in: modifying (31) the goals of said user (2) for the purchase of durable goods; modifying (32) the financial risk profile of said user (2); modifying (33) the insurance risk profile of said user (2); modifying (34) the credit profile of said user (2); and indicating (35) the relationships with other life cycle plans.

11. The method for calculating optimal product purchase choices according to any one of the preceding claims, further comprising the step that consists in defining (60) the goals and criteria to be optimized and those to be penalized within said life cycle plan of said user (2), by means of a criteria optimization module (85) of said remote application device (4).

12. The method for calculating optimal product purchase choices according to claim 11, wherein said definition step (60), performed by said criteria optimization module (85), comprises the steps that consist in: selecting (61) a goal/criterion to be optimized; selecting (62) a goal/ criterion to be penalized; selecting (63) other goals/criteria to be disregarded; and calculating (64) the outcome of said goals/criteria optimization based on the selections in the preceding steps (61) to (63).

13. The method for calculating optimal product purchase choices according to claim 12, wherein said definition step (60), performed by said criteria optimization module (85), comprises furthermore the step that consists in inferring (65) an intelligible history of the life cycle plan of said user (2) based on the selections in the preceding steps (61) to (63).

14. A system (1) for calculating optimal product purchase choices, comprising at least one user interface device (3), operated by a user (2), at least one remote application device (4), and at least one remote calculation device (5), which are connected and in communication by means of a telematic communication network, each device (3, 4, 5) being provided with an electronic control unit, a memory, and a transceiver; said remote application device (4) comprises an automatic profiling module (83) configured to create automatically a life cycle plan based on the age of said user (2) and optionally on other sociodemographic data of said user (2); said remote calculation device (5) comprises a choice optimization module (92) and a scenario simulation module (94) which are configured to analyze the sustainability of said life cycle plan of said user (2), representing the results of said analysis in the form of simulated scenarios; and said user interface device (3) comprises a product offer module (73) configured to provide said user (2) with a set of sustainable products, retrieved from a product database (82) of said remote application device (4), previously calculated by said choice optimization module (92) of said remote calculation device (5) based on said life cycle plan of said user (2).

15. The system (1) for calculating optimal product purchase choices according to claim 14, wherein said automatic profiling module (83) is furthermore configured to: select the age of said user (2); optionally, select other sociodemographic data of said user (2); infer a net income based on the age and the other sociodemographic data of said user (2); infer statistically an average saving and its uncertainty based on said net income; and infer said life cycle plan of said user (2) based on said saving.

16. The system (1) for calculating optimal product purchase choices according to claim 14 or 15, wherein said choice optimization module (92) and said scenario simulation module (94) are furthermore configured to: calculate the optimization of said product purchase choices based on said life cycle plan of said user (2); and calculate the simulation of the results over time of said product purchase choices.

17. The system (1) for calculating optimal product purchase choices according to any one of claims 14 to 16, wherein said remote application device (4) further comprises a scenario management module (84) and said user interface device (3) comprises furthermore a graphic representation module (74), which are configured to: generate and display a chart representing wealth scenarios over time; generate and display a chart representing damage risk scenarios covered or not covered by insurance policies; and generate and display a chart representing credit default risk scenarios.

18. The system (1) for calculating optimal product purchase choices according to any one of claims 14 to 17, wherein said product offer module (73) is furthermore configured to: provide sustainable durable goods; provide sustainable financial products; provide sustainable insurance products; provide sustainable credit products; and provide products for relationship with other life cycle plans.

19. A system (1) for calculating optimal product purchase choices according to any one of claims 14 to 18, wherein said user interface device (3) further comprises a user access module (71) configured to verify the identity of said user (2) and, if said verification has a positive outcome, authorize the entry of said user (2) in said system (1).

20. The system (1) for calculating optimal product purchase choices according to claim 19, wherein said user access module (71) is furthermore configured to: enter an identifier of said user (2); enter a password of said user (2); verify the identity of said user (2) based on said identifier and said password entered by said user (2) and, in case of positive outcome, authorize entry; and choose between creating a new life cycle plan or selecting a life cycle plan to be customized.

21. The system (1) for calculating optimal product purchase choices according to claim 19 or 20, wherein said user access module (71) is furthermore configured to signal one or more notifications to said user (2).

22. The system (1) for calculating optimal product purchase choices according to any one of claims 14 to 21, wherein said user interface device (3) further comprises a plan customization module (75) configured to modify an existing life cycle plan, searched and selected by said user (2) by means of a plan search module (72) of said user interface device (3) and retrieved from a plan database (81) of said remote application device (4).

23. The system (1) for calculating optimal product purchase choices according to claim 22, wherein said plan customization module (75) is furthermore configured to: modify the goals of said user (2) for purchasing durable goods; modify the financial risk profile of said user (2); modify the insurance risk profile of said user (2); modify the credit profile of said user (2); and indicate the relationships with other life cycle plans.

24. The system (1) for calculating optimal product purchase choices according to any one of claims 14 to 23, wherein said remote application device (4) further comprises a criteria optimization module (85) configured to define the goals and criteria to be optimized and those to be penalized within the scope of said life cycle plan of said user (2).

25. The system (1) for calculating optimal product purchase choices according to claim 24, wherein said criteria optimization module (85) is furthermore configured to: select a goal/criterion to be optimized; select a goal/criterion to be penalized; select other goals/criteria to be disregarded; and calculate the outcome of said goals/criteria optimization based on the preceding selections.

26. The system (1) for calculating optimal product purchase choices according to claim 25, wherein said criteria optimization module (85) is furthermore configured to infer an intelligible history of the life cycle plan of said user (2) based on the preceding selections.