Financial business support apparatus and financial business support method

Abstract

To accurately predict the balance of future funds of a borrower, and support funding under conditions favorable to both lender and borrower.SOLUTION: A financial business support apparatus 1 includes: a storage unit which stores financial instrument information, which is design information of a financial instrument for extending funds to a business operator, and conditions on an index value that indicates operational capability of the business operator, which is necessary for extending funds with the financial instrument to the business operator; and a control apparatus which executes an order reception prediction process for predicting a probability distribution of future fixed order quantity, by a predetermined algorithm, based on input preliminary order reception information indicating unfixed order reception, in the business operator, a funding prediction process for predicting the balance of funds of the business operator at the time of a future predetermined point of time, based on a result of the prediction, and an output generation process for outputting, to an output device, information indicating the predicted balance of funds.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a financial business support device and a financial business support method. [Background technology]

[0002] Small and medium-sized enterprises usually request loans from financial institutions by presenting various information in order to continue their business and make capital investments. However, if financial institutions lack information such as the credit information or deposit and withdrawal history of small and medium-sized enterprises, it is difficult for them to accurately estimate the default risk, which significantly affects the content of the loan. On the other hand, it is also difficult for small and medium-sized enterprises to demonstrate to financial institutions that they have a low default risk. For this reason, financial institutions are forced to overestimate the default risk, which may result in them being unable to expand loans to small and medium-sized enterprises.

[0003] As a technology to assist financial institutions in estimating the risk of default, for example, Patent Document 1 describes a system that receives a loan amount requested by a borrower company, predicts a future cash balance distribution based on the borrower company's past cash balance, calculates a future default probability based on the loan amount requested and the cash balance distribution, determines an interest rate based on the default probability, and returns loan information including the interest rate to the borrower company. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2020-13229 A Summary of the Invention [Problem to be solved by the invention]

[0005] In Patent Document 1, the future cash balance distribution of a company, which is necessary for determining the default probability, is predicted based on the past cash balance records. However, the cited document 1 has a problem that it is difficult to accurately predict the future cash balance unless the past trend in the company's cash balance continues or there is no periodicity such as seasonality.

[0006] In addition, in Patent Document 1, the interest rate on the loan is determined based on the desired loan amount and the future default probability calculated based on the cash balance distribution. However, since various conditions (loan amount, loan timing, etc.) are attached to the loan, it is possible to lower the interest rate by taking these conditions into account, but Patent Document 1 does not sufficiently consider such a point.

[0007] The present invention has been made in consideration of such problems, and aims to provide a financial operations support device and method that are capable of accurately predicting the future financial balance of a borrower of funds, and supporting the lending of funds on terms favorable to both the lender and the borrower. [Means for solving the problem]

[0008] One of the present inventions for solving the above problems is a financial business support device that includes a storage device that stores financial product information, which is design information for a financial product that lends funds to a business, and conditions related to index values ​​representing the business's business capability that are necessary for lending funds to the business using the financial product, and a control device that executes an order prediction process that takes as input unconfirmed order information from the business and predicts the probability distribution of future confirmed order numbers using a predetermined algorithm based on the input unconfirmed order information, a cash flow prediction process that predicts the business's cash balance at a predetermined future point in time based on the prediction results, and an output generation process that outputs information indicating the predicted cash balance to an output device. Effect of the Invention

[0009] According to the present invention, it is possible to accurately predict the future balance of funds of a borrower of funds, and to assist in lending funds under favorable conditions for both the lender and the borrower of funds. Configurations and effects other than those described above will become apparent from the following description of the embodiments. [Brief description of the drawings]

[0010] [Figure 1] 1 is a diagram illustrating an example of a configuration of a financial operation support system according to an embodiment of the present invention. [Diagram 2] FIG. 13 is a diagram showing an example of a flow of a financial business support process. [Diagram 3] FIG. 13 is a diagram showing an example of a registration confirmation screen. [Figure 4] FIG. 13 is a diagram showing an example of a fund raising necessity determination screen. [Diagram 5] FIG. 11 is a flow diagram illustrating details of a prediction process. [Figure 6] FIG. 11 is a diagram showing an example of order record information. [Figure 7] 13 is a graph showing an example of a forecast using the firm order forecast model represented by Equation 2. [Figure 8] 1 is a graph illustrating a prediction of the probability distribution of future firm order quantities predicted by a firm order forecast model. [Figure 9] 13 is a graph illustrating a prediction of the probability distribution of future confirmed order amounts calculated using Equation 4. [Figure 10] FIG. 13 is a diagram illustrating an example of order amount forecast information that is output. [Figure 11] FIG. 13 is a diagram showing an example of deposit and withdrawal information. [Figure 12] FIG. 13 is a diagram showing an example of cash balance information. [Figure 13] 1 is a graph illustrating a prediction of a future cash balance based on a cash flow forecasting model. [Figure 14] 13 is an example of output cash flow forecast information. [Figure 15] FIG. 11 is a diagram showing an example of CO2 emission intensity information. [Figure 16]FIG. 13 is a diagram showing an example of output business feasibility evaluation information. [Figure 17] FIG. 11 is a flow diagram illustrating details of a fund raising plan formulation process. [Figure 18] FIG. 2 is a diagram showing an example of financial product information. [Figure 19] FIG. 13 is a diagram showing an example of fund raising plan information to be output. [Figure 20] FIG. 13 is a diagram showing an example of a recommended financing plan display screen. [Figure 21] FIG. 13 is a diagram showing an example of an examination screen. [Figure 22] FIG. 13 is a diagram showing an example of an examination result display screen. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. This embodiment is an example for explaining the present invention, and appropriate omissions and simplifications are made for clarity of explanation. The present invention can be implemented in various other forms. Unless otherwise specified, each component may be singular or plural.

[0012] In addition, in order to facilitate understanding of the invention, the position, size, shape, range, etc. of each component shown in the drawings may not represent the actual position, size, shape, range, etc. Therefore, the present invention is not necessarily limited to the position, size, shape, range, etc. disclosed in the drawings.

[0013] 1 is a diagram showing an example of the configuration of a financial business support system 100 according to this embodiment. The financial business support system 100 includes information processing devices, namely, a financial institution server 9, an investment institution server 10, and one or more user terminals 8. These information processing devices are communicatively connected to each other via a wired or wireless communication network 6, such as the Internet, a LAN (Local Area Network), a WAN (Wide Area Network), a VPN (Virtual Private Network), or a dedicated line.

[0014] The user terminal 8 is an information processing device used by a business operator (hereinafter referred to as a user, for example, a small or medium-sized enterprise) performing a specified business. This business operator is a borrower of funds (loan recipient) who seeks to receive financing from a financial institution or investment institution to perform the business. The user terminal 8 is, for example, a device such as a PC (personal computer), a workstation, a server device, a smartphone, or a tablet terminal. The user terminal 8 outputs the results of execution of each program described below in a format that can be confirmed by the user, and can also receive data input from the user.

[0015] The financial institution server 9 and the investment institution server 10 are each an information processing device managed by a lender that provides funds (loans) to users. Specifically, the financial institution server 9 is an information processing device used by a financial institution. The investment institution server 10 is an information processing device used by an investment institution. Below, the financial business support system 100 of this embodiment will be explained with a focus on the financial institution server 9, but the functions of each information processing device are similar in the financial institution server 9 and the investment institution server 10.

[0016] The financial operations support device 1 is an information processing device that supports financial operations by a lender for a user who is a borrower. That is, in response to a request from a user (user terminal 8), the financial operations support device 1 predicts the user's future fund balance and creates a fund raising plan that is suitable for the user and can be lent by the lender based on the predicted fund balance. The financial operations support device 1 provides the created fund raising plan to the user (user terminal 8), and the user (user terminal 8) receives funds from the lender based on the fund raising plan.

[0017] The financial business support device 1 is composed of one or more information processing devices. Specifically, the financial business support device 1 includes various hardware including an arithmetic device 3 (control device) such as a central processing unit (CPU), a digital signal processor (DSP), a graphics processing unit (GPU), a field-programmable gate array (FPGA), or an application specific integrated circuit (ASIC), a storage device 2 such as a random access memory (RAM), a read only memory (ROM), a hard disk drive (HDD), or a solid state drive (SSD), and a communication device 4 including a network interface card (NIC), a wireless communication module, a universal serial bus (USB) module, or a serial communication module. The financial business support device 1 may include an input device such as a keyboard, a mouse, or a touch panel, and a display device such as a liquid crystal monitor or a liquid crystal display (LCD). The user terminal 8, the financial institution server 9, and the investment institution server 10 also include similar hardware.

[0018] Next, the functions of the financial business support device 1 will be described. First, the financial business support device 1 stores order record information i1, which is information on the history of each case of business for which the user has received a provisional notice, deposit and withdrawal information i2, which is information on the planned deposit to the user or withdrawal from the user, cash balance information i3, which is information on the user's daily deposit balance, business feasibility evaluation model information i4, which is information on a mathematical model for calculating an index value (hereinafter referred to as a business feasibility evaluation score) representing the user's business capability (future growth potential of the business, etc.), and financial product information i5, which is design information of each financial product (interest rate, fee, repayment period, etc.). The financial product information i5 includes information on conditions related to the business feasibility evaluation score (hereinafter referred to as a lending allowance range) necessary for lending funds to the user through financial products.

[0019] In addition, the financial business support device 1 outputs each piece of information: order amount forecast information o1, which is forecast information such as the number of cases for which the user has received a tentative indication that will result in a definite order in the future; cash flow forecast information o2, which is forecast information on the balance of funds (deposit balance in this embodiment); business feasibility evaluation information o3, which is information on the business feasibility score, which is a parameter representing the user's business ability; and fund raising plan proposal information o4, which is information on the fund raising plan to raise funds from lenders (financial institutions or investment institutions).

[0020] Furthermore, the financial operation support device 1 has the following functional units (programs): an order forecasting unit f1, a cash flow forecasting unit f2, a business feasibility evaluation unit f3, a fund raising plan formulation unit f4, and an output generation unit f5.

[0021] The order forecasting unit f1 inputs order data whose order deadline is a future date, and predicts the probability distribution of future confirmed order quantities. Specifically, first, the order forecasting unit f1 creates a confirmed order forecasting model in advance based on past data on the unofficial order numbers and confirmed order numbers stored in the order record information i1. The confirmed order forecasting model is a model in which information on unofficial order numbers that have been received but are not yet confirmed as to whether they will be accepted is used as an input value, and the confirmed order number after the future order closing date is used as an output value. In this case, once the date of the "order closing date" has passed, the unofficial order numbers that have not been confirmed become invalid. In this embodiment, this output value is output as a probability distribution (probability value) of the confirmed order numbers, but the output value may also be a probability distribution or probability value of the ratio to the number that is the input value. The above order data, which is the input value for the confirmed order forecast model, is stored in actual order performance information i1, and as will be described in detail later, contains information on whether the orders received by the company as of a certain date in the past were unofficial or confirmed, and the number of orders. The order forecasting unit f1 predicts the probability distribution of future confirmed order quantities using such an algorithm. Then, the order forecasting unit f1 generates order amount forecast information o1, which is forecast information on future order amounts, based on the prediction results.

[0022] The cash flow forecasting unit f2 predicts the user's cash balance at a specified future point in time based on the prediction results (order amount forecast information o1) made by the order forecasting unit f1 using a cash flow forecasting model described below, and generates cash flow forecast information o2.

[0023] In this embodiment, the balance of funds to be predicted is the user's deposit balance. Also, in this embodiment, the cash flow prediction unit f2 predicts the probability distribution of the user's future deposit balance.

[0024] The business feasibility evaluation unit f3 calculates a business feasibility evaluation score for the user based on the cash flow forecast information o2 generated by the cash flow forecasting unit f2.

[0025] The fundraising plan drafting unit f4 drafts one or more fundraising plans (e.g., loan amount, deposit date) for the provision of funds to a user through financial products based on the financial product information i5, calculates a business feasibility assessment score to be achieved in the future by the lending of funds under each fundraising plan based on each of the drafted fundraising plans and the fund balance predicted by the cash flow forecasting unit f2, and identifies, from among the calculated business feasibility assessment scores, fundraising plans that satisfy the above-mentioned lending tolerance range.

[0026] The output generating unit f5 outputs information indicating the fund raising plan identified by the fund raising plan formulation unit f4 to an output device such as the user terminal 8.

[0027] Each functional unit of the financial business support apparatus 1 described above is realized by the arithmetic unit 3 reading and executing each program stored in the storage device 2. Further, each program can be recorded on a recording medium and distributed, for example. Note that the financial business support apparatus 1 may be realized using virtual information processing resources provided using virtualization technology, process space separation technology, or the like, such as a virtual server provided by a cloud system, for example, for all or part of it. Also, all or part of the functions provided by the financial business support apparatus 1 may be realized by services provided by a cloud system via an API (Application Programming Interface) or the like.

[0028] FIG. 2 is a diagram showing an example of a flow of a financial business support process for supporting a user's financing in the financial business support system 100. The financial business support process starts, for example, when the financial business support apparatus 1 receives a predetermined request from the user terminal 8 related to a certain company (hereinafter referred to as the designated company).

[0029] The financial business support apparatus 1 reads input data (order performance information i1, deposit / withdrawal information i2, cash balance information i3, business evaluation model information i4, and financial product information i5) (step s101). Note that the financial business support apparatus 1 may receive this information from an information processing apparatus other than the financial business support apparatus 1 (user terminal 8, financial institution server 9, investment institution server 10, or a predetermined database, etc.).

[0030] Further, the financial business support apparatus 1 may display the registration confirmation screen d10 described below on the screen of the enterprise user terminal 8 and accept designation of input data from the user.

[0031] (Registration confirmation screen) FIG. 3 is a diagram showing an example of a registration confirmation screen d10. The registration confirmation screen d10 includes an editing column d11 that displays the content of the order reception result information i1 and accepts editing from the user, an editing column d12 that displays the content of the payment information i2 and accepts editing from the user, an editing column d13 that displays the content of the cash balance information i3 and accepts editing from the user, and a start button d14 that accepts an instruction to end the editing of the input data from the user.

[0032] Next, as shown in FIG. 2, the financial business support apparatus 1 executes an order reception and fund flow prediction process s102 for predicting the future confirmed order number and the future remaining balance of funds based on the internal order reception number received by the target company (step s102). The financial business support apparatus 1 outputs order amount prediction information o1, fund flow prediction information o2, and business profitability evaluation information o3 based on the result of the process of the order reception and fund flow prediction process s102. The details of the order reception and fund flow prediction process s102 will be described later.

[0033] The financial business support apparatus 1 transmits data related to the remaining balance of funds to be presented to the target company (fund flow prediction information o2 and business profitability evaluation information o3 including information on the business profitability evaluation score) to the user terminal 8 related to the target company (step s103). The user terminal 8 displays a screen showing the received data content.

[0034] The user terminal 8 determines whether or not the target company needs to raise funds based on the received data or the displayed screen (step s104).

[0035] For example, the user terminal 8 displays a fund raising necessity determination screen d20 described below and accepts an input of information indicating whether or not the target company needs to raise funds from the target company.

[0036] In addition, the user terminal 8 may perform an automatic determination to output information indicating whether or not the target company needs to raise funds based on the data received from the financial business support device 1 by a predetermined algorithm or model. For example, the upper and lower limit values of the business evaluation score are set in advance in the user terminal 8. When the value of the business evaluation score received from the financial business support device 1 is equal to or higher than the lower limit value and equal to or lower than the upper limit value, the user terminal 8 outputs information indicating that no fund-raising is required. When the value of the business evaluation score received from the financial business support device 1 is less than the lower limit value or exceeds the upper limit value, the user terminal 8 outputs information indicating that fund-raising is required. Also, for example, the user terminal 8 learns the past fund flow prediction result o2 and the performance data of the determination result of whether or not the enterprise associated therewith needs to raise funds by a machine learning method such as deep learning to generate a decision-making model, and inputs the fund flow prediction result o2 into the decision-making model, so that a fund-raising requirement determination result similar to the past determination of whether or not to raise funds can be obtained as an output.

[0037] (Fund-raising Requirement Judgment Screen) FIG. 4 is a diagram showing an example of a fund-raising requirement judgment screen d20. The fund-raising requirement judgment screen d20 includes a graph display column d21 for displaying a graph of the fund flow prediction result based on the fund flow prediction information o2, a radar chart display column d22 for displaying a radar chart of the business evaluation result based on the business evaluation information o3, an automatic determination execution button d23 pressed by the user from the user terminal 8 when performing the above-described automatic determination process, a fund-raising requirement determination button d24 pressed by the user terminal 8 when it is determined that the target company needs to raise funds, and a fund-raising unnecessary determination button d25 pressed by the user terminal 8 when it is determined that the target company does not need to raise funds.

[0038] In the graph display column d21, a graph showing the transition of the balance of the target company (past performance and future predicted values) is displayed. Specifically, this graph displays the average value of the predicted value of the cash balance and the interval (probability distribution) within which the predicted value falls with a predetermined probability (95%, 70%, etc.).

[0039] In the radar chart display column d22, a radar chart showing the values of various types of business scores is displayed. Specifically, in the radar chart display column d22, in addition to the business scores of the target company, the business scores of the industry average of the target company and the business scores of competing companies are displayed.

[0040] Subsequently, as shown in FIG. 2, when it is determined that the target company needs to raise funds (step s105: Yes), the user terminal 8 transmits predetermined information to the financial business support device 1, and the process of step s106 described below is performed in the financial business support device 1. When it is determined that the target company does not need to raise funds (step s105: No), the user terminal 8 transmits predetermined information to the financial business support device 1 and ends the process.

[0041] In step s106, the financial business support device 1 executes a fund-raising plan formulation process s106 for generating a fund-raising plan (step s106). The details of the fund-raising plan formulation process s106 will be described later.

[0042] Then, the financial business support device 1 stores the processing result of the fund-raising plan formulation process s106 in the fund-raising plan information o4 (step s107). The financial business support device 1 transmits the proposal information of the fund-raising plan indicated by the fund-raising plan information o4 to the user terminal 8.

[0043] When the user terminal 8 receives the proposal information, it determines a fund-raising plan that is preferable for the target company among the various fund-raising plans in the fund-raising plan information o4 (step s108).

[0044] For example, the user terminal 8 displays a recommended fund-raising plan display screen (described later) showing the content of the fund-raising plan information o4, and accepts the designation of a fund-raising plan from the user of the target company. Alternatively, the user terminal 8 may generate and store in advance a model for determining a preferable fund-raising plan in the same manner as in step s104, and input the fund-raising plan information o4 received from the financial business support device 1 into the model to automatically determine a preferable fund-raising plan.

[0045] After that, the user terminal 8 transmits information indicating a request for funds financing including the determined funding plan to the financial service support device 1.

[0046] When the financial service support device 1 receives the information on the request for funds financing from the user terminal 8, it transmits the information on the funding plan and the application information necessary for executing the funding plan (for example, the application content to be submitted to the financial institution and the information on the business evaluation score of the target company) to the financial institution server 9 (step s109).

[0047] When the financial institution server 9 receives each piece of information from the financial service support device 1, it determines whether to provide financing to the target company and the financing conditions based on the received information (step s110).

[0048] For example, the financial institution server 9 displays a review screen for receiving an input specifying whether to provide financing to the target company and the financing conditions from the person in charge of the financial institution (described later). Also, similar to steps s104 and s108, the financial institution server 9 may generate and store in advance a model for determining whether to provide financing to the target company and the financing conditions, and automatically determine whether to provide financing to the target company and the financing conditions by inputting the information received from the financial service support device 1 into the model.

[0049] The financial institution server 9 transmits the information on the content determined in step s110 (information on the approval or disapproval of financing or the review result) to the financial service support device 1 (step s111).

[0050] The financial service support device 1 transmits the received review result information to the user terminal 8 and causes the user terminal 8 to display a review result display screen (described later) showing the review result information (step s112).

[0051] After that, based on the review result display screen displayed on the user terminal 8, the target company determines whether to receive financing or not (step s113).

[0052] Note that, similar to step s104, the user terminal 8 may also generate and store in advance a model for determining whether to receive financing or not, and automatically determine whether to receive financing or not by inputting the information of the review result received from the financial business support device 1 into the model.

[0053] In the above financial business support process, the financial business support device 1 is configured to mediate the transmission and reception of data between the user terminal 8 and the financial institution server 9 (steps s109, step s112), but the user terminal 8 and the financial institution server 9 may directly transmit and receive data.

[0054] Also, each determination in steps s104, s108, and s110 may be executed interactively using a predetermined generative AI (Generative Artificial Intelligence) stored in the financial business support device 1.

[0055] For example, in step s104, using the generative AI installed in the financial business support device 1, the enterprise may be able to analyze, confirm, and make decisions on the details of the prediction result of the fund balance interactively. In step s108, using the generative AI installed in the financial business support device 1, the enterprise may be able to analyze, confirm, select, and apply for the details of the financing plan interactively. In step s110, using the generative AI installed in the financial business support device 1, financial institutions and investment institutions may be able to analyze, confirm, and review the details of the application content interactively. Also, the financial business support device 1 may generate output data such as screens and transmission content using the generative AI. Next, the details of the order receiving and cash flow prediction process s102 and the financing plan formulation process s106 will be described.

[0056] <Order Receiving and Cash Flow Prediction Process> FIG. 5 is a flowchart for explaining the details of the order receiving and cash flow prediction process s102. First, the order reception prediction unit f1 learns a confirmed order prediction model based on the historical performance data of the internal order numbers and the confirmed order numbers stored in the order reception performance information i1. The confirmed order prediction model takes, as input values, information on the internal order numbers for which an internal order has been received but whether an order will be placed is uncertain, and outputs, as output values, the probability distribution of the confirmed order numbers after a predetermined future order deadline (step s102-1).

[0057] (Order reception performance information) Here, FIG. 6 is a diagram showing an example of the order reception performance information i1 used for creating the confirmed order prediction model. This order reception performance information i1 includes, for each order received by the company at a certain past "date", the product code i12 of the product, the order deadline i13 of the order, the order type i14 of the order, the name i15 of the company that is the order source (the delivery destination company) and the classification i16 of the company, the order quantity i17 of the product in the order (unit: CS (number of cases)), the unit price i18 of the order, and each data of the scheduled payment date i19 of the sales amount related to the order.

[0058] The order type i14 is data that can identify whether the order is an internal order (uncertain order), a confirmed order (confirmed order), or invalid. When the current date exceeds the scheduled payment date i19, data indicating invalid is set for the order type i14.

[0059] Note that the data described here is an example. For example, the order reception performance information i1 may have data on the cumulative number of months since the start of transactions with the order source in addition to the company classification i16. Also, in this embodiment, the unit of the order quantity i17 is CS, but other units such as the number of pieces, the number of pallets, the number of talents, the number of liters, the number of tons, and the amount may be used.

[0060] Here, due to the characteristics of the order receipt performance information i1, which is the learning data, in the confirmed order prediction model created, the longer the number of days from the time of predicting the number of confirmed orders for the target case to the order closing date of that target case, the greater the deviation of the output value of the confirmed order prediction model (the deviation of the value of the ratio of the number of confirmed orders to the indicated number of orders). On the contrary, the shorter the number of days from the time of predicting the number of confirmed orders for the target case to the order closing date of that target case, the smaller the deviation of the output value of the confirmed order prediction model. Therefore, the uncertainty of the predicted value of the ratio of the number of confirmed orders to the indicated number of orders (the range of values that can be taken in the probability distribution) varies depending on the number of days from the time of prediction to the order closing date.

[0061] Therefore, in this embodiment, an example of the confirmed order prediction model f1 is represented by the following Equation 1. Equation 1 assumes that the probability distribution f1 of the number of confirmed orders to be obtained in the future, when the indicated number of orders oFore and the number of days t from the time of prediction to the order closing date are given, follows a normal distribution with a mean μ and a variance σ 2 is an example.

[0062]

Equation

[0063] Here, N is the probability density function representing the normal distribution with a mean μ and a variance σ 2 is.

[0064] Here, an explanation of the estimation method of the mean μ and the variance σ 2 in Equation 1 will be given. The order prediction unit f1 extracts all the records whose order closing date i13 is a past date from among the records of each case in the order receipt performance information i1, and identifies the indicated number of orders and the number of confirmed orders by checking the order type i14 of each extracted record. The order prediction unit f1 calculates the number of days from the time of prediction to the order closing date for each by referring to the date i11 and the order closing date i13 in each extracted record. Based on the identified indicated number of orders and the number of confirmed orders, and the calculated number of days, the order prediction unit f1 identifies the distribution of the number of confirmed orders for each number of days, and using a predetermined statistical method, the mean μ and the variance σ 2Estimate it.

[0065] In addition to Equation 1, the order reception prediction unit f1 may create the following Equation 2, for example, to calculate the ratio f2(t) of the confirmed order quantity to the indicated order quantity when the number of days t from the time of prediction implementation to the order reception deadline is given.

[0066]

Equation

[0067] Here, FIG. 7 is a graph showing an example of prediction by the confirmed order prediction model represented by Equation 2. In this case, the order reception prediction unit f1 extracts a plurality of actual values d1 by specifying data on the number of days from the time of prediction implementation to the order reception deadline for each past case where the order quantity has been confirmed from the order reception actual result information i1, and based on each extracted actual value d1, estimates the mean μ and variance σ 2 Estimate it.

[0068] As shown in FIG. 7, in this confirmed order prediction model, the longer the number of days t from the time of prediction implementation to the order reception deadline, the larger the variance (spread width) of the probability distribution f1(t) of the ratio of the confirmed order quantity to the indicated order quantity, and the shorter the number of days t, the smaller the variance of f1(t). Specifically, an interval d3(t) within which the value of the probability distribution f1(t) falls within 95% of its range and an interval d4(t) within which the value of the probability distribution f1(t) falls within 70% of its range are calculated respectively centered around the mean value d5(t) of the probability distribution f1(t).

[0069] Here, the order reception prediction unit f1 may add other explanatory variables to the explanatory variables (indicated order quantity, confirmed order quantity) of Equation 1. For example, the name i15 of the order source, the classification i16 of the order source, or information on the cumulative number of months since the start of the transaction with the order source in the order reception actual result information i1 may be added as explanatory variables. Alternatively, information on date-specific sales promotion campaigns or events, or information on the presence or absence of date-specific supply chain disruptions due to disasters, etc. may be added as explanatory variables. For example, when the order source b, the classification c, and the cumulative number of months p are added as explanatory variables, Equation 2 becomes as follows in Equation 3.

[0070]

Number

[0071] Note that the above equations 1-3 assume that the distribution of the firm orders follows a normal distribution, but other arbitrary value distribution forms may also be assumed.

[0072] Also, the firm order prediction model described above may not be a function like equations 1-3, but may be represented in other forms. For example, the firm order prediction model may be a trained model consisting of an input layer, an intermediate layer, and an output layer (neural network), or a model based on multivariate analysis. And the generation method of these models is not limited to statistical methods, and may also be generated by methods such as machine learning including deep learning.

[0073] Next, as shown in FIG. 5, the order prediction unit f1 inputs the information of the unconfirmed cases into the firm order prediction model generated in step s102-1 to predict the probability distribution of the number of future firm order cases (firm order number) (step s102-2).

[0074] For example, first, the order prediction unit f1 extracts the records whose order closing date i13 is a future date from each record of the order performance information i1, and inputs the data of the extracted records into the firm order prediction model as the values of the explanatory variables in the above equations 1 to 3.

[0075] Then, the order prediction unit f1 calculates the firm order amount mFix by future payment scheduled date based on the predicted firm order number. For example, the order prediction unit f1 multiplies the predicted value oFix of the firm order number by the unit price ui (unit price i18) for each order i (∈ set I) (product code i12) stored in the order performance information i1 based on the following equation 4, and aggregates by the payment scheduled date t receive (payment scheduled date i19) to calculate the firm order amount mFix by future payment scheduled date.

[0076] [Number]

[0077] Then, the order reception prediction unit f1 outputs the predicted value of the probability distribution of the confirmed order amount to the order amount prediction information o1.

[0078] Here, FIG. 8 is a graph for explaining the prediction of the probability distribution of the future confirmed order quantity predicted by the confirmed order prediction model. The order reception prediction unit f1 predicts the probability distribution of the confirmed order quantity by inputting each actual value d11 of the indicated order quantity into the confirmed order prediction model. In the probability distribution of the confirmed order quantity, the average d15 of the confirmed order quantity, the interval d13 where the probability that the predicted value of the confirmed order quantity falls is 95%, and the interval d14 where the probability is 70% are calculated respectively.

[0079] Also, FIG. 9 is a graph for explaining the prediction of the probability distribution of the future confirmed order amount calculated by Equation 4. First, the order reception prediction unit f1 predicts the probability distribution of the confirmed order amount by inputting the predicted value oFix of the confirmed order quantity into Equation 4. In the probability distribution of the confirmed order amount, the average d25 of the confirmed order amount, the interval d23 where the probability that the predicted value of the confirmed order amount falls is 95%, and the interval d24 where the probability is 70% are calculated respectively.

[0080] (Order amount prediction information) And, FIG. 10 is a diagram showing an example of the order amount prediction information o1 output by the order reception prediction unit f1. The order amount prediction information o1 has information on the scheduled payment date o11 of each case and the predicted value o12 regarding the confirmed order amount (on the probability distribution) of each case. Each predicted value o12 has information on the average amount o121 of the confirmed order amount and the variance o121 of the confirmed order amount. Note that in the order amount prediction information o1, the lower limit and upper limit of the interval where the probability that the predicted value of the confirmed order amount falls is M% (M is a real number between 0 and 100) may be set. Also, the figure is an example of the order amount prediction information o1 when the confirmed order amount follows a normal distribution. When the confirmed order amount follows other probability distributions, parameter values characterizing the probability distribution other than the mean and variance are set in the order amount prediction information o1.

[0081] Next, as shown in FIG. 5, the cash flow prediction unit f2 predicts the future balance of funds (the deposit balance in this embodiment) based on the probability distribution of the future confirmed order amount predicted in step s102-2, the cash flow information i2 (information on each schedule of future accounts receivable, accounts payable, cash disbursements due to facility investments, etc. stored therein), and the cash balance information i3 (information on the cash balance at the time of prediction stored therein) (step s102-3).

[0082] (Cash flow information) Here, FIG. 11 is a diagram showing an example of the cash flow information i2 used for predicting the future balance of funds. The cash flow information i2 has each data of the date (cash flow date i21) on which a cash inflow or outflow is scheduled, the distinction between cash inflow and outflow (cash flow type i22), the classification i23 of the cash inflow or outflow, the information on the product (product code i24) related to the case to which the cash inflow or outflow pertains, the name of the business partner i25 related to the case to which the cash inflow or outflow pertains, and the amount i26 of the cash inflow or outflow. The cash flow type i22 is data for specifying, for example, types of accounts receivable, accounts payable, and expenses (such as facility investments).

[0083] (Cash balance information) Also, FIG. 12 is a diagram showing an example of the cash balance information i3 used for predicting the future balance of funds. The cash balance information i3 has each data of the date i31, the financial institution code i32 of the financial institution, the type of deposit i33, and the deposit balance i34 on that date in the deposit.

[0084] Based on the deposit and withdrawal information i2 and the cash balance information i3, the cash flow prediction unit f2 predicts the future cash balance as follows, for example. First, the cash flow prediction unit f2 calculates the future withdrawal amount for each date by aggregating the amount i26 in the deposit and withdrawal information i2 by date i21. Also, the cash flow prediction unit f2 calculates the future deposit amount for each date based on the predicted value of the probability distribution of the firm orders by the scheduled deposit date calculated in step s102-2 and the amount i26 by date i21 in the deposit and withdrawal information i2. Then, the cash flow prediction unit f2 calculates the probability distribution of the future cash balance for each date by adding the deposit amount with the prediction time as the deposit date to the cash balance at the prediction time obtained from the cash balance information i3 and subtracting the withdrawal amount with the prediction time as the withdrawal date.

[0085] The cash flow prediction unit f2 outputs the calculated probability distribution of the future cash balance for each date to the cash flow prediction information o2.

[0086] Note that the cash flow prediction unit f2 creates an expression represented by, for example, Equation 5-7 below as a cash flow prediction model for predicting the cash balance on each future day t.

[0087] [Equation 5] Cash balance(t) = Cash balance(t0) - Σ τ=t0~t {Withdrawal amount(τ)} + Σ τ=t0~t {Deposit amount(τ)}

[0088] [Equation 6] Withdrawal amount(t) = Accounts payable(t) + Other scheduled withdrawal amounts such as capital investment

[0089] [Equation 7] Deposit amount(t) = Accounts receivable(t) + Predicted value of firm orders(t) - Booked firm orders(t) + Other scheduled deposit amounts such as financing

[0090] Here, t0 is the date of the prediction execution time (for example, the current date). In Equation 7 (the calculation formula for the deposit amount(t)), the booked firm orders are subtracted to avoid double-counting the booked firm orders among the firm orders.

[0091] Here, FIG. 13 is a graph for explaining the prediction of future cash balances predicted based on the cash flow prediction model. In the probability distribution of the cash balance, the average d35 of the cash balance, the interval d33 in which the predicted value of the cash balance falls with a probability of 95%, and the interval d34 in which the probability is 70% are calculated respectively.

[0092] (Cash flow prediction information o2) FIG. 14 is an example of the output cash flow prediction information o2. The cash flow prediction information o2 has data of a code o21 (cash flow prediction information code) assigned for each prediction of the balance of funds (deposit balance), the target date o22 of the prediction of the balance of funds, and the predicted value o23 (average value o231, lower limit o232, and upper limit o233) of the cash balance on the target date. The lower limit o232 and the upper limit o233 are data of the lower limit amount and the upper limit amount of the predicted value when the predicted value of the cash balance falls within each predetermined ratio (for example, 95%). A plurality of predicted values o23 may be set for each predetermined ratio (70%,...).

[0093] Note that the cash flow prediction information o2 described here is an example. The cash flow prediction information o2 may have, for example, data of the average value of the predicted value of the cash balance and the lower limit amount and the upper limit amount of the interval in which the probability that the predicted value of the cash balance falls is L% (L is an arbitrary real number from 0 to 100), with the "cash flow prediction information code" and "date" numbered for each prediction as keys.

[0094] Next, as shown in FIG. 5, the business evaluation unit f3 calculates a business evaluation score based on the prediction result of the balance of funds in step s102-3 and the business evaluation model stored in the business evaluation model information i4 (step s102-4).

[0095] Note that the business evaluation model can be expressed, for example, by the following formulas 8-10.

[0096] [Equation 8] Business evaluation score y = f2 (fund balance feature vector x)

[0097] [Number 9] The balance feature vector x = [average value of the deposit balance during period T, minimum value of the deposit balance during period T, average value of the operating funds during period T,...] T

[0098] [Number 10] Operating funds [month] = Deposit balance [$] ÷ (Average value of fixed costs [$ / month] + Average value of variable costs [$ / month])

[0099] Note that the period T in Equation 9 is an arbitrary aggregation period. Also, Equation 9 has, as features of the balance feature vector x, the average value and minimum value of the future cash balance predicted in step s102-3, and the degree to which the cash balance contributes to the user's business continuation (for example, a value indicating how many months' worth of operating funds the cash balance is). However, the features of Equation 9 may also be other parameters. For example, it may be a value of the probability that the user's operating funds will be less than or equal to N months (N is an arbitrary real number) of business activities, calculated based on the probability distribution of the future cash balance predicted in step s102-3.

[0100] Here, an example of a method for generating a business performance evaluation model based on Equations 8-10 when the business performance evaluation score is the default rate, which is an evaluation index for default risk, will be described.

[0101] First, the business performance evaluation unit f3 acquires, as learning data, the actual values of the balance feature vector x in each of a plurality of enterprises and the actual values of the default history indicating whether or not each of these enterprises has defaulted (for example, a binary value where 1 indicates default and 0 indicates no default). Then, based on the acquired learning data, the business performance evaluation unit f3 creates a business performance evaluation model with the balance feature vector x as the input value and a value indicating the occurrence or non-occurrence of default as the output value. Note that this business performance evaluation model may be a logistic regression model created based on a predetermined statistical method, or may be a learned model that is a neural network model created by machine learning such as deep learning.

[0102] In the above description, the business evaluation model is constructed using learning data such as actual results. However, the business evaluation unit f3 may obtain a predetermined model created in advance from an external information processing device (for example, a financial institution server 9 or an investment institution server 10) via a communication network 6 or the like as the business evaluation model, and store it in the business evaluation model information i4. This model is, for example, a model executed by the financial institution server 9 in step s110 (examination (credit business) of an application for a financial product from a user), and is a model for calculating the degree to which the default rate, sales growth rate, or cash balance contributes to the continuation of the user's business. By using the model used in the business for examination or judgment in this way, the probability that the business evaluation score predicted in step s102-4 will be acceptable in subsequent examinations or judgments by financial institutions or investment institutions can be increased.

[0103] Next, an example of a method for generating a business evaluation model when the business evaluation score is the sales growth rate will be described. The business evaluation model for calculating the growth rate of sales compared to the previous year can be expressed by the following formula 11.

[0104] [Equation 11] Sales growth rate = Predicted value of future firm order amount [$ / month] ÷ Actual value of firm order amount in the previous year [$ / month]

[0105] Note that Equation 11 can be applied not only to sales amounts but also to the growth rate of the quantity of sales or the number of delivery destination companies that are the order sources.

[0106] Next, an example of a method for generating a business evaluation model when the business evaluation score is the amount of CO2 emissions discharged with the sale of a product will be described. First, the business evaluation unit f3 obtains information on the CO2 emission factor (emission coefficient) for each product (CO2 emission factor information).

[0107] (CO2 emission factor information) FIG. 15 is a diagram showing an example of the CO2 emission factor information 1500. The CO2 emission factor information 1500 stores the product code 1501 of each product and the CO2 emission factor 1502 of each product.

[0108] Then, the business evaluation unit f3 calculates the CO2 emission amount based on the CO2 emission per unit using the following Equation 12 as a business evaluation model.

[0109] [Equation 12] CO2 emission amount [kg] = Number of future product orders [CS] × CO2 emission per unit [kg / CS]

[0110] As described above, the case where the business evaluation score is the sales growth rate, the CO2 emission amount, and the default rate has been explained. However, the business evaluation score may be, for example, the sales growth rate which is an evaluation index of business growth potential, a value indicating how many months' worth of working capital the cash balance is as an evaluation index of business sustainability, or other index scores such as the value of the emission amount of greenhouse gases such as CO2 as an evaluation index of environmental impact. In the following, it is assumed that the business evaluation score is the default rate.

[0111] Note that the business evaluation score may be a comprehensive value obtained by combining the values of a plurality of evaluation indexes with predetermined weighting coefficients for each evaluation index. In this case, the business evaluation score is calculated, for example, by the following Equation 13.

[0112] [Equation 13] Business evaluation score y = Coefficient 1 × Default rate + Coefficient 2 × Sales growth rate + Coefficient 3 × Number of months the cash balance is the working capital + Coefficient 4 × CO2 emission amount +...

[0113] The output generation unit f5 outputs the calculated business evaluation score information to the business evaluation information o3.

[0114] (Business evaluation information o3) Figure 16 is a diagram showing an example of the output business evaluation information o3. The business evaluation information o3 has each data of the item o31 of the business evaluation score of the enterprise, the score value o32 of the business evaluation score, and the business evaluation score values o33 of other enterprises (the average value o331 in the same industry, the score values o332 of each competing enterprise).

[0115] <Fundraising Plan Proposal Establishment Process> Next, FIG. 17 is a flowchart for explaining the details of the fundraising plan proposal establishment process s106.

[0116] First, the fundraising plan establishment department f4 selects one financial product from the financial product information i5. Specifically, the fundraising plan establishment department f4 acquires one record from the financial product information i5 (step s106-1).

[0117] (Financial product information i5) FIG. 18 is a diagram showing an example of the financial product information i5. The financial product information i5 includes the code i51 of each financial product, the application destination i52 of that financial product, the allowable range i54 of each business evaluation score which is the condition (financing allowable range) under which the financial institution can provide that financial product (default rate i531 and sales increase rate i532), and each data of the details i54 of the design of that financial product (interest rate and fee i541, repayment period i542).

[0118] Next, as shown in FIG. 17, the fundraising plan establishment department f4 formulates an initial plan for fundraising using the financial product selected in step s106-1 (step s106-2). For example, the fundraising plan establishment department f4 arbitrarily sets each value such as the date of receipt of funds, the amount of financing, and the date of withdrawal of funds so as to satisfy the conditions indicated by the allowable range i54 of the record acquired in step s106-1.

[0119] The fundraising plan establishment department f4 sets parameters (for example, the upper limit value of the number of repetitions, the upper limit value of the processing time, or the lower limit value of the improvement amount of the business performance evaluation score value) for determining the number of repetitions of the processing in steps s106-4 to s106-7 described later, and then repeats the processing in steps s106-4 to s106-7 for the number of times indicated by the parameters (steps s106-3, s106-8).

[0120] That is, first, the fundraising plan formulation department f4 predicts the future cash balance based on the current fundraising plan proposal using financial products, the order amount prediction information o1, and the cash flow prediction information o2 (step s106-4). Specifically, the fundraising plan formulation department f4 predicts the cash balance for each future day based on the cash flow prediction model, similar to step s102-3 described above.

[0121] For example, the fundraising plan formulation department f4 calculates the probability distribution of the cash balance by date in the future by adding and subtracting the incoming and outgoing amounts indicated in the fundraising plan proposal from the cash balance at each time point indicated in the cash flow prediction information o2. In the case of Equation 5-7 above, the fundraising plan formulation department f4 substitutes the incoming amount in the fundraising plan proposal into the value of the item "Other planned incoming amount (t) such as fundraising", for example.

[0122] Furthermore, the fundraising plan formulation department f4 calculates the business evaluation score using the calculated cash balance (cash balance) as the input value through the same process as step s102-4 (for example, Equation 8-10) (step s106-4).

[0123] Then, the fundraising plan formulation department f4 checks whether the value of the business evaluation score calculated in step s106-4 is within the financing tolerance range of the financial product selected in step s106-1 by referring to the tolerance range i53 of the financial product information i5 (step s106-5).

[0124] If the value of the business evaluation score is within the financing tolerance range of the financial product (step s106-4: Yes), the fundraising plan formulation department f4 executes the process of step s106-6, and if the value of the business evaluation score is not within the financing tolerance range of the financial product (step s106-4: No), the fundraising plan formulation department f4 executes the process of step s106-7.

[0125] In step s106-6, the fundraising plan formulation department f4 stores the fundraising information and the value of the business evaluation score at that time. After that, step s106-9 is performed.

[0126] In step S106-7, the financing plan formulation department F4 changes the financing information at that time. For example, the financing plan formulation department F4 changes one or both of the deposit date and the loan amount. After that, the process of step S106-4 is repeated.

[0127] As described above, the financing plan formulation department F4 calculates the user's future fund balance (deposit balance) and business evaluation score when funds are lent to the user in each financing plan proposal (for example, date and amount) that can be formulated as details of financial products.

[0128] In step S106-9, the financing plan formulation department F4 checks whether the processes of steps S106-2 to S106-8 have been performed for all financial products in the financial product information I5. If the above processes have been performed for all financial products in the financial product information I5, the financing plan formulation department F4 performs the process of step S106-10. If there are financial products in the financial product information I5 for which the above processes have not been performed, the financing plan formulation department F4 repeats the processes after step S106-1 to select that financial product.

[0129] In step S106-10, the financing plan formulation department F4 outputs the information on each financing set in the previous processes and the value of the business evaluation score for this to the financing plan proposal information O4. Thus, the financing plan proposal formulation process S106 ends.

[0130] (Financing plan proposal information O4) FIG. 19 is a diagram showing an example of the output financing plan proposal information O4. The financing plan proposal information O4 includes the code O41 of the financial product targeted by the financing plan, the financing plan O42 (the deposit date O421 and the deposit amount O422 for purchasing the financial product) for raising funds by the financing plan, and the predicted result O43 of the result of raising funds by the financing plan (each data of the corresponding fund flow prediction information code O431, business evaluation score (default rate O432, sales increase rate O433, etc.)).

[0131] Through the above fundraising plan formulation process s106, the financial business support device 1 can formulate a fundraising plan such that the business evaluation score is within the financing allowable range of the financial product.

[0132] In this embodiment, a fundraising plan (combination of date and amount) within the financing allowable range of the financial product is searched by sequentially changing each value and performing calculations. However, other methods may be adopted for searching the fundraising plan. For example, a fundraising plan such that the business evaluation score after fundraising by the fundraising plan is Pareto optimal, or a fundraising plan such that the weighted sum of each value of the business evaluation score is the best, may be obtained by a mathematical optimization method such as a mixed integer programming method, or by an exhaustive search of all combinations of values that the date and amount can take.

[0133] Next, the screens displayed on each information processing device of the financial business support system 100 will be described.

[0134] (Recommended Fundraising Plan Display Screen) FIG. 20 is a diagram showing an example of a recommended fundraising plan display screen displayed on the user terminal 8 in step s108.

[0135] The recommended fundraising plan display screen d30 includes a display column d31 for the code of each financial product, a fund flow prediction result display column d32 that displays the fundraising plan (fundraising date d321, repayment date d322, etc.) by the financial product together with the predicted value of the deposit balance, a business evaluation score display column d33 that displays the business evaluation score achieved by the fundraising of the fundraising plan, and an application candidate button d34 selected by the user when the fundraising based on the fundraising plan is to be a candidate for application to a financial institution.

[0136] Note that in the fund flow prediction result display column d32 and the business evaluation score display column d33, the deposit balance and the business evaluation score when no fundraising is performed may be respectively displayed. Also, in the fund flow prediction result display column d32 and the business evaluation score display column d33, the corresponding industry average value or the value of a competing company may be respectively displayed.

[0137] Also, when a plurality of financing plan proposals are displayed on the recommended financing plan display screen d30, an interface may be provided on the recommended financing plan display screen d30 to perform sorting (determination of display order) based on the values of predetermined items (for example, the value of the business evaluation score, annual interest rate, amount of commission, or the name of the financial institution or investment institution that provides the financial product), and display it on the recommended financing plan display screen d30.

[0138] The recommended financing plan display screen d30 includes an application column d35 that is selected when the user applies for the financing of each application candidate set in the application candidate column d34. When the application column d35 is selected, the output generation unit f5 transmits predetermined application information including the financing plan proposal information o4 related to the financing of each application candidate set in the application candidate column d34 to the financial institution server 9 or the investment institution server 10.

[0139] (Review Screen) FIG. 21 is a diagram showing an example of a review screen d40 displayed on the financial institution server 9 or the investment institution server 10 in step s110. The review screen d40 includes a pre-review result display column d411 in which it is displayed whether (or to what extent) the business evaluation score related to each application candidate is within the financing allowable range, a code display column d412 in which the code of the financial product related to each application candidate is displayed, a fund flow prediction result display column d413 in which the financing plan proposal (financing date d4131, repayment date d4132, etc.) by the financial product related to each application candidate is displayed together with the predicted value of the deposit balance, and a business evaluation score display column d414 in which the business evaluation score achieved by the financing based on each financing plan proposal is displayed. The application content display column d41. Note that the content of the financing allowable range may be displayed in the pre-review result display column d411.

[0140] In addition, in the cash flow prediction result display column d413 and the business evaluation score display column d414, the deposit balance and the business evaluation score in the case of not raising funds may be displayed respectively. Further, in the cash flow prediction result display column d413 and the business evaluation score display column d414, the corresponding industry average value or the value of a competing company may be displayed respectively.

[0141] Also, when a plurality of financing plan proposals are displayed in the application content display column d41, an interface d53 that can sort based on the value of the business evaluation score, the profit of a financial institution or an investment institution (for example, the value obtained by subtracting the financing amount from the planned repayment amount from the company), or the value obtained by subtracting the investment amount from the planned dividend amount from the company may be provided on the review screen d40.

[0142] Furthermore, the review screen d40 has an information display button d42 selected when displaying the financial information, income and expenditure history, or credit information of the user (applying company), a response button d43 selected when transmitting the review result information to the user terminal 8, and an interview setting button d44 selected when setting the interview date and time with the user.

[0143] When the response column d43 is selected, the financial institution server 9 transmits information on the review result including the approval or disapproval of financing, financing conditions, and proposals for amendments to the application content based on the content displayed in the application content display column d41 to the user terminal 8.

[0144] (Review Result Display Screen) FIG. 22 is a diagram showing an example of a review result display screen d50 displayed on the user terminal 8. The review result display screen d50 includes a result display column d51 having a display column d511 for the code of the financial product related to the financing based on each financing plan proposal, a financing plan proposal display column d512 in which the content of each financing plan proposal (for example, the deposit date and the financing amount) is displayed, a review result display column d513 in which the content of the review result from the financial institution (information indicating whether it is judged within the financing allowable range, that is, whether financing is possible, and comments from the person in charge of the financial institution) is displayed, and a contract candidate setting column d514 selected by the user when each financial product is a contract target candidate.

[0145] In addition, when a plurality of financing plan proposals are displayed in the result display column d51, an interface may be provided on the review result display screen d50 that enables sorting based on the value of the business evaluation score, the annual interest rate, the amount of the fee, or the name of the financial institution or investment institution that provides the financial product.

[0146] Further, the review result display screen d50 is provided with a contract start button d52 that is selected when the user enters into a purchase contract for a financial product. When the contract start column d52 is selected, the user terminal 8 transmits the contract application information of the contract target candidate set in the contract candidate setting column d514 to the financial institution server 9.

[0147] As described above, the financial business support device 1 of the present embodiment takes the internal order information with undetermined order reception of the user as input, and based on the input internal order information, uses a confirmed order prediction model or the like to predict the probability distribution of the number of confirmed orders by future date, and outputs information (order amount prediction information o1) indicating the predicted result (order reception and cash flow prediction process s102). Then, the financial business support device 1 predicts the balance (deposit balance) of the user's funds at a predetermined future point in time based on the output order amount prediction information o1, formulates a financing plan proposal for the user's funds by the financial product based on the financial product information i5, and based on each formulated financing plan proposal and the predicted deposit balance, calculates the index values (business evaluation scores) achieved by the financing of funds by each financing plan proposal respectively, and identifies the financing plan proposals that meet the financing allowable range of the financial product information i5 among the calculated index values (financing plan proposal formulation process s106). Then, the financial business support device 1 outputs information indicating the predicted balance. In addition, the financial business support device 1 outputs information indicating the identified financing plan proposal.

[0148] That is, the financial business support device 1 of the present embodiment predicts the future order status (number of orders, order amount) of unconfirmed internal orders using a confirmed order prediction model or the like, and predicts the future balance of the user's funds. Thus, even if there is no periodicity or the like in the fluctuation of the balance of funds, the future balance of funds can be accurately predicted. Then, the financial business support device 1 formulates each financing plan using financial products, and identifies a financing plan such that the business evaluation score satisfies the financing tolerance range of the financial product. Thereby, it is possible to finance the user and the financier (such as a financial institution) in an optimal form.

[0149] As described above, according to the financial business support device 1 of the present embodiment, it is possible to accurately predict the future balance of funds of the fund borrower, and support financing funds to both the fund financier and the borrower under favorable conditions (conditions such as default risk and interest rate). Thereby, for example, a financial institution or the like can expand the financing opportunities for enterprises.

[0150] Further, the financial business support device 1 of the present embodiment calculates the total value of each index value (total value with weighting according to a plurality of respective indexes. Note that each index value is the user's default rate, sales growth rate, value indicating how many months of the user's working capital the cash balance corresponds to, or greenhouse gas emissions amount) achieved by financing with the financing plan, and identifies a financing plan that satisfies the conditions of the calculated total value among the calculated total values.

[0151] By using, as the business evaluation score, the total value obtained by weighting and synthesizing a plurality of different types of index values in this way, it is possible to evaluate the user from various aspects and provide financing such as financing with appropriate financial products.

[0152] Further, the financial business support device 1 of the present embodiment calculates a business evaluation score based on the financing plan, the average value or the minimum value of the deposit balance, and the degree to which the deposit balance contributes to the continuation of the user's business (see Equation 9 etc.).

[0153] As a result, an appropriate business evaluation score corresponding to the user's financial risk or the state of fund management can be calculated.

[0154] In addition, the financial business support apparatus 1 of the present embodiment calculates a business evaluation score achieved by the financing of funds in a funding plan that satisfies the financing tolerance range, and a business evaluation score achieved when there is no financing of funds in the funding plan, respectively, and displays each calculated index value on the screens of the user terminal 8 and the financial institution server 9 or the investment institution server 10 (recommended funding plan display screen d30, review screen d40).

[0155] As a result, the effect of financing from financial institutions and the like can be confirmed.

[0156] In addition, the financial business support apparatus 1 of the present embodiment displays the average value of the business evaluation scores of the user's peer companies, the business evaluation scores of other business operators competing with the user, and the financing tolerance range on the screen of the financial institution server 9 or the investment institution server 10 (review screen d40).

[0157] As a result, financial institutions and the like can accurately determine whether or not to finance the user.

[0158] In addition, the financial business support apparatus 1 of the present embodiment calculates a business evaluation score of the user at a predetermined future time based on the predicted deposit balance of the user, determines whether or not the calculated business evaluation score satisfies the financing tolerance range, and executes the funding plan proposal creation process s106 when the calculated business evaluation score does not satisfy the financing tolerance range.

[0159] As a result, since a funding plan is created only when it is considered that the user needs to raise funds, the burden of the user's funding business can be reduced.

[0160] In addition, the financial business support device 1 of the present embodiment specifies a financing plan that satisfies the financing allowable range of the total value among the total values of each business evaluation score (business evaluation score with weighting according to indicators) achieved by financing funds according to the financing plan.

[0161] Thereby, a financing plan that reflects the business evaluation scores from multiple perspectives can be specified.

[0162] In addition, the financial business support device 1 of the present embodiment predicts the range (probability distribution) of the probability that the project for which the user has received an indication will be awarded a contract in the future for each future point in time.

[0163] In this way, by calculating the probability of winning a contract with the probability distribution at each future point in time, a predicted value regarding the contract-awarded project that reflects the probability that varies according to the time series can be calculated. Thereby, for example, regarding the fluctuation of the deposit balance, even when there is no continuation or periodicity of the past trend, the future balance of funds can be predicted. And an appropriate financing plan (loan amount, interest rate, etc.) such that the business evaluation score falls within the financing allowable range can be specified, and the financing opportunities for enterprises can be expanded.

[0164] In addition, when the financial business support device 1 of the present embodiment transmits information indicating a financing plan to the user terminal 8 and receives information indicating the desire for financing according to the financing plan from the user terminal 8, it transmits the information indicating the financing plan to the financial institution server 9 (investment institution server 10), receives information indicating the approval or disapproval of financing corresponding to the financing plan from the financial institution server 9 (investment institution server 10), and transmits the received information indicating the approval or disapproval of financing to the user terminal 8.

[0165] In this way, by the financial business support device 1 mediating the communication regarding the financing of funds between the borrower (user) and the lender (financial institution, investment institution), smooth financial business can be supported.

[0166] In addition, when the financial business support device 1 of the present embodiment identifies a plurality of financing plan proposals, it displays these plurality of financing plan proposals on the screen of the user terminal 8 in a predetermined order based on the value of the business score or the value of a predetermined item constituting the financing plan proposal.

[0167] Thereby, the user can easily identify an appropriate financing plan proposal.

[0168] As described above, the present invention is not limited to the above-described embodiments, and includes various modifications and equivalent configurations within the scope of the appended claims. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and the present invention is not necessarily limited to those having all the configurations described. Also, additions, deletions, or replacements may be made to a part of the configuration of the embodiments.

[0169] For example, the borrowers of funds are not limited to companies, and may be individual consumers considering, for example, housing loans. Also, the lenders are not limited to financial institutions such as banks or credit unions, or investment institutions, and may be individual investors. Also, the object of financing may be not only cash but also funds in other forms such as virtual currency.

[0170] Also, each model (confirmed order prediction model, cash flow prediction model, business evaluation model) described in the present embodiment is an example, and may be realized by other formulas or algorithms.

[0171] Also, in the present embodiment, the cases with uncertain confirmed order numbers are assumed to be the cases that have received internal indication, but cases in other states (for example, cases with a provisional contract) may also be acceptable.

[0172] Also, a part of the hardware provided in each device of the present embodiment may be provided in other devices.

[0173] Also, each program of each device may be provided in another device, a certain program may be composed of a plurality of programs, or a plurality of programs may be integrated into one program.

[0174] Also, each of the above-described configurations, functions, processing units, processing means, etc. may be realized in hardware by designing a part or all of them, for example, by means of an integrated circuit, or may be realized in software by a processor interpreting and executing a program for realizing each function. Information such as programs, tables, files, etc. for realizing each function can be stored in a storage device such as a memory, a hard disk, an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card, or a DVD.

[0175] Also, in each drawing, control lines and information lines show those considered necessary for explanation, and do not necessarily show all the control lines and information lines necessary for implementation. In practice, it may be considered that almost all components are interconnected.

Explanation of Reference Numerals

[0176] 1 Financial Business Support Device, 9 Financial Institution Server, f1 Order Receiving Prediction Unit, f2 Cash Flow Prediction Unit, f3 Business Evaluation Unit, f4 Funding Plan Formulation Unit, f5 Output Generation Unit

Claims

1. A storage device that stores financial product information, which is design information of a financial product for financing a business operator, and conditions regarding an index value representing the business operator's business capabilities necessary for financing the business operator with the financial product, and A control device that, using internal order information with undetermined orders in the business operator as input, predicts the probability distribution of the future confirmed order quantity by a predetermined algorithm based on the input internal order information, A fund flow prediction process that predicts the balance of funds at a predetermined future time of the business operator based on the predicted result, And an output generation process that outputs information indicating the predicted balance of funds to an output device. A financial business support device comprising the above.

2. The control device Based on the financial product information, formulates one or more fund-raising plan proposals for financing the business operator with the financial product, and based on each formulated fund-raising plan proposal and the predicted balance of funds, calculates the index values achieved by financing with each fund-raising plan proposal respectively, and further executes a fund-raising plan proposal formulation process for identifying the fund-raising plan proposals that satisfy the conditions among the calculated index values, In the output generation process, outputs information indicating the identified fund-raising plan proposal to an output device. The financial business support device according to Claim 1.

3. The storage device stores, as conditions regarding the index value, a comprehensive value condition in which at least one of the default rate, sales growth rate, degree to which the cash balance contributes to the continuation of the business operator's business, and greenhouse gas emissions of the business operator is weighted according to each index, The control device In the fund-raising plan proposal formulation process, calculates the comprehensive value of each index value achieved by financing with the fund-raising plan proposal respectively, and identifies the fund-raising plan proposals that satisfy the comprehensive value condition among the calculated comprehensive values. The financial business support device according to Claim 2.

4. The control device is In the fundraising plan formulation process, based on the formulated fundraising plan, the average value or minimum value of the predicted remaining funds, and the degree to which the predicted remaining funds contribute to the business continuity of the operator, calculate the index value. The financial business support device according to claim 2.

5. The control device is Calculate the index value achieved by the financing of the funds in the fundraising plan that satisfies the conditions and the index value achieved when there is no financing of the funds in the fundraising plan, and output each calculated index value to the output device. The financial business support device according to claim 2.

6. The control device is Output to the output device at least any one of the average value of the index values of other operators in the same industry as the operator, the index values of operators competing with the operator, and the conditions regarding the index values. The financial business support device according to claim 2.

7. The control device is Calculate an index value representing the business ability of the operator at the future predetermined time point based on the predicted remaining funds, determine whether the calculated index value satisfies the conditions, and execute the fundraising plan formulation process when the calculated index value does not satisfy the conditions. The financial business support device according to claim 2.

8. The storage device stores, as conditions regarding the index value, conditions for the total value of two or more respective indices with weighting according to each index. The control device is In the fundraising plan formulation process, calculate the total value of each index value achieved by the financing of the funds by the fundraising plan, and identify the fundraising plan that satisfies the conditions of the total value with Pareto optimality among the calculated total values. The financial business support device according to claim 2.

9. The control device In the order receiving prediction process, predicts the range of the probability of the number of orders to be received in the future for each case including at least the undetermined cases, for each future time point. The financial business support device according to claim 2.

10. The control device Transmits the information indicating the identified financing plan proposal to the first information processing device related to the business operator. When receiving information indicating a request for financing according to the identified financing plan proposal from the first information processing device, transmits the information indicating the identified financing plan proposal to the second information processing device related to the business operator capable of financing the business operator, receives information indicating the availability of financing of the funds corresponding to the identified financing plan proposal from the second information processing device, and transmits the received information indicating the availability of financing of the funds to the first information processing device. The financial business support device according to claim 2.

11. The control device When a plurality of financing plan proposals are identified, outputs each of the plurality of financing plan proposals to an output device in an order based on the index value or the values of predetermined items constituting the financing plan proposal. The financial business support device according to claim 2.

12. A financial business support method by an information processing device including a storage device that stores financial product information which is design information of a financial product for financing a business operator and conditions regarding an index value representing the business ability of the business operator necessary for financing the business operator with the financial product, and a control device, The control device An order receiving prediction process that uses the internal order receiving information with undetermined orders in the business operator as an input, and predicts the probability distribution of the future confirmed order number based on the input internal order receiving information by a predetermined algorithm, Based on the predicted results, a cash flow prediction process for predicting the balance of funds of the operator at a predetermined future point in time, and an output generation process for outputting information indicating the predicted balance of funds to an output device are executed. A financial business support method.

Images