Financial data evaluation system and financial data evaluation method

Abstract

A financial data evaluation system and a financial data evaluation method are provided that enable financial institutions to accurately determine whether financial settlement details have been manipulated in financial data. [Solution] The system is characterized by comprising a database construction means that collects anonymous financial data, which has been anonymized, from multiple financial institutions and constructs a database; same business operator determination means that compares the anonymous financial data contained in the database and determines whether the anonymous financial data relate to the same business operator; data group acquisition means that acquires a same business operator data group, which is a group of anonymous financial data relating to the same business operator, based on the determination by the same business operator determination means; evaluation data acquisition means that acquires evaluation data indicating an evaluation of the anonymous financial data based on the same business operator data group; and evaluation data provision means that provides some or all of the evaluation data to the financial institution that is the source of the anonymous financial data.

Description

[Technical Field]

[0001] The present invention relates to a financial data evaluation system and a financial data evaluation method for evaluating financial data provided by a business operator to a financial institution. [Background technology]

[0002] Unlisted small and medium-sized enterprises are not required to follow uniform accounting standards. For this reason, when submitting financial statements to financial institutions that provide loans, small and medium-sized enterprises, as debtors, sometimes intentionally prepare multiple financial statements that misrepresent their actual financial situation, and use different financial statements for each financial institution from which they receive loans. Similarly, when applicants for new loans submit financial statements to financial institutions, they often manipulate the financial statements in the same way. Such behavior significantly undermines the reliability of financial statements, preventing financial institutions from making appropriate loan decisions and resulting in disadvantages.

[0003] In the past, determining whether or not there was any "intentional manipulation of financial statements" (hereinafter referred to as "manipulation of financial statements") required the checks of checkers with many years of experience and specialized knowledge in banking operations. Furthermore, this check required a significant amount of time.

[0004] For example, Patent Document 1 discloses a technology for providing a financial analysis support system and method that can support financial analysis by checkers of financial statements and reduce the checking workload of the checkers. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-312580 Summary of the Invention [Problem to be solved by the invention]

[0006] Specifically, the technology disclosed in Patent Document 1 is a technology that, based on the financial data of a company whose financial statements are already known to have been manipulated, finds in advance the characteristics of the data that would be obtained if the financial statements had been manipulated, and, based on these characteristics, determines whether the financial data provided by the company has the characteristics of the data that would be obtained if the financial statements had been manipulated.

[0007] However, in order to collect sufficient financial data from a company that is already known to have manipulated its financial statements, a large amount of financial data must be collected and then checked by an inspector.

[0008] In terms of data collection, Patent Document 1 partially discloses the use of financial data obtained from other financial institutions, but due to confidentiality restrictions between companies and financial institutions, it is difficult to collect large amounts of financial data. Furthermore, even if a large amount of financial data is collected, the person checking it must perform a huge amount of work to check whether the collected financial data has been manipulated. Therefore, it is difficult to collect sufficient financial data from companies whose financial statements are already known to have been manipulated.

[0009] For this reason, the technique disclosed in Patent Document 1 has the problem that it is difficult for financial institutions to accurately determine whether the financial statements have been manipulated in the financial data provided by businesses.

[0010] The present invention has been devised in consideration of the above-mentioned problems, and its purpose is to provide a financial data evaluation system and a financial data evaluation method that enable financial institutions to accurately determine manipulation of financial statements in financial data. [Means for solving the problem]

[0011] The financial data evaluation system of the first invention is a financial data evaluation system that evaluates financial data provided by businesses to financial institutions, and is characterized by comprising: a database construction means that collects anonymous financial data, in which the financial data has been anonymized, from a plurality of financial institutions and constructs a database; a same business determination means that determines whether the anonymous financial data relate to the same business by comparing the anonymous financial data contained in the database; a data group acquisition means that acquires a same business data group, which is a group of anonymous financial data relating to the same business, based on the determination by the same business determination means; an evaluation data acquisition means that acquires evaluation data indicating an evaluation of the anonymous financial data based on the same business data group acquired by the data group acquisition means; and an evaluation data provision means that provides some or all of the evaluation data acquired by the evaluation data acquisition means to the financial institution that is the source of the anonymous financial data.

[0012] The financial data evaluation system according to the second invention is characterized in that, in the first invention, the anonymous financial data has a plurality of data items, and the evaluation data acquisition means acquires the evaluation data based on the distribution of data in one or more of the data items in the same business data group.

[0013] A financial data evaluation system according to a third aspect of the present invention is the system according to the second aspect of the present invention, characterized in that the evaluation data acquisition means acquires the evaluation data including a reliability indicating the authenticity of the anonymous financial data.

[0014] The financial data evaluation system of the fourth invention is characterized in that, in the third invention, the evaluation data acquisition means identifies, based on the evaluation data, cautionary data items in the anonymous financial data that are data items that lower the reliability, and the evaluation data providing means provides information regarding the cautionary data items and the degree to which the cautionary data items lower the reliability to the financial institution that is the source of the anonymous financial data.

[0015] The financial data evaluation method of the fifth invention is a financial data evaluation method for evaluating financial data provided by a business to a financial institution, and is characterized in that it comprises a database construction step of collecting anonymous financial data, in which the financial data has been anonymized, from a plurality of the financial institutions and constructing a database; a same business determination step of comparing the anonymous financial data contained in the database to determine whether the anonymous financial data relate to the same business; a data group acquisition step of acquiring a same business data group, which is a group of anonymous financial data relating to the same business, based on the determination made by the same business data determination step; an evaluation data acquisition step of acquiring evaluation data indicating an evaluation of the anonymous financial data based on the same business data group acquired by the data group acquisition step; and an evaluation data provision step of providing some or all of the evaluation data acquired by the evaluation data acquisition step to the financial institution that is the source of the anonymous financial data. [Effects of the Invention]

[0016] According to the first to fourth inventions, the database construction means collects anonymous financial data, which is financial data that has been anonymized, from multiple financial institutions and constructs a database. The evaluation data acquisition means acquires evaluation data indicating the evaluation of the anonymous financial data based on a group of data from the same business. The evaluation data provision means provides some or all of the evaluation data to the financial institution that is the source of the anonymous financial data. Therefore, the financial data evaluation system can collect a large amount of anonymous financial data and then provide evaluation data related to the anonymous financial data to financial institutions. This enables financial institutions to accurately determine any manipulation of financial statements in the financial data provided by businesses.

[0017] In particular, according to the second aspect of the present invention, the evaluation data acquisition means acquires evaluation data based on the distribution of data in one or more data items in the same business data group. Therefore, the financial data evaluation system can evaluate anonymous financial data based on the variability and bias of data in the same business data group and provide the evaluation data to financial institutions. This enables financial institutions to more accurately determine whether financial statements have been manipulated in the financial data submitted by businesses.

[0018] In particular, according to the third aspect of the present invention, the evaluation data acquisition means acquires evaluation data including a reliability indicating the authenticity of the anonymous financial data. Therefore, the financial data evaluation system can provide financial institutions with information that is useful for determining whether financial statements have been manipulated. This enables financial institutions to more accurately determine whether financial statements have been manipulated in the financial data submitted by businesses.

[0019] In particular, according to the fourth aspect of the present invention, the evaluation data acquisition means identifies, based on the evaluation data, caution data items that are data items that lower the reliability of the anonymous financial data, and the evaluation data provision means provides the financial institution that is the source of the anonymous financial data with information regarding the caution data items and the degree to which the caution data items lower the reliability. Therefore, the financial data evaluation system can provide the financial institution with information that is useful in determining whether the financial statements of the financial data have been manipulated. This enables the financial institution to more accurately determine whether the financial statements of the financial data submitted by the business have been manipulated.

[0020] According to the fifth aspect of the present invention, the database construction step collects anonymous financial data, which is financial data that has been anonymized, from multiple financial institutions and constructs a database. The evaluation data acquisition step acquires evaluation data indicating the evaluation of the anonymous financial data based on a group of data from the same business. The evaluation data provision step provides some or all of the evaluation data to the financial institution that provided the anonymous financial data. Therefore, the financial data evaluation method can collect a large amount of anonymous financial data and then provide evaluation data related to the anonymous financial data to financial institutions. This enables financial institutions to accurately determine whether financial statements have been manipulated in the financial data submitted by businesses. [Brief explanation of the drawings]

[0021] [Figure 1] FIG. 1 is a schematic diagram showing an example of the overall configuration of a financial data evaluation system to which the present invention is applied. [Figure 2] FIG. 2 is a schematic diagram showing an example of the hardware configuration of the financial data evaluation device according to the present invention. [Figure 3] FIG. 3 is a schematic diagram showing an example of the functional configuration of the financial data evaluation device according to the present invention. [Figure 4] FIG. 4 is a flowchart showing an example of steps of the financial data evaluation method according to the first embodiment. [Figure 5] FIG. 5 is a schematic diagram showing an example of a database made up of anonymous financial data. [Figure 6] FIG. 6(a) is a schematic diagram showing an example of a data table of anonymous financial data 5a contained in the database, FIG. 6(b) is a schematic diagram showing an example of a data table of anonymous financial data 5b contained in the database, and FIG. 6(c) is a schematic diagram showing an example of a data table of anonymous financial data 5c contained in the database. [Figure 7] FIG. 7 is a schematic diagram showing an example of a database classified by linked business operators. [Figure 8]Figure 8(a) is a schematic diagram showing an example of the distribution of data for a certain data item in a same-enterprise data group, and Figure 8(b) is a schematic diagram showing a modified example of the distribution of data for a certain data item in a same-enterprise data group. [Figure 9] FIG. 9 is a schematic diagram showing an example of a radar chart that the evaluation data providing unit provides to the financial institution. DETAILED DESCRIPTION OF THE INVENTION

[0022] Hereinafter, an embodiment of a financial data evaluation system 100 to which the present invention is applied will be described in detail with reference to the drawings.

[0023] Hereinafter, for example, when financial institutions are referred to collectively, they will be written as financial institution 3, and when financial institutions are to be distinguished from one another, they will be written as financial institution 3a, financial institution 3b, etc. The same applies to business operators 2, financial data 4, anonymous financial data 5, evaluation data 6, and same business operator data group 7.

[0024] <Financial Data Evaluation System 100> FIG. 1 is a schematic diagram showing an example of the overall configuration of a financial data evaluation system 100 to which the present invention is applied.

[0025] The financial data evaluation system 100 is a system that evaluates financial data 4 provided by a business operator 2 to a financial institution 3 .

[0026] As shown in FIG. 1, financial data evaluation system 100 includes financial data evaluation device 1. As shown in FIG. 1, in financial data evaluation system 100, business operator 2 provides financial data 4a to financial institution 3a and provides financial data 4b to financial institution 3b. Financial institution 3a anonymizes financial data 4a and provides anonymous financial data 5a to financial data evaluation device 1, and financial institution 3b anonymizes financial data 4b and provides anonymous financial data 5b to financial data evaluation device 1. In addition, financial data evaluation device 1 constructs database 8 using anonymous financial data 5 collected from financial institution 3, and, based on an analysis using same business operator data group 7 included in database 8, provides evaluation data 6a indicating an evaluation of anonymous financial data 5a to financial institution 3a and provides evaluation data 6b indicating an evaluation of anonymous financial data 5b to financial institution 3b.

[0027] Here, the financial data 4 is data relating to the financial status of the business operator 2, for example, data relating to financial statements. The business operator 2 needs to provide the financial data 4 to, for example, a financial institution 3 from which it receives a loan.

[0028] Additionally, the anonymous financial data 5 is data that has been anonymized from the financial data 4, making it impossible to identify the business operator 2. Although it is not possible to identify the business operator 2 from the anonymous financial data 5, the anonymous financial data 5 is data that is linked to a specific business operator 2.

[0029] Furthermore, the evaluation data 6 is data relating to an evaluation of the anonymous financial data 5. For example, the evaluation data 6 is data relating to an evaluation of the credibility of the financial data 4, or an evaluation of whether the contents of the financial data 4 are consistent. The evaluation data 6 is data linked to the anonymous financial data 5. Furthermore, although it is not possible to identify the business operator 2 from the evaluation data 6, the evaluation data 6 is data linked to a specific business operator 2.

[0030] Furthermore, database 8 is a collection of anonymous financial data 5. In database 8, the anonymous financial data 5 constitutes a plurality of same business operator data groups 7. Here, the same business operator data groups 7 are collections of anonymous financial data 5 relating to the same business operator. Furthermore, the same business operator data groups 7 are subsets of database 8.

[0031] The data format of the financial data 4, anonymous financial data 5, and evaluation data 6 is, for example, a data table. Furthermore, these data formats may be set arbitrarily other than data tables. Furthermore, these data may include image files, etc. Furthermore, the provision and acquisition of various data by the financial data evaluation device 1, the business entity 2, and the financial institution 3 may be performed using known communication technologies. Furthermore, the anonymous financial data 5 and evaluation data 6 may be partially restricted or processed so that various confidentiality regulations are observed when transmitting and receiving the data.

[0032] Each element in FIG. 1 will be explained below.

[0033] <Financial Data Evaluation Device 1> The financial data evaluation device 1 is a device that evaluates anonymous financial data 5. The financial data evaluation device 1 may be a device owned by a party other than the business operator 2 and the financial institution 3 in FIG. 1. For example, the financial data evaluation device 1 may be owned by a data management company or the like.

[0034] FIG. 2 is a schematic diagram showing an example of the hardware configuration of the financial data evaluation device 1 according to the present invention.

[0035] The financial data evaluation device 1 includes, for example, a housing 111, a CPU 101, a ROM 102, a RAM 103, a storage device 104, and I / Fs 105 to 107. The CPU 101, the ROM 102, the RAM 103, the storage device 104, and the I / Fs 105 to 107 are connected by an internal bus 110.

[0036] The CPU 101 controls the entire financial data evaluation device 1. The ROM 102 stores operation code for the CPU 101. The RAM 103 is a work area used when the CPU 101 is operating. The storage device 104 stores various data. For example, the storage device 104 stores anonymous financial data 5 collected from financial institutions 3, a database 8 constructed from the anonymous financial data 5, and the like. The storage device 104 may also store evaluation data 6. The storage device 104 may be, for example, a hard disk drive (HDD), a solid state drive (SSD), an SD card, a miniSD card, or other data storage device. Note that the financial data evaluation device 1 may also include a graphics processing unit (GPU), not shown.

[0037] I / F 105 is an interface for transmitting and receiving data to and from a communication device owned by financial institution 3. I / F 106 is an interface for transmitting and receiving data to and from input device 108. A keyboard, for example, is used as input device 108, and a user using financial data evaluation device 1 inputs various data or control commands for financial data evaluation device 1 via input device 108. I / F 107 is an interface for transmitting and receiving various data to and from display device 109. Display device 109 outputs various data stored in storage device 104, or the processing status of financial data evaluation device 1, etc. A display is used as display device 109, and may be, for example, a touch panel type.

[0038] <Business 2> The business entity 2 is a corporation such as a company or a sole proprietor. For example, the business entity 2 is a debtor who has received a loan from the financial institution 3, or a company that wishes to obtain a new loan from the financial institution 3. The business entity 2 provides financial data 4 to the financial institution 3 that is the source of the loan.

[0039] There may be multiple business operators 2. In this case, each of the multiple business operators 2 may be an independent company, etc. Each business operator 2 submits financial data 4 to one or more financial institutions 3. Furthermore, the business operator 2 may provide financial data 4 only to some financial institutions 3 and not provide financial data 4 to other financial institutions 3. If the business operator 2 has manipulated the details of its financial settlement in the financial data 4 or if there are deficiencies in the financial data 4, the business operator 2 will provide different financial data 4 to each financial institution 3.

[0040] <Financial institution 3> The financial institution 3 is an institution, such as a bank, that provides financing to the business operator 2. The financial institution 3 may also be a trading company or leasing company that provides financing to the business operator 2.

[0041] The financial institution 3 acquires financial data 4 from the business operator 2. The financial institution 3 also provides the financial data evaluation device 1 with anonymous financial data 5, which is the financial data 4 anonymized. The reason why the financial institution 3 provides the financial data evaluation device 1 with anonymized data is because it needs to fulfill the confidentiality obligations that arise between the business operator 2 and the financial institution 3.

[0042] 1 shows two financial institutions 3, but the number of financial institutions 3 may be any number. Furthermore, the multiple financial institutions 3 may each be independent banks, etc. Each financial institution 3 may obtain financial data 4 from multiple businesses 2.

[0043] FIG. 3 is a schematic diagram showing an example of the functional configuration of the financial data evaluation device 1 according to the present invention.

[0044] As shown in Fig. 3, the financial data evaluation device 1 includes functional units such as a database construction unit 11, a same business entity determination unit 12, a data group acquisition unit 13, an evaluation data acquisition unit 14, and an evaluation data provision unit 15. Each function shown in Fig. 3 is realized, for example, by a CPU 101 using a RAM 103 as a working area to execute a program stored in a storage device 104 or the like. Each functional unit in Fig. 3 will be described below.

[0045] <Database Construction Department 11> The database construction unit 11 collects anonymous financial data 5 from multiple financial institutions 3 and constructs a database 8. Here, the database 8 is a collection of anonymous financial data 5 and is stored in the storage device 104. For example, the database construction unit 11 collects the anonymous financial data 5 by receiving data from a communication device owned by each financial institution 3 via the I / F 105.

[0046] <Same business operator determination department 12> The same business operator determination unit 12 compares the anonymous financial data 5 contained in the database 8 to determine whether the anonymous financial data 5 relate to the same business operator 2. The timing at which the same business operator determination unit 12 compares the anonymous financial data 5 can be set arbitrarily.

[0047] <Data group acquisition unit 13> The data group acquisition unit 13 acquires the same business operator data group 7 based on the determination by the same business operator determination unit 12. Here, the same business operator data group 7 is a collection of anonymous financial data 5 relating to the same business operator.

[0048] <Evaluation data acquisition unit 14> The evaluation data acquisition unit 14 acquires evaluation data 6 indicating an evaluation of the anonymous financial data 5 based on the same business operator data group 7. The timing at which the evaluation data acquisition unit 14 acquires the evaluation data 6 may be after the same business operator data group 7 is acquired by the data group acquisition unit 13.

[0049] <Evaluation Data Provider 15> The evaluation data providing unit 15 provides part or all of the evaluation data 6 to the financial institution 3 in accordance with the evaluation data 6. The evaluation data providing unit 15 provides the evaluation data 6 to the financial institution 3, for example, by transmitting the evaluation data 6 to a communication device held by the financial institution 3 via the I / F 105.

[0050] <First embodiment: financial data evaluation method> Next, an example of the steps of a financial data evaluation method to which the present invention is applied will be described as a first embodiment.

[0051] Figure 4 is a flowchart showing an example of the steps of the financial data evaluation method in the first embodiment. The financial data evaluation method includes a database construction step S11, a same business entity determination step S12, a data group acquisition step S13, an evaluation data acquisition step S14, and an evaluation data provision step S15. Each step in Figure 4 will be described below.

[0052] <Database construction step S11> In the database construction step S11, the database construction unit 11 collects anonymous financial data 5, which is financial data 4 anonymized, from a plurality of financial institutions 3, and constructs a database 8.

[0053] For example, financial institution 3 acquires financial data 4 in advance when considering financing for business operator 2. Here, financial institution 3 anonymizes financial data 4 to generate anonymous financial data 5 so that business operator 2 cannot be identified from the anonymous financial data 5.

[0054] Here, the anonymization performed by the financial institution 3 on the financial data 4 involves, for example, deleting information regarding the company name, company code, head office address, and telephone number from the financial data 4. The financial institution 3 may also process the data by adding or subtracting a small value to the numerical data in the financial data 4, so that the business operator 2 cannot be identified.

[0055] The database construction unit 11 collects anonymous financial data 5 from a plurality of financial institutions 3. The financial data evaluation device 1 stores the collected anonymous financial data 5 in the storage device 104 and constructs a database 8. Here, the database 8 is a collection of anonymous financial data 5. The database construction unit 11 may also construct the database 8 by storing the anonymous financial data 5 collected from a plurality of financial institutions 3 on an external server or the like.

[0056] Fig. 5 is a schematic diagram showing an example of a database 8 composed of anonymous financial data. The database 8 in Fig. 5 is composed of anonymous financial data 5a, anonymous financial data 5b, anonymous financial data 5c, anonymous financial data 5d, anonymous financial data 5e, etc. The database 8 may include anonymous financial data 5 relating to multiple businesses 2.

[0057] Furthermore, the anonymous financial data 5 constituting the database 8 includes multiple pieces of anonymous financial data 5 relating to the same business operator 2. This is because, as shown in FIG. 1, when a specific business operator 2 provides financial data 4 to multiple financial institutions 3, the database construction unit 11 acquires the anonymous financial data 5 separately from each financial institution 3. Here, if a specific business operator 2 manipulates its financial statements and provides different financial data 4 to each financial institution 3, the multiple pieces of anonymous financial data 5 in the database 8 will have differences and variations in the numerical data, etc., even if they are anonymous financial data 5 linked to the same business operator.

[0058] Here, the anonymous financial data 5 may be composed of business-related data, finance-related data, and reorganization-related data, etc. Here, the business-related data is information about the business 2, such as the business 2's industry, the prefecture where the business 2 is located, and the date of establishment. Because the business-related data is basic information about the business 2, it is unlikely that false information will be provided. The finance-related data is information about the business 2's financial situation, such as the amount of assets and liabilities of the business 2. The finance-related data is information that is reviewed when applying for a loan and contains a lot of numerical data. Therefore, if the business 2 manipulates the financial statements in the financial data 4, there is a high possibility that the financial-related data will contain data that differs from the original data. Furthermore, the reorganization-related data is data used for the purpose of smooth operation of the database 8, such as a code linked to the financial institution 3 or a reference number assigned to each data by the administrator of the database 8.

[0059] Here, the anonymous financial data 5 may have multiple data items. Each data item may be a data item related to business-related data, finance-related data, and reorganization-related data. For example, data items related to business-related data may be "industry" and "prefecture," data items related to finance-related data may be "asset amount" and "liability amount," and data items related to reorganization-related data may be "reorganization code" and "financial institution code."

[0060] FIG. 6(a) is a schematic diagram showing an example of a data table of anonymous financial data 5a included in database 8. In FIG. 6(a), sorting item 1 and sorting item 2 are sorting-related data, such as "sorting code" and "financial institution code." In FIG. 6(a), data items 1 to 3 are business-related data, such as "date of establishment," "industry," and "prefecture." In FIG. 6(a), data item 4 is finance-related data, such as "asset amount." Although FIG. 6(a) shows six data items, the anonymous financial data 5 may include more data items. For example, there may be 20 data items related to business-related data and 100 data items related to finance-related data.

[0061] Figure 6(b) is a schematic diagram showing an example of a data table of anonymous financial data 5b contained in database 8, and Figure 6(c) is a schematic diagram showing an example of a data table of anonymous financial data 5c contained in database 8. The explanation of each data item in Figures 6(b) and 6(c) is the same as in Figure 6(a).

[0062] A person who owns the financial data evaluation device 1 can refer to the anonymous financial data 5 by referring to the database 8. Furthermore, by using the database 8, a person who owns the financial data evaluation device 1 can sort the anonymous financial data 5 based on data items, set search conditions, and search for anonymous financial data 5 that meets the conditions, etc.

[0063] <Same business operator determination step S12> In the same business operator determination step S12, the same business operator determination unit 12 compares the anonymous financial data 5 contained in the database 8 to determine whether the anonymous financial data 5 relate to the same business operator 2. In the same business operator determination step S12, the anonymous financial data 5 constituting the database 8 is classified by the business operator 2 to which it is linked.

[0064] For example, the same business operator determination unit 12 selects two sets of anonymous financial data 5 from the database 8 and compares them to make a determination. The same business operator determination unit 12 may perform this process for all combinations of anonymous financial data 5 that make up the database 8.

[0065] Here, the same business operator determination unit 12 may use the business operator-related data in the anonymous financial data 5 to determine whether the two sets of anonymous financial data 5 relate to the same business operator. For example, the business operator-related data of both sets of data to be compared, that is, information such as the industry of the business operator 2 linked to the anonymous financial data 5 and the prefecture where the business operator 2 is located, is compared, and if this information matches, the same business operator determination unit 12 determines that the two sets of anonymous financial data 5 relate to the same business operator 2. Here, the same business operator determination unit 12 may refer to more data items in the business operator-related data. Furthermore, data other than the business operator-related data may also be referenced as appropriate in this determination.

[0066] For example, consider a case where anonymous financial data 5a in FIG. 6(a) is compared with anonymous financial data 5b in FIG. 6(b). For the sake of explanation, it is assumed that the business-related data included in anonymous financial data 5 consists of three items: data item 1 to data item 3. As shown in FIGS. 6(a) and 6(b), the business-related data in anonymous financial data 5a and anonymous financial data 5b are as follows: data item 1 is "YYYYMM," data item 2 is "AAA," and data item 3 is "BBB." Since the business-related data in both sets corresponds, same business determination unit 12 determines that business entity 2 linked to anonymous financial data 5a is the same as business entity 2 linked to anonymous financial data 5b.

[0067] Also, for example, consider a case where anonymous financial data 5a in FIG. 6(a) is compared with anonymous financial data 5c in FIG. 6(c). As shown in FIG. 6(c), the business-related data of anonymous financial data 5c has data item 1 as "YYYYMM," data item 2 as "DDD," and data item 3 as "EEE." While anonymous financial data 5a and anonymous financial data 5c correspond in data item 1, they have different data in data items 2 and 3. In this case, same business entity determination unit 12 determines that business entity 2 linked to anonymous financial data 5a is not the same as business entity 2 linked to anonymous financial data 5c.

[0068] Although the example given above shows a case where the business-related data included in the anonymous financial data 5 includes three items, data item 1 to data item 3, more data items may be referenced in determining whether the data are the same business. Furthermore, the same business determination unit 12 may set specific data items and always determine that the data are not identical if the data do not correspond for these data items. Furthermore, the same business determination unit 12 may set specific data items and determine that the data are the same business 2 even if the data do not correspond for these data items. In this way, the same business determination unit 12 references multiple data items, checks the correspondence between the data, and then comprehensively determines whether the anonymous financial data 5 are data related to the same business 2. In this way, the anonymous financial data 5 constituting the database 8 is classified by the associated business 2.

[0069] <Data group acquisition step S13> In the data group acquisition step S13, the data group acquisition unit 13 acquires a same business operator data group 7, which is a group of anonymous financial data 5 related to the same business operator 2, based on the determination by the same business operator determination unit 12.

[0070] Here, the same business operator data group 7 is a collection of anonymous financial data 5 linked to the same business operator 2. Here, the anonymous financial data 5 included in the same business operator data group 7 is linked to the same business operator 2, but is data provided by different financial institutions 3.

[0071] The data group acquisition unit 13 acquires the same business operator data group 7 based on the anonymous financial data 5 classified for each linked business operator 2 in the same business operator determination step S12. Furthermore, since the database 8 includes anonymous financial data 5 relating to multiple business operators 2, the data group acquisition unit 13 acquires multiple same business operator data groups 7 for each business operator 2.

[0072] FIG. 7 is a schematic diagram showing an example of a database classified by linked business operator 2. In FIG. 7, anonymous financial data 5a, anonymous financial data 5b, and anonymous financial data 5e are anonymous financial data 5 linked to the same business operator 2 and constitute a same business operator data group 7a. Additionally, anonymous financial data 5c and anonymous financial data 5d are also anonymous financial data 5 linked to the same business operator 2 and constitute a same business operator data group 7c. Here, the business operator 2 linked to the same business operator data group 7a is different from the business operator 2 linked to the same business operator data group 7c.

[0073] Here, the data group acquiring unit 13 acquires the same business operator data group 7, but since the anonymous financial data 5 has been anonymized, the data group acquiring unit 13 cannot identify the business operator 2.

[0074] <Evaluation data acquisition step S14> In the evaluation data acquisition step S14, the evaluation data acquisition unit 14 acquires evaluation data 6 indicating the evaluation of the anonymous financial data 5 based on the same business entity data group 7.

[0075] For example, the evaluation data acquisition unit 14 refers to data items related to financial-related data for anonymous financial data 5 included in the same business operator data group 7. If the business operator 2 has properly provided financial data 4 to the financial institution 3 without manipulating the financial statements, the data items related to financial-related data will correspond to other anonymous financial data 5 included in the same business operator data group 7. Furthermore, differences in numerical data, etc. may occur due to factors such as the timing of providing financial data 4 to each financial institution 3 and the processing performed during anonymization, but if the financial data 4 has been provided appropriately, there will be no significant loss of consistency between the anonymous financial data 5 included in the same business operator data group 7.

[0076] For example, the evaluation data acquisition unit 14 may consider a case where the numerical data of a certain data item in specific anonymous financial data 5 included in the same business entity data group 7 is significantly different from the numerical data in other anonymous financial data 5. In this case, the evaluation data acquisition unit 14 may evaluate that this anonymous financial data 5 is inconsistent with the other anonymous financial data 5 and has low data credibility.

[0077] Also, for example, consider a case where the numerical data of a certain data item of specific anonymous financial data 5 included in the same business operator data group 7 corresponds to or has a small difference from the numerical data of other anonymous financial data 5. In this case, the evaluation data acquisition unit 14 may evaluate that this anonymous financial data 5 is consistent with the other anonymous financial data 5 and that the data is highly credible. The evaluation data acquisition unit 14 may acquire data related to these evaluations as evaluation data 6. Here, the evaluation data 6 may include, for example, a numerical result related to the difference between the data when comparing anonymous financial data 5 included in the same business operator data group 7.

[0078] Furthermore, when evaluating the anonymous financial data 5, multiple data items may be referenced, mainly including financial-related data included in the anonymous financial data 5. For example, the evaluation data acquisition unit 14 may acquire evaluation data 6 related to the anonymous financial data 5 by referencing 100 data items.

[0079] Furthermore, the evaluation data acquisition unit 14 may acquire evaluation data based on the distribution of data in one or more data items in the same business operator data group 7.

[0080] Fig. 8(a) is a schematic diagram showing an example of the distribution of data in a data item in a same-enterprise data group 7. In Fig. 8(a), the same-enterprise data group 7 includes five anonymous financial data 5, and the numerical data related to the data item 4 is represented by a number line. In Fig. 8(a), the numerical data of the data item 4 related to each anonymous financial data 5 is represented on the number line by a cross, triangle, inverted triangle, square, or star marker.

[0081] In Figure 8(a), the five numerical data corresponding to data item 4 are all concentrated around 1,000,000,000. In this case, the evaluation data acquisition unit 14 may evaluate the five anonymous financial data 5 in Figure 8(a) as having high data credibility.

[0082] 8(b) is a schematic diagram showing a modified example of the data distribution for a certain data item in the same business operator data group 7. The data distribution in FIG. 8(b) is significantly different from that in FIG. 8(a), in that the numerical data represented by the star-shaped markers is approximately 750,000,000, compared to the other numerical data, which is approximately 1,000,000,000. In this case, the evaluation data acquisition unit 14 may evaluate the anonymous financial data 5 related to the numerical data represented by the star-shaped markers in FIG. 8(b) as having low data credibility because it does not match the other anonymous financial data 5.

[0083] Furthermore, even if the difference in the numerical data is not as large as that shown in Figure 8(b), if there is a large variation in the values ​​of each data, the evaluation data acquisition unit 14 may evaluate the anonymous financial data 5 as having low credibility. For example, the evaluation data acquisition unit 14 may calculate the variance of the data, and if the variance value exceeds a preset threshold, may evaluate the data as having low credibility.

[0084] By performing an analysis based on the data distribution, it is possible to analyze whether and to what extent the anonymous financial data 5 is consistent with other anonymous financial data 5 included in the same business data group. In this way, by analyzing the data distribution, it is possible to obtain evaluation data 6 based on the variability and bias of the data. These analyses and evaluations based on the data distribution may be included in the evaluation data 6.

[0085] Furthermore, such an evaluation based on the data distribution may be performed for multiple data items. For example, the evaluation data acquisition unit 14 may evaluate the credibility of data for multiple data items based on the data distribution, and acquire evaluation data 6 for the anonymous financial data 5 by combining these evaluations. Here, each data item may be weighted as appropriate.

[0086] 8(a) and 8(b), the evaluation data acquiring unit 14 is not limited to using a one-dimensional data distribution focusing on one data item, but may also consider the distribution of data in a multidimensional vector space by referring to multiple data items. For example, the evaluation data acquiring unit 14 may set a two-dimensional vector space with the asset amount on the vertical axis and the liability amount on the horizontal axis, perform an analysis based on the data distribution in this vector space, and include the analysis results in the evaluation data 6.

[0087] Based on these analyses and evaluations, the evaluation data acquisition unit 14 may acquire evaluation data 6 including reliability indicating the credibility of the anonymous financial data 5. The reliability is a quantitative evaluation of the credibility of the anonymous financial data 5 from the viewpoint of whether the anonymous financial data 5 is accurate, whether the anonymous financial data 5 is consistent with other data in the same business entity data group 7, or whether the contents of the anonymous financial data 5 are consistent as financial statements, and is expressed as a score from 0 to 100 or a rank such as A, B, C, or the like.

[0088] For example, the evaluation data acquisition unit 14 may quantitatively evaluate the anonymous financial data 5 using known techniques related to data science and acquire the reliability. For example, the evaluation data acquisition unit 14 may acquire the reliability by combining factors such as data variance, distance between data, and the number of samples of anonymous financial data 5 included in the same business operator data group 7. Furthermore, for example, the evaluation data acquisition unit 14 may quantitatively evaluate the anonymous financial data 5 using known techniques related to machine learning and acquire the reliability.

[0089] The evaluation data acquisition unit 14 may identify a data item requiring caution based on the acquired evaluation data 6. Here, the data item requiring caution is a data item that is causing a decrease in the reliability of the anonymous financial data 5. For example, if the data distribution of data item 4 is as shown in FIG. 8(b), the anonymous financial data 5 represented by the star-shaped marker is not consistent with other data, and therefore has a low reliability. In this case, the evaluation data acquisition unit 14 may identify data item 4 as a data item requiring caution in the anonymous financial data 5 represented by the star-shaped marker.

[0090] Here, the evaluation data acquisition unit 14 may acquire information regarding the degree to which the caution data item reduces the reliability. For example, the evaluation data acquisition unit 14 analyzes the distribution of data for data items other than data item 4 shown in FIG. 8(b) and acquires the degree to which the discrepancy in the numerical data for data item 4 reduces the reliability. That is, the evaluation data acquisition unit 14 acquires a numerical value or the like indicating the degree to which the difference in the numerical data for data item 4 shown in FIG. 8(b) contributes to the reduction in the reliability of anonymous financial data 5 represented by a star-shaped marker. Here, the degree to which the caution data item reduces the reliability is expressed as a score from 0 to 100 or a rank such as A, B, C, or the like.

[0091] Furthermore, the evaluation data acquiring unit 14 may include, in the evaluation data 6, information on the caution data items and the degree to which the caution data items lower the reliability.

[0092] The evaluation data acquiring unit 14 may convert the contents of the evaluation data 6 into a form or diagram that is easy for humans to understand, and include these in the evaluation data 6. For example, the evaluation data 6 may include a diagram such as a radar chart that shows the differences between data in a group of data from the same business operator.

[0093] <Evaluation data provision step S15> In the evaluation data providing step S15, the evaluation data providing unit 15 provides part or all of the evaluation data 6 to the financial institution 3 that is the provider of the anonymous financial data 5.

[0094] 1, the evaluation data providing unit 15 provides evaluation data 6a related to the anonymous financial data 5a to the financial institution 3a that provided the anonymous financial data 5a. The evaluation data providing unit 15 also provides evaluation data 6b related to the anonymous financial data 5b to the financial institution 3b that provided the anonymous financial data 5b. In this way, the evaluation data providing unit 15 provides evaluation data 6 corresponding to the provided anonymous financial data 5 to the financial institution 3 that provided the anonymous financial data 5.

[0095] For example, by acquiring the evaluation data 6 from the evaluation data provider 15, the financial institution 3a can ascertain the extent of the difference or variation between the financial data 4a provided by the business operator 2 and the financial data 4b submitted to the financial institution 3b by the same business operator 2. Furthermore, by referring to the evaluation data 6, a person checking the financial data 4 at the financial institution 3a can accurately determine whether the financial data 4a provided by the business operator 2 has been manipulated.

[0096] The evaluation data providing unit 15 may provide information regarding the caution data items and the degree to which the caution data items reduce the reliability to the financial institution 3. In this case, a person checking the financial data 4 at the financial institution 3a can more accurately and quickly determine whether the financial data 4a provided by the business operator 2 has been manipulated in terms of financial settlement details by closely examining the financial data 4, focusing on the caution data items.

[0097] The evaluation data providing unit 15 may partially restrict the evaluation data 6 to be provided to the financial institution 3. For example, if the evaluation data 6 to be provided to a specific financial institution 3 includes information that can identify confidential information obtained from other financial institutions 3, the evaluation data providing unit 15 may delete the relevant part from the evaluation data 6 before providing the evaluation data 6 to the financial institution 3.

[0098] FIG. 9 is a schematic diagram showing an example of a radar chart provided to the financial institution 3 by the evaluation data providing unit 15. The radar chart in FIG. 9 is included in the evaluation data 6. The radar chart in FIG. 9 visually represents the differences between data in the same business operator data group 7. The radar chart in FIG. 9 displays data items 4 to 15, and these data items can be set as appropriate. For example, it is also possible to change the data items in the radar chart in response to a request from the financial institution 3.

[0099] By referring to the radar chart in Figure 9, a person checking the financial data 4 at the financial institution 3 can easily understand the extent of the difference or variation between the financial data 4 provided by the business 2 and the financial data 4 submitted by the same business 2 to other financial institutions. This allows the financial institution 3 to more accurately and quickly determine whether the financial data 4 provided by the business 2 has been manipulated.

[0100] For example, if the anonymous financial data 5 submitted by financial institution 3 corresponds to the data indicated by the solid line in Figure 9, financial institution 3 can determine that the numerical value in data item 6 is significantly different from the data provided to other financial institutions. In this case, financial institution 3 that provided anonymous financial data 5 corresponding to the data indicated by the solid line may determine that the financial data 4 obtained from business operator 2 has been manipulated.

[0101] In this case, data item 6 is a caution data item. Therefore, the evaluation data 6 provided to the financial institution 3 by the evaluation data providing unit 15 may include information that the data item 6 is a caution data item and information regarding the degree to which the data item 6 reduces the reliability.

[0102] The above steps complete the financial data evaluation method to which the present invention is applied. Steps S11 to S15 may be repeatedly executed as appropriate. For example, steps S11 to S15 may be executed periodically at predetermined intervals, or may be executed when the database 8 is updated.

[0103] According to the first embodiment, the database construction unit 11 collects anonymous financial data 5, which is financial data 4 that has been anonymized, from multiple financial institutions 3. Therefore, the financial data evaluation device 1 can collect a large amount of data on the financial status of businesses, which is normally difficult to collect due to confidentiality obligations, and construct a database 8. Furthermore, even if a person who owns the financial data evaluation device 1 constructs the database 8, they cannot identify the businesses 2 linked to the anonymous financial data 5, so confidentiality regulations are observed.

[0104] Furthermore, according to the first embodiment, the same business operator determination unit 12 classifies a large amount of collected anonymous financial data 5 into groups related to the same business operator 2. The data group acquisition unit 13 acquires the same business operator data group 7 based on the anonymous financial data 5 classified into groups related to the linked business operators. Therefore, the financial data evaluation device 1 can perform analysis and evaluation using data related to the same business operator 2 while maintaining the anonymity of the data.

[0105] Furthermore, according to the first embodiment, the evaluation data acquisition unit 14 acquires evaluation data 6 regarding the anonymous financial data 5 based on the distribution of data in the same business operator data group 7, etc. Furthermore, the evaluation data provision unit 15 provides the evaluation data 6 to the financial institution 3. Therefore, by providing the financial data evaluation device 1 with the anonymous financial data 5 regarding the financial data 4 that the financial institution 3 manages, the financial institution 3 can obtain the results of an analysis of the anonymous financial data 5 provided by the financial institution 3 in light of the anonymous financial data 5 provided by other financial institutions 3. Therefore, the financial institution 3 can accurately determine whether the financial settlement details in the financial data 4 have been manipulated, without requiring the person checking the financial data 4 to perform a huge amount of work.

[0106] Furthermore, according to the first embodiment, the database construction unit 11 collects anonymous financial data 5, which is financial data 4 anonymized, from multiple financial institutions 3 and constructs a database 8. The evaluation data acquisition unit 14 acquires evaluation data 6 indicating an evaluation of the anonymous financial data 5 based on the same business operator data group 7. The evaluation data provision unit 15 provides some or all of the evaluation data 6 to the financial institution 3 that is the provider of the anonymous financial data 5. Therefore, the financial data evaluation system 100 according to this embodiment can collect a large amount of anonymous financial data 5 and then provide the financial institution 3 with evaluation data 6, which is the result of an evaluation using the anonymous financial data 5. This enables the financial institution 3 to accurately determine whether financial statements have been manipulated in the financial data 4 submitted by the business operator 2.

[0107] Although an embodiment of the present invention has been described, this embodiment is presented as an example and is not intended to limit the scope of the invention. This novel embodiment can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. This embodiment and its modifications are included within the scope and spirit of the invention, and are also included in the invention described in the claims and their equivalents. [Explanation of symbols]

[0108] 1: Financial data evaluation device 2: Business operator 3: Financial institutions 3a: Financial institutions 3b: Financial institution 4: Financial Data 4a: Financial Data 4b: Financial Data 5: Anonymous financial data 5a: Anonymous Financial Data 5b: Anonymous Financial Data 5c: Anonymous Financial Data 5d: Anonymous Financial Data 5e: Anonymous Financial Data 6: Evaluation data 6a: Evaluation data 6b: Evaluation data 7: Data set from the same business operator 7a: Data set from the same operator 7c: Same company data group 8: Database 11: Database Construction Department 12: Same business operator determination department 13: Data group acquisition section 14: Evaluation data acquisition unit 15: Evaluation Data Providing Department 100: Financial Data Evaluation System 101: CPU 102:ROM 103:RAM 104: Storage device 105: Interface 106: Interface 107: Interface 108: Input device 109:Display device 110: Internal bus 111: Housing S11: Database construction step S12: Same business operator determination step S13: Data collection step S14: Evaluation data acquisition step S15: Evaluation data provision step

Claims

1. A financial data evaluation system for evaluating financial data provided by a business operator to a financial institution, a database construction means for collecting the anonymized financial data from a plurality of the financial institutions and constructing a database; same business operator determination means for determining whether the anonymous financial data are related to the same business operator by comparing the anonymous financial data contained in the database; a data group acquisition means for acquiring a same business operator data group, which is a group of the anonymous financial data related to the same business operator, based on the determination by the same business operator determination means; evaluation data acquisition means for acquiring evaluation data indicating an evaluation of the anonymous financial data based on the same business entity data group acquired by the data group acquisition means; The financial institution may provide the anonymous financial data to the financial institution by providing part or all of the evaluation data acquired by the evaluation data acquisition means. A financial data evaluation system characterized by:

2. the anonymous financial data comprises a plurality of data items; The evaluation data acquisition means acquires the evaluation data based on a distribution of data in one or more of the data items of the same business entity data group.

2. The financial data evaluation system according to claim 1, wherein:

3. The evaluation data acquisition means acquires the evaluation data including a reliability indicating the authenticity of the anonymous financial data.

3. The financial data evaluation system according to claim 2, wherein:

4. The evaluation data acquisition means identifies, based on the evaluation data, data items that are causing a decrease in the reliability of the anonymous financial data and that require attention; The evaluation data providing means provides information regarding the caution data items and the degree to which the caution data items lower the reliability to the financial institution that is the source of the anonymous financial data.

4. The financial data evaluation system according to claim 3, wherein:

5. A financial data evaluation method for evaluating financial data provided by a business operator to a financial institution, comprising: a database construction step of collecting the anonymized financial data from a plurality of the financial institutions and constructing a database; a same business operator determination step of determining whether the anonymous financial data are related to the same business operator by comparing the anonymous financial data contained in the database; a data group acquisition step of acquiring a same business operator data group, which is a group of the anonymous financial data related to the same business operator, based on the determination made by the same business operator determination step; an evaluation data acquisition step of acquiring evaluation data indicating an evaluation of the anonymous financial data based on the same business entity data group acquired by the data group acquisition step; an evaluation data providing step of providing a part or all of the evaluation data acquired by the evaluation data acquiring step to the financial institution that is the source of the anonymous financial data; A method for evaluating financial data, comprising causing a computer to execute the above steps.

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