WO2018150606A1 - 情報処理装置、情報処理方法およびコンピュータプログラム - Google Patents
情報処理装置、情報処理方法およびコンピュータプログラム Download PDFInfo
- Publication number
- WO2018150606A1 WO2018150606A1 PCT/JP2017/027037 JP2017027037W WO2018150606A1 WO 2018150606 A1 WO2018150606 A1 WO 2018150606A1 JP 2017027037 W JP2017027037 W JP 2017027037W WO 2018150606 A1 WO2018150606 A1 WO 2018150606A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- individual
- information
- personal
- score
- data
- Prior art date
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/03—Credit; Loans; Processing thereof
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0407—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the identity of one or more communicating identities is hidden
- H04L63/0414—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the identity of one or more communicating identities is hidden during transmission, i.e. party's identity is protected against eavesdropping, e.g. by using temporary identifiers, but is known to the other party or parties involved in the communication
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
- H04L63/0815—Network architectures or network communication protocols for network security for authentication of entities providing single-sign-on or federations
Definitions
- the present invention relates to data processing technology, and more particularly to an information processing apparatus, an information processing method, and a computer program.
- a technology for efficiently realizing asset liability management (Asset Liability Management (ALM)) for the purpose of normal bank management has been proposed (for example, see Patent Document 1). Further, a technique for improving the accuracy of debtor asset assessment and reducing credit risk of financial institutions has been proposed (see, for example, Patent Document 2).
- the present invention has been made on the basis of the above-mentioned idea of the present inventor, and a main purpose is to provide a technique for supporting accurate evaluation of the trustworthiness of an individual.
- an information processing apparatus acquires data that reflects personal ability or personality and acquires a plurality of types of performance data indicating the performance that the individual has achieved in the past. And a score determination unit that determines a personal score indicating the level of personal trust based on a plurality of types of performance data acquired by the acquisition unit.
- Another aspect of the present invention is an information processing method.
- This method is data that reflects the individual's ability or personality, and includes a step of acquiring a plurality of types of performance data indicating the results achieved by the individual in the past, and a plurality of types of performance data acquired in the acquiring step. Based on this, the computer executes a step of determining a personal score indicating the level of personal trust.
- a business support device (a business support device 14 to be described later) that supports a loan business for individuals (for example, a housing loan) in a financial institution.
- This business support device dynamically calculates both credit amount and lending interest rate for each customer according to various attribute information of individual customers (including individuals who are potential customers and individuals who are sales targets) To do.
- financial institutions are supported to provide services that are more in line with the conditions of individual customers.
- the credit amount can be said to be a loanable amount, and can also be said to be a loan upper limit.
- a personal number (My Number (registered trademark)) is assigned to each citizen from a public institution (government, etc.).
- the personal number is an ID unique to the individual that is not changed throughout the lifetime. From 2016, personal numbers will be required for administrative procedures such as social security, taxes and disaster countermeasures.
- the business support apparatus uses this personal number to collect various attribute information of an individual who receives a loan from an external apparatus.
- FIG. 1 shows a configuration of an information system 10 according to the first embodiment.
- the information system 10 includes a PC 12 a and a PC 12 b collectively referred to as a PC 12, a business support device 14, and a personal attribute information source 16. 1 are connected via a communication network 18 including a LAN, a WAN, the Internet, and a dedicated line.
- a communication network 18 including a LAN, a WAN, the Internet, and a dedicated line.
- encryption and authentication processing for maintaining security may be performed as appropriate during communication.
- PC 12a is a PC installed in bank A and operated by a bank A loan officer.
- the PC 12b is a PC installed in the bank B and operated by a bank B loan officer.
- the PC 12 may be another type of information terminal such as a tablet terminal or a smartphone.
- the personal attribute information source 16 is a general term for a plurality of database devices (hereinafter referred to as “DB”) that store various attribute information related to individuals who are debtors.
- the personal attribute information source 16 includes a collateral information DB 20, a route price information DB 22, a property information DB 24, an annuity information DB 26, a possessed securities information DB 28, an insurance information DB 30, a debt information DB 32, an income information DB 34, a work information DB 36, and a company information DB 38. .
- each DB included in the personal attribute information source 16 is installed.
- each DB is installed outside the bank A and in a company or institution outside the bank B, but as a modification, it is installed in at least one of the bank A and the bank B. Good.
- One DB may be distributed and installed in a plurality of companies and institutions.
- the retained securities information DB 28 may be realized by a plurality of securities company DBs
- the liability information DB may be realized by a plurality of banks or credit card company DBs.
- the personal attribute information held in the personal attribute information source 16 includes information indicating personal assets, liabilities, and income.
- An asset in the embodiment means an economic value that is attributed to an individual and expected to generate profit for the individual, and can be said to be a property.
- a liability means a payment obligation attributed to an individual and owed to an external third party, and includes, for example, a borrowing.
- the collateral information DB 20 the route price information DB 22, the property information DB 24, the pension information DB 26, the securities information DB 28, and the insurance information DB 30 hold information related to personal assets.
- the liability information DB 32 holds information related to individual debt
- the income information DB 34 and the work information DB 36 hold information related to personal income. Specific examples are shown below.
- the collateral information DB 20 holds the appraisal value of land and buildings that are collateral (for example, assets subject to mortgage setting) in financing.
- the collateral information DB 20 may be installed in, for example, a research company or a real estate company.
- the route price information DB 22 holds information on route prices throughout Japan.
- the route price information DB 22 may be installed in, for example, a public organization (such as a tax organization).
- the property information DB 24 holds information such as price information and sales time of properties (land, buildings, etc.) that an individual intends to purchase.
- the property information DB 24 may be installed in a real estate company or a home sales company.
- the pension information DB 26 holds personal pension information.
- the pension information includes the annual amount that the individual will receive in the future, for example, the defined contribution pension amount.
- the pension information DB 26 may be installed in a private or public pension mechanism or pension information service company.
- the held securities information DB 28 holds information such as stocks and bonds held by individuals.
- the owned securities information DB 28 may be installed in a plurality of securities companies.
- the insurance information DB 30 holds information on life insurance that an individual joins, for example, saving life insurance.
- Insurance information DB30 may be installed in a plurality of insurance companies.
- the liability information DB 32 holds information on liabilities (for example, car loans) for which individuals are obligated to pay.
- the debt information DB 32 may be installed in a bank other than the banks A and B, a credit card company, or a credit information agency.
- the income information DB 34 holds information (annual income amount, income amount, etc.) indicating individual income.
- the income information DB 34 may be installed in a public organization such as a tax organization.
- the work information DB 36 holds information such as the name of the company where the individual works, the treatment at the place of work (position, etc.), and the length of service.
- the work information DB 36 may be installed in a company where a person works or a credit information agency.
- the company information DB 38 holds information indicating the management status and financial status of various companies.
- the company information DB 38 may be installed in a credit information agency, an ICT service company, or the like.
- Each DB included in the personal attribute information source 16 stores attribute information related to each individual in association with a personal number assigned to each individual.
- each DB receives an acquisition request for personal attribute information from a predetermined external device via the communication network 18, each DB provides attribute information associated with the personal number designated as a key in the request to the request source device.
- the business support device 14 is an information processing device such as a server managed by an ICT service company.
- the ICT service company is, for example, a system integrator or an ASP (Application Service Provider) provider.
- the business support device 14 provides the PC 12a and the PC 12b with web pages including information (hereinafter also referred to as “business support information”) that supports the business of a plurality of financial institutions (in the embodiment, the bank A and the bank B). Since the function of the web server is publicly known, description thereof is omitted.
- the business support apparatus 14 uses the personal number of the individual to be analyzed (hereinafter also referred to as “analysis target individual”) as the loan destination candidate of the A bank or the B bank, and uses the personal number of the analysis target individual. Collect multiple types of attribute information related to debt, income, etc. from the personal attribute information source 16. Then, based on the collected plural types of attribute information, business support information for supporting the execution of the loan business in accordance with the state of each individual to be analyzed is provided to the PC 12 of the A bank or the B bank. Further, the business support apparatus 14 provides such business support information providing service as an ASP type service to a plurality of financial institutions (in the embodiment, bank A and bank B).
- FIG. 2 is a block diagram showing a functional configuration of the business support apparatus 14 of FIG.
- the business support apparatus 14 includes a control unit 40, a storage unit 42, and a communication unit 44.
- the control unit 40 executes various types of data processing such as collection processing of attribute information related to the individual to be analyzed and generation processing of business support information for the banks A and B.
- the storage unit 42 is a storage area that stores data that is referred to or updated by the control unit 40.
- the communication unit 44 communicates with an external device according to a known communication protocol.
- the control unit 40 transmits / receives data to / from each DB included in the PC 12a, PC 12b, and personal attribute information source 16 via the communication unit 44.
- Each block shown in the block diagram of the present specification can be realized in terms of hardware by an element such as a CPU and a memory of a computer or a mechanical device, and in terms of software, it can be realized by a computer program or the like. , Depicts functional blocks realized by their cooperation. Therefore, those skilled in the art will understand that these functional blocks can be realized in various forms by a combination of hardware and software.
- a business support application including a module corresponding to each block of the control unit 40 may be installed in the storage of the business support device 14.
- the CPU of the business support apparatus 14 may exhibit the functions of these blocks by reading out the modules corresponding to the respective blocks of the control unit 40 to the main memory and executing them.
- Each functional block of the storage unit 42 may be realized by storing data in a storage device such as a storage or a memory of the business support device 14.
- the storage unit 42 includes a bank A parameter holding unit 46 and a bank B parameter holding unit 48.
- the bank A parameter holding unit 46 stores parameters predetermined by the bank A.
- the bank B parameter holding unit 48 is a parameter determined independently of the parameters stored in the bank A parameter holding unit 46, and stores a parameter predetermined by the bank B.
- the parameters stored in the bank A parameter holding unit 46 and the bank B parameter holding unit 48 are data for deriving the score of the individual to be analyzed according to the contents of the asset information, debt information, and income information of the individual to be analyzed. is there.
- This parameter is information indicating the degree to which each of the plurality of attribute information of the individual to be analyzed affects the work support information (in the embodiment, the credit amount and the lending interest rate), and can be said to be data for weighting.
- This parameter is not limited to a numerical value, and may be a program indicating an algorithm for realizing the degree of influence or weighting according to the attribute value.
- a parameter for reflecting the content indicated by the attribute information in the credit amount is referred to as a credit amount parameter
- a parameter for reflecting the content indicated by the attribute information in the interest rate is referred to as an interest rate parameter.
- the credit of each attribute information classified as asset information so that the amount of assets indicated by the asset information (for example, the market capitalization of the stock held) is positively correlated with the credit amount, while being inversely correlated with the interest rate.
- An amount parameter and an interest rate parameter may be defined.
- the credit amount parameter and interest rate parameter of each attribute information classified as liability information so that the amount of debt indicated by the liability information (for example, the existing loan balance) is inversely correlated with the credit amount while being directly correlated with the interest rate.
- the credit amount parameter and interest rate of each attribute information classified as income information so that the amount of income indicated by the income information (including the height of the position) is positively correlated with the credit amount and inversely correlated with the interest rate.
- a parameter may be defined.
- Each bank may set the parameters of each information item so that the correlation coefficient of the information item to be emphasized with respect to the interest rate or the like is larger than the correlation coefficient of other information items.
- different weights may be set for each type according to the judgment of each bank. The same applies to debt information and income information. This example will be described below.
- bank A places more importance on the market capitalization of stocks than the defined contribution pension amount.
- Bank A uses the credit parameter for the defined contribution pension amount and the amount of the defined contribution pension amount to be more positively correlated with the credit amount than the degree to which the defined contribution pension amount is directly correlated with the credit amount.
- a credit amount parameter for the market capitalization of stocks may be set.
- bank A has an interest rate parameter for the defined contribution pension amount, so that the degree of the inverse correlation to the interest rate of the market capitalization of the stock is stronger than the degree of the inverse correlation to the interest rate of the defined contribution pension amount, You may set the interest rate parameter for the market capitalization of stocks.
- Bank B places more importance on the defined contribution pension amount than the market capitalization of shares.
- Bank B has a credit parameter for the defined contribution pension amount and the amount of the defined contribution pension amount that is more positively correlated with the credit amount than the degree that the market capitalization of the shares held is positively correlated with the credit amount.
- a credit amount parameter for the market capitalization of stocks may be set.
- Bank B has an interest rate parameter for the defined contribution pension amount, so that the degree of the inverse correlation with respect to the interest rate of the defined contribution pension amount is stronger than the degree of inverse correlation with respect to the interest rate of the market capitalization of shares. You may set the interest rate parameter for the market capitalization of stocks.
- each of the plurality of financial institutions that use the business support apparatus 14 sets arbitrary values as the credit amount parameter and the interest rate parameter.
- the control unit 40 includes a personal attribute acquisition unit 50, a personal score determination unit 52, a support information generation unit 54, a support information provision unit 60, and a parameter setting unit 62.
- the personal attribute acquisition unit 50 transmits an attribute acquisition request designating the personal number of the individual to be analyzed as a search key to a plurality of DBs included in the personal attribute information source 16.
- the personal attribute acquisition unit 50 is attribute information associated with the personal number of the search key from each DB included in the personal attribute information source 16, for example, at least one of asset information, liability information, and income information related to the individual to be analyzed. Get one.
- the personal attribute acquisition unit 50 acquires the defined contribution pension amount of the individual to be analyzed from the pension information DB 26 installed in the public institution.
- the personal attribute acquisition unit 50 acquires stock brands and quantities held by the individual to be analyzed from the securities information DB 28 installed in the securities company.
- the personal attribute acquisition unit 50 acquires the liabilities (for example, the balance of the car loan, the repayment status, etc.) held by the individual to be analyzed from the debt information DB 32 installed in a bank other than Bank A and Bank B or a credit information agency.
- the personal score determination unit 52 is a plurality of attribute information regarding the individual to be analyzed acquired by the personal attribute acquisition unit 50. Specifically, the personal score determination unit 52 includes a plurality of attribute information classified as asset information, liability information, or income information. First, the score of the individual to be analyzed for determining the business contents of the financial institution for the individual to be analyzed is determined. Specifically, the personal score determination unit 52 determines a score according to a plurality of attribute information related to the individual to be analyzed and parameters predetermined by the bank A or the bank B for each attribute information.
- the score of the individual to be analyzed is data for adjusting the value of the reference credit amount and the value of the reference interest rate specified by the bank A or bank B as the analysis request source.
- a score for adjusting the reference credit amount is called a credit amount adjustment score
- a score for adjusting the reference interest rate is called an interest rate adjustment score.
- the credit amount adjustment score can be said to be adjustment data that reflects the actual attribute information of the individual to be analyzed on the credit amount by the weighting indicated by the credit amount parameter.
- the interest rate adjustment score can be said to be adjustment data that reflects the actual attribute information of the individual to be analyzed to the interest rate by the weighting indicated by the interest rate parameter.
- the standard credit amount and the standard interest rate are standard credit amount and interest rate determined in advance in each of the bank A and the bank B.
- the reference interest rate may be a conventional loan interest rate (a floating interest rate, a 10-year fixed interest rate, etc.) determined based on a short-term prime rate.
- a reference credit amount and a reference interest rate are designated by a person in charge at each bank when an analysis request is made to the business support apparatus 14.
- the business support apparatus 14 may acquire the reference credit amount and the reference interest rate from each bank apparatus in advance and store them in the storage unit 42 in advance.
- the personal score determination unit 52 of the embodiment includes a collateral information rate, a pension rate, a holding stock rate, a participation insurance rate, a service company rank rate, a service years rate, a job title rate, a debt rate, and an income rate as credit adjustment scores. decide.
- the personal score determination unit 52 determines a collateral information rate, an annuity rate, a holding stock rate, an enrollment insurance rate, a working company rank rate, a service years rate, a job title rate, a debt rate, and an income rate as interest rate adjustment scores.
- the personal score determination unit 52 stores the collateral information (land and building), building age, road price, property information acquired from the personal attribute information source 16, the bank A parameter holding unit 46 or the bank B parameter holding unit 48.
- the collateral information rate as the credit amount adjustment score is calculated according to the credit amount parameter associated with each attribute information.
- the personal score determination unit 52 uses the collateral information (land and building), age, road price, property information acquired from the personal attribute information source 16 and the bank A parameter holding unit 46 or the bank B parameter holding unit 48.
- a collateral information rate as an interest rate adjustment score is calculated according to the interest rate parameter associated with each attribute information.
- the credit amount parameter stored in the bank A parameter holding unit 46 and the bank B parameter holding unit 48 of the embodiment increases the credit amount as the asset amount of the individual to be analyzed (for example, the market price or valuation amount of the stock held) increases.
- the value is determined as follows. Increasing the credit amount can be said to increase the increment from a predetermined standard reference credit amount.
- the value of the interest rate parameter is determined such that the interest rate decreases as the asset amount of the individual to be analyzed increases. Reducing the interest rate can be said to increase the discount from a predetermined standard reference interest rate.
- the individual score determination unit 52 determines the collateral information rate, the pension rate, the stock holding rate, and the enrollment insurance rate as the credit amount adjustment score so that the credit amount increases as the asset amount of the individual to be analyzed increases.
- the personal score determination unit 52 determines a collateral information rate, an annuity rate, a stock holding rate, and an enrollment insurance rate as an interest rate adjustment score so that the interest rate decreases as the asset amount of the individual to be analyzed increases.
- the relationship between the amount of income and the income rate is the same. As described above, when the credit risk (in other words, credit loss risk) of a specific individual to be analyzed is relatively low, the credit amount to the individual is relatively increased and the interest rate is relatively decreased. To adjust.
- the credit amount parameter stored in the bank A parameter holding unit 46 and the bank B parameter holding unit 48 of the embodiment is such that the credit amount decreases as the debt amount (for example, borrowing balance) of the individual to be analyzed increases. Is determined.
- the value of the interest rate parameter is determined such that the interest rate increases as the amount of debt of the individual to be analyzed increases.
- the individual score determination unit 52 determines the collateral information rate, the pension rate, the stock holding rate, and the enrollment insurance rate as the credit amount adjustment score so that the credit amount decreases as the amount of debt held by the individual to be analyzed increases.
- the personal score determination unit 52 determines the collateral information rate, pension rate, stock holding rate, and insurance coverage rate as the interest rate adjustment score so that the interest rate increases as the debt amount of the individual to be analyzed increases.
- the support information generation unit 54 generates information for supporting the business of the financial institution for the analysis target individual based on the score of the analysis target individual determined by the personal score determination unit 52. Specifically, the support information generation unit 54 determines a value obtained by adjusting the reference credit amount based on the credit amount adjustment score of the analysis target individual as the credit amount for the analysis target individual. Further, the support information generation unit 54 determines a value obtained by adjusting the reference interest rate based on the interest rate adjustment score of the analysis target individual as the interest rate for the analysis target individual. Then, the support information generation unit 54 generates business support information indicating the credit amount and interest rate for the individual to be analyzed.
- the support information generation unit 54 includes a credit amount determination unit 56 and an interest rate determination unit 58.
- the credit amount determination unit 56 determines the credit amount for the individual to be analyzed by adjusting the reference credit amount based on the credit amount adjustment score of the individual to be analyzed.
- the credit amount determination unit 56 adds a reference credit amount, a collateral information rate as a credit amount adjustment score, a pension rate, a stock holding rate, a working company rank rate, and a service years rate to a predetermined credit amount calculation formula (function).
- the position rate, debt rate, and income rate may be input, and the credit amount for the individual to be analyzed may be acquired as the calculation result.
- Credit amount for individuals to be analyzed standard credit amount x collateral information rate x pension rate x holding stock rate x working company rank rate x years of service rate x position rate x liability rate x income rate
- the individual score determination unit 52 is “0 ⁇ rate ⁇ 1” when the credit amount for the individual to be analyzed is smaller than the reference credit amount, and “1 ⁇ rate” when the credit amount for the individual to be analyzed is equal to or greater than the reference credit amount.
- the score of each attribute information is determined so that it becomes. In addition, you may determine so that the multiplication result of multiple types of credit amount adjustment scores may be in the said range.
- the interest rate determination unit 58 determines the lending interest rate for the individual to be analyzed by adjusting the reference interest rate based on the interest rate adjustment score of the individual to be analyzed.
- the interest rate determination unit 58 calculates the reference interest rate, the collateral information rate as the interest rate adjustment score, the pension rate, the stock holding rate, the working company rank rate, the years of service rate, the job rate,
- the debt rate and the income rate may be input, and the interest rate for the individual to be analyzed may be acquired as the calculation result.
- Interest rate for individuals to be analyzed standard credit amount x collateral information rate x pension rate x holding stock rate x working company rank rate x years of service rate x position rate x debt rate x income rate
- the personal score determination unit 52 Each attribute is set so that “0 ⁇ rate ⁇ 1” when the interest rate for the individual subject to analysis is discounted from the base rate, and “1 ⁇ rate” when the interest rate for the individual subject to analysis is greater than or equal to the base rate. Determine the information score. In addition, you may determine so that the multiplication result of several types of interest rate adjustment scores may become the said range.
- the support information providing unit 60 transmits the business support information including the credit amount and interest rate for the individual to be analyzed generated by the support information generating unit 54 to the analysis request source PC 12a or PC 12b. Specifically, the web page data indicating the business support information is transmitted to the PC 12a or PC 12b.
- the parameter setting unit 62 transmits and displays a web page for changing at least one of the credit amount parameter and the interest rate parameter to the PC 12a and the PC 12b.
- the parameter setting unit 62 receives the initial value and the updated value of the credit amount parameter and the interest rate parameter input to the web page from the PC 12a and the PC 12b.
- the parameter setting unit 62 reflects the received parameter value in the score determination processing of the individual to be analyzed by the personal score determination unit 52.
- the parameter setting unit 62 stores the credit amount parameter and the interest rate parameter value received from the PC 12 a in the bank A parameter holding unit 46. In other words, the previous parameter value stored in the bank A parameter holding unit 46 is updated to the latest value received from the PC 12a.
- the parameter setting unit 62 stores the value of the credit amount parameter and the interest rate parameter received from the PC 12 b in the bank B parameter holding unit 48. In other words, the previous parameter value stored in the bank B parameter holding unit 48 is updated to the latest value received from the PC 12b.
- the updated values of the credit amount parameter and the interest rate parameter are reflected in the score of the individual to be analyzed, and are reflected in the credit amount and the interest rate for the individual to be analyzed.
- the loan officer of bank A activates the web browser of the PC 12a, logs in to the business support site provided by the business support device 14, and selects the loan business support menu.
- the business support device 14 transmits a web page (referred to as “analysis target designation page”) for inputting information related to the individual to be analyzed to the PC 12a for display.
- the loan officer of Bank A sets the individual credit number and interest rate on the analysis target designation page in addition to the individual number of the individual to be analyzed as the individual to be analyzed as the individual who is the mortgage loan candidate. Enter the operation.
- the web browser of the PC 12a transmits an analysis request, which is an HTTP request including the individual number of the individual to be analyzed, the reference credit amount, and the reference interest rate, to the business support apparatus 14.
- the personal attribute acquisition unit 50 of the business support device 14 uses the personal number specified in the request as a key to analyze from a plurality of DBs included in the personal attribute information source 16 Get multiple types of attribute information about an individual.
- the personal score determination unit 52 of the business support device 14 is a parameter stored in the bank A parameter holding unit 46, and responds to a plurality of types of attribute information according to a credit amount parameter predetermined by the analysis request source A bank.
- the credit amount adjustment score (shareholding rate, debt rate, etc.) is determined.
- the personal score determination unit 52 determines an interest rate adjustment score according to a plurality of types of attribute information according to interest rate parameters predetermined by the bank A as the analysis request source.
- the support information generation unit 54 of the business support device 14 determines the credit amount for the individual to be analyzed based on the reference credit amount specified in the analysis request and the credit amount adjustment score determined by the personal score determination unit 52. Further, the support information generation unit 54 determines the interest rate of the loan for the individual to be analyzed based on the reference interest rate specified in the analysis request and the interest rate adjustment score determined by the personal score determination unit 52. Then, the support information generation unit 54 generates web page data of business support information indicating the credit amount and interest rate of the loan to the individual to be analyzed, and the support information providing unit 60 transmits the web page data to the PC 12a for display. .
- the person in charge of bank A formulates a loan plan according to the credit amount and interest provided from the business support apparatus 14 and presents it to the individual to be analyzed.
- the credit amount and interest rate appropriate for each individual according to the asset holding status, debt holding status, and income status of each individual as a debtor are presented to the financial institution, Can support risk management and risk control of financial institutions.
- the stock is treated as a collateral element of debt and reflected in the credit amount and interest rate.
- the actual performance for example, company rank, length of service, title, treatment, etc.
- the collateral market value can be calculated by calculating the collateral value linked with the property price information.
- the business support device 14 performs the same process according to the analysis request transmitted from the PC 12b. Execute. However, when the individual score determination unit 52 determines the score of the individual to be analyzed, the parameters are stored in the bank B parameter holding unit 48, and the credit amount parameter and the interest rate parameter predetermined by the analysis request source B bank It differs in that it refers to.
- the loan officer of bank A determines the updated values of the credit amount parameter and the interest rate parameter.
- the loan officer of bank A activates the web browser of the PC 12a, logs in to the loan business support site provided by the business support device 14, and selects the parameter setting menu.
- the business support apparatus 14 transmits a web page (referred to as a “parameter setting page”) for inputting the credit amount parameter and the updated value of the interest rate parameter to the PC 12a for display.
- the loan officer inputs the updated value of the credit amount parameter and the interest rate parameter to the parameter setting page, and inputs an operation for reflecting the setting value.
- the web browser of the PC 12a transmits a parameter setting request, which is an HTTP request including the updated value of the credit amount parameter and the interest rate parameter, to the business support apparatus 14.
- a parameter setting request which is an HTTP request including the updated value of the credit amount parameter and the interest rate parameter
- the parameter setting unit 62 of the business support apparatus 14 stores the credit amount parameter and the updated value of the interest rate parameter included in the request in the bank A parameter holding unit 46.
- the setting operation of the credit amount parameter and the interest rate parameter of the bank B is the same, but the storage destination of the parameter value is the bank B parameter holding unit 48.
- the business support apparatus 14 collectively provides business support services for a plurality of financial institutions as an ASP service.
- each financial institution can enjoy the business support service at a lower cost than the construction of the business support device 14 on its own.
- the credit amount parameter and the interest rate parameter for determining the score of the individual to be analyzed can be set to values uniquely determined by each financial institution and can be changed as needed.
- each financial institution can cause the business support device 14 to determine the risk management policy and the credit amount and interest rate in accordance with the business strategy.
- FIG. 3 shows an example of financing for a certain individual.
- FIG. 3A shows individual attribute information at the time of the initial loan.
- FIG. 3B shows the credit amount (upper stage) and the interest rate (lower stage) determined by the business support apparatus 14 based on the attribute information shown in FIG.
- FIG. 4 shows an example of financing for the same individual as FIG.
- FIG. 4A shows individual attribute information five years after FIG. 3A.
- FIG. 4B shows the credit amount (upper stage) and the interest rate (lower stage) determined by the business support apparatus 14 based on the attribute information shown in FIG.
- FIG. 3 (a) Comparing the attribute information in FIG. 3 (a) with the attribute information in FIG. 4 (a), FIG. 3 (a) has a smaller liability amount, so FIG. 3 (a) has a lower credit risk based on the liability. It can be said. However, Figure 4 (a) has larger assets (collateral, share price, defined contribution pension amount, etc.) and income (working company rank, years of service, title, income amount). It can be said that the credit risk based on assets and income is smaller.
- the credit amount and interest rate calculated by the business support apparatus 14 comprehensively reflect the assets held, liabilities held, and income of the individual to be analyzed. In this example, the credit amount larger than FIG. 3B is calculated in FIG. 4B, and the interest rate smaller than FIG. 3B is calculated in FIG. 4B.
- a person in charge of a financial institution can propose an additional loan to a low interest rate to a customer by looking at the result of FIG.
- a credit amount smaller than that in FIG. 3B is calculated in FIG. In b), it is possible to calculate a higher interest rate than in FIG.
- each DB in the personal attribute information source 16 electronically stores attribute information related to the individual to be analyzed, and the business support apparatus 14 acquires the attribute information of the individual to be analyzed from each DB. did.
- at least a part of attribute information related to the individual to be analyzed may be reported verbally or on paper from the individual to be analyzed to bank A or bank B, and the attribute information thus reported is sent from the PC 12 to the business support apparatus 14. It may be entered.
- attribute information for example, in addition to the individual number, standard credit amount, and standard interest rate of the individual subject to analysis, one or more attribute information (stock stocks and quantity held, title and years of service at the workplace, etc.) declared by the individual subject to analysis
- the analysis request may be input from the PC 12 to the business support apparatus 14. It is suitable for acquiring attribute information for which electronic acquisition from an external DB is prohibited or restricted by law or attribute information that requires high confidentiality.
- the business support apparatus 14 of the above embodiment derives the credit amount adjustment score and the interest rate adjustment score of the analysis target individual according to the plurality of types of attribute information of the analysis target individual. Based on those scores, information (information indicating the credit amount and interest rate for the individual to be analyzed) that supports the financing operation from the financial institution to the individual to be analyzed was generated and provided to the PC 12.
- the business support device 14 is a score for determining the business content of the financial institution for the individual to be analyzed, and may determine a score other than the credit amount adjustment score and the interest rate adjustment score.
- a score indicating the importance of the individual to be analyzed for the financial institution may be determined, or a score indicating the accuracy of loan establishment, purchase of securities, contract of insurance, etc. may be determined.
- the support information generation unit 54 of the business support device 14 generates business support information indicating the score of the individual to be analyzed determined by the personal score determination unit 52, and the support information provision unit 60 displays the business support information. You may provide to PC12.
- the business support device 14 collects attribute information related to a plurality of individuals specified by the PC 12a or the PC 12b and stores business support information for supporting the business of the financial institution for the plurality of individuals.
- the generation may be executed collectively. In other words, the generation of business support information regarding a plurality of individuals may be executed as a batch process.
- the business support device 14 selects a score (for example, a score indicating the number of shares held) from a plurality of individuals. May extract individuals who satisfy the extraction conditions predetermined by the financial institution. Then, business support information including the extracted personal score and various attribute information may be generated and provided to the financial institution.
- the business support apparatus 14 collects attribute information about an analysis target person from a plurality of DBs included in the personal attribute information source 16 using a personal number assigned to the analysis target person from a public institution. .
- the first temporary number for identifying the analysis target person in the financial institution, and the analysis target individual in an entity different from the financial institution A second temporary number for identification may be determined in advance, and the first temporary number and the second temporary number may be associated with each other by a predetermined device.
- FIG. 5 shows the configuration of the information system of the fourth modified example.
- the information system 10 of the fourth modification includes a personal number management device 70 in addition to the configuration of FIG.
- the business support apparatus 14 accesses the personal number management apparatus 70 via the communication network 18.
- the personal number management apparatus 70 corresponds to the personal number management apparatus proposed by the present applicant in “Japanese Patent Application No. 2013-216936 (Japanese Patent Laid-Open No. 2015-79406)”.
- the personal number management device 70 receives a personal number report from an individual (not shown) (that is, an individual who can be analyzed), and based on the personal number, a financial institution (here, bank A). A first temporary number for identifying the individual is determined in step (b). The personal number management device 70 may directly transmit the determined first temporary number together with personal identification information (name, address, etc.) to the device of the bank A designated by the individual as the destination of the first temporary number. . Alternatively, the personal number management device 70 may provide the determined first temporary number to the personal device, and the individual may declare the first temporary number to the bank A.
- the personal number management device 70 receives a personal number declaration from the same individual, and determines a second temporary number for identifying the individual at each company or organization of the personal attribute information source 16 based on the personal number. To do.
- the second temporary number may be transmitted to the personal attribute information source 16 in the same manner as the first temporary number.
- the second temporary number is determined to be different for each company / institution managing the DB of the personal attribute information source 16, but here, as a second temporary number, for simplicity of explanation, explain.
- Each DB of the personal attribute information source 16 stores attribute information related to the individual to be analyzed in association with the second temporary number of the individual. Actually, DBs of companies and institutions different from each other may store attribute information related to the analysis target person in association with different second temporary numbers.
- an individual's personal number, first temporary number, and second temporary number are IDs having different systems, lengths, contents, and the like. Moreover, it is desirable that both the first temporary number and the second temporary number are determined to be IDs that are difficult to guess the original personal number.
- the first temporary number of the individual to be analyzed may be handled in the same manner as the personal number of the individual to be analyzed in the bank A, and the second temporary number of the individual to be analyzed is stored in the company or institution of the personal attribute information source 16 It may be handled in the same way as a personal number. However, since the first temporary number is different from the personal number, the number management cost in the bank A can be reduced, and the influence when the first temporary number is leaked is limited. The same can be said for the second temporary number.
- the personal number management device 70 stores the personal personal number, the first temporary number, and the second temporary number in association with each other (see, for example, FIG. 3 of JP-A-2015-79406).
- the personal number management device 70 receives a search request designating the first temporary number, the personal number management device 70 transmits information indicating the second temporary number associated with the first temporary number to the requesting device.
- the PC 12a of the fourth modified example transmits an analysis request including the first temporary number, the reference credit amount, and the reference interest rate of the individual to be analyzed to the business support apparatus 14.
- the personal attribute acquisition unit 50 of the business support apparatus 14 transmits a search request specifying the first temporary number specified in the analysis request to the personal number management apparatus 70, and the first temporary number The second temporary number managed in association with is acquired from the personal number management device 70.
- the personal attribute acquisition unit 50 transmits an attribute acquisition request designating the second temporary number as a key to a plurality of DBs included in the personal attribute information source 16, and manages the attribute information associated with the second temporary number. Is acquired from each DB.
- the personal attribute acquisition unit 50 may acquire a plurality of types of second temporary numbers from the personal number management device 70 together with information of the DB provided with each second temporary number. And you may transmit the search request which designated the different 2nd temporary number with respect to different DB.
- the personal number management device 70 centrally manages personal numbers that require high security and confidentiality. Since the financial institution and the personal attribute information source 16 perform information management using the first temporary number or the second temporary number different from the personal number as a key, the risk of leakage of the personal number can be reduced. In addition, the burden of personal number management at each company or institution can be reduced.
- the business support apparatus 14 collectively provides business support services for a plurality of financial institutions as an ASP service.
- the business support device 14 may be constructed as a device that generates business support information for one financial institution or a small number of financial institutions in the same company group.
- the business support apparatus 14 that includes the bank A parameter holding unit 46 but does not include the bank B parameter holding unit 48 may be built in the bank A.
- the business support apparatus 14 that includes the bank B parameter holding unit 48 but does not include the bank A parameter holding unit 46 may be built in the bank B.
- the analysis target by the business support apparatus 14 is an individual, but the subject to be analyzed is not limited to an individual.
- the subject to be analyzed by the business support apparatus 14 may be a corporation (company, organization, etc.).
- the loan destination of the financial institution supported by the business support device 14 is not limited to an individual, and may be a corporation.
- each DB of the personal attribute information source 16 may store the attribute information of the analysis target corporation in association with the corporation number that is a unique number of the corporation assigned to the corporation by a public institution.
- the PC 12 may transmit an analysis request specifying the corporate number of the analysis target corporation to the business support apparatus 14.
- the business support apparatus 14 may collect attribute information of the analysis target corporation from each DB of the personal attribute information source 16 using the corporation number as a key. Then, information that supports the business of the financial institution with respect to the corporation (for example, information on the credit amount or interest rate of the loan to the corporation) may be generated and provided to the PC 12.
- a seventh modification will be described. What is used to collect various attribute information of individual customers from an external device is not limited to a personal number. For example, a credit card number may be used. Moreover, you may use ID which identifies the user linked between several providers by SAML (Security
- SAML Security
- Each DB included in the personal attribute information source 16 replaces and stores attribute information related to an individual with a personal number assigned to the individual, and a personal credit card number or an ID for identifying the user. You may memorize
- the personal attribute acquisition unit 50 of the business support apparatus 14 uses an ID (hereinafter referred to as a “personal ID”) for identifying an individual to be analyzed, including a personal number, a credit card number, and an ID for identifying the user. And the plurality of types of attribute information of the individual to be analyzed may be collected directly from each DB of the personal attribute information source 16.
- the personal attribute acquisition unit 50 uses OpenID Connect, personal attribute information source 16 as OpenID Provider, business support device 14 as Relying Party, and attribute information (also referred to as “claim”) of the individual to be analyzed. It may be acquired from the personal attribute information source 16.
- the business support apparatus 14 when the business support apparatus 14 directly collects attribute information from the personal attribute information source 16, among the providers that provide the personal attribute information source 16, the business that is affiliated with the bank A or B in FIG. 5 provides Information for identifying one or more personal attribute information sources 16 may be preset in the business support apparatus 14.
- the setter of this information may be, for example, a loan officer of A bank or B bank.
- a loan officer or the like of Bank A or Bank B hereinafter referred to as “business officer” stores the first information (for example, attribute information name) for identifying the attribute information of the individual to be analyzed and the attribute information.
- the second information for identifying the personal attribute information source 16 to be obtained may be obtained from the individual to be analyzed by e-mail or the like.
- the person in charge of business is collection support information that makes a pair of the first information and the second information, and a plurality of collection support information may be set in the business support device 14.
- a plurality of personal attribute information sources 16 may be specified by an aggregated claim or a distributed claim.
- the business support apparatus 14 causes a terminal used by the individual to be analyzed to display a screen on which a plurality of collection support information pairs of the first information and the second information can be input during a sequence for specifying an OpenID provider. May be.
- the sequence for specifying the above OpenID Provider is as follows: (1) Initiate is transmitted from the terminal of the individual to be analyzed to the business support device 14 (Relying Party), and (2) Authorization Request is sent from the business support device 14 to the terminal of the target individual to be analyzed. It may be transmitted.
- the business support device 14 may acquire one or more collection support information input on the above screen from the terminal of the individual to be analyzed. Based on the one or more collection support information, the business support apparatus 14 requests request parameters “_claim names” (a parameter including a claim name and an acquisition source identifier) and “_claim_sources” (a parameter including an acquisition source identifier and a value). May be set. The business support apparatus 14 may execute an OpenID Connect sequence using any one of the plurality of personal attribute information sources 16 as an OpenID Provider according to the request parameter.
- one attribute information may be divided into a plurality of servers, and each server may store fragment information of one attribute information. Further, one attribute information may be divided after being encrypted.
- the liability information DB 32 may physically include a plurality of servers, and each of the plurality of servers may hold fragment information obtained by dividing a certain individual's debt information.
- the business support device 14 may collect fragment information from a plurality of servers and restore the original attribute information when using personal attribute information.
- both the attribute information provider for example, the customer who is the debtor
- the attribute information provider for example, a financial institution
- the work support apparatus 14 may restore the attribute information.
- the business support apparatus 14 may execute processing such as reference or update of attribute information.
- the business support apparatus 14 may divide the attribute information and distribute and store it as fragment information on a plurality of servers.
- JP 2013-020212 A JP 2013-020313 A, JP 2013-020314 A, JP 2013-120515 A, JP 2013-120516 A, International Publication 2013/65133, International Publication. 2013/80290.
- the personality or personality is reflected in the data, and the trustworthiness of the individual is determined based on a plurality of types of performance data indicating the past achievements of the individual.
- a business support device (a business support device 114 described later) for determining a personal score to be shown is proposed. For example, by providing this personal score, it is possible to support a financial institution, a recruiting company, and the like to accurately evaluate the personal credit.
- the plurality of types of performance data include data indicating an individual's work history, data indicating an individual's educational history, and data indicating a qualification possessed by the individual.
- a target individual from whom a personal score is derived is also referred to as a “target individual”.
- FIG. 6 shows a configuration of the information system 100 according to the second embodiment.
- the information system 100 includes an educational history management device 102, a work history management device 104, a qualification management device 106, a recruiting company device 110, an applicant device 112, and a business support device 114. 6 are connected via a communication network (corresponding to the communication network 18 of the first embodiment) including a LAN, a WAN, the Internet, and a dedicated line.
- a communication network corresponding to the communication network 18 of the first embodiment
- Each device in FIG. 6 may be realized by a single information processing device. Alternatively, it may be realized as a system by cooperation of a plurality of information processing apparatuses such as a PC, a smartphone, an application server, and a database server.
- the educational history management device 102, the work history management device 104, and the qualification management device 106 are data that reflects the ability or character of each of a plurality of individuals, and are information processing devices that manage performance data indicating the performance of each individual.
- the educational history management device 102 stores data indicating the educational background of each of a plurality of individuals.
- the educational history management apparatus 102 may be provided for each educational institution (school or the like).
- the information system 100 may include a plurality of educational history management devices 102 corresponding to a plurality of educational institutions.
- Each educational history management device 102 may store attribute information related to graduates of the self-education institution. For example, the date of enrollment, the date of graduation, the department, etc. may be stored.
- the work history management apparatus 104 stores data indicating the work history of each of a plurality of individuals.
- the work history management device 104 may be provided for each company (in other words, a company) that employs employees.
- the information system 100 may include a plurality of work history management devices 104 corresponding to a plurality of companies.
- Each work history management device 104 may store attribute information regarding employees (including retirees) of the company. For example, you may memorize the date of joining, the date of leaving, the department, position, reward / discipline history, etc.
- the qualification management device 106 stores data related to qualifications acquired by each of a plurality of individuals.
- the qualification management device 106 may be provided for each organization (company / organization, etc., hereinafter referred to as “qualification testing institution”) that conducts qualification examination work.
- the information system 100 may include a plurality of qualification management devices 106 corresponding to a plurality of qualification testing institutions.
- Each qualification management device 106 may store attribute information related to a qualification acquirer or a passer who is managed by the own organization. For example, you may memorize
- the recruiting company device 110 is an information processing apparatus (for example, a PC) provided in a recruiting company (referred to as a “recruiting company”).
- the applicant device 112 is an information processing device (for example, a smartphone) of an applicant who applies for a job offer from a recruiting company. In the second embodiment, this applicant is a target individual whose personal score is derived by the business support apparatus 114.
- the business support device 114 is an information processing device that supports recruitment work in a recruiting company.
- the business support apparatus 114 shares the educational history BC 116a, which is a block chain in which educational data is stored, with the educational history management apparatus 102, in other words, performs distributed management.
- the job support apparatus 114 shares the job history BC 116b, which is a block chain in which job history data is stored, with the job history management apparatus 104.
- the business support apparatus 14 shares the qualification BC 116c, which is a block chain in which qualification data is stored, with the qualification management apparatus 106.
- the job support apparatus 114 may share a single educational background BC 116a with a plurality of educational background management apparatuses 102.
- the business support apparatus 114 may share a single work history BC 116b with a plurality of work history management apparatuses 104.
- the business support apparatus 114 may share a single qualification BC 116c with a plurality of qualification management apparatuses 106.
- the process of registering data in the block chain, the consensus building process for generating a new block, and the like may be realized by a known technique.
- educational data, work history data, and qualification data may be recorded on the block chain as transaction data.
- educational data, work history data, and qualification data may be stored as field data of the smart contract instance.
- FIG. 7 is a block diagram showing a functional configuration of the business support apparatus 114 of FIG.
- the business support apparatus 114 includes a control unit 120, a storage unit 122, and a communication unit 124. These blocks correspond to the control unit 40, the storage unit 42, and the communication unit 44 of FIG.
- the control unit 120 transmits / receives various data to / from the educational history management device 102, the work history management device 104, the qualification management device 106, the recruiting company device 110, and the applicant device 112 via the communication unit 124.
- the storage unit 122 includes a BC data holding unit 126 and an evaluation standard holding unit 128.
- the BC data holding unit 126 stores data of each of the educational background BC 116a, the professional history BC 116b, and the qualification BC 116c.
- the evaluation reference holding unit 128 corresponds to the bank A parameter holding unit 46 and the bank B parameter holding unit 48 of the first embodiment.
- the evaluation criterion holding unit 128 stores evaluation criterion data that is data for deriving a personal score of the target individual.
- the evaluation standard data can be said to be data indicating the degree to which each of the plurality of types of performance data of the target individual, which reflects the ability or character of the target individual, affects the personal score.
- the evaluation reference data may be an algorithm and / or a parameter for reflecting each of a plurality of types of performance data in the personal score.
- the evaluation reference data may be a program including an algorithm and / or a parameter for deriving a personal score from each of a plurality of types of performance data.
- the evaluation standard data may be obtained by adding or subtracting a personal score related to work history when the work history (same academic background and qualification) satisfies a predetermined condition.
- This predetermined condition may include working for a company whose capital is a predetermined amount or more, and may include working for a company whose number of employees is a predetermined value or more.
- a specific example of the evaluation reference data will be described later with reference to FIG.
- the control unit 120 includes a request reception unit 130, a personal attribute acquisition unit 132, a personal score determination unit 134, a resume generation unit 136, and a resume transmission unit 138. Although not shown because it is a known function, the control unit 120 further includes a function for maintaining and managing the educational background BC 116a, the professional history BC 116b, and the qualification BC 116c. For example, the control unit 120 further includes a function of forming an agreement with an external device sharing each block chain.
- the request reception unit 130 is data transmitted from the applicant device 112 and receives data requesting to submit the applicant's resume to the recruiting company (hereinafter also referred to as “resume submission request”).
- the ID of the applicant assigned in advance to the applicant that is, the individual for whom the personal score is derived
- the ID of the applicant may be an ID issued by a predetermined ID issuing entity (for example, the business support device 114), or may be a personal number (so-called my number) assigned to the applicant by the administrative organization.
- the ID of the applicant is held in each of the applicant, the work support device 114, the educational history management device 102 (education institution, etc.), the professional history management device 104 (company, etc.), and the qualification management device 106 (qualification testing organization, etc.).
- the information system 100 may include a plurality of job offer company devices 110.
- the resume submission request may include identification information of the recruiting company to which the resume is submitted.
- the personal attribute acquisition unit 132 acquires a plurality of types of performance data of the target individual managed by the external device.
- the personal attribute acquisition unit 132 extracts the educational history data of the target individual registered in the educational history BC 116 a from the educational history BC 116 a stored in the BC data holding unit 126.
- the personal attribute acquisition unit 132 may retrieve the educational history data of the target individual from the data of the educational background BC 116a using the ID of the target individual specified in the resume submission request as a key.
- the personal attribute acquisition unit 132 extracts the job history data of the target individual registered in the job history BC 116b by the job history management device 104 from the data of the job history BC 116b stored in the BC data holding unit 126. Further, the personal attribute acquisition unit 132 extracts the qualification data of the target individual registered in the qualification BC 116c by the qualification management device 106 from the data of the qualification BC 116c stored in the BC data holding unit 126.
- the educational history management device 102 may register a smart contract instance including the educational data of the target individual as field data in the educational history BC 116a.
- the educational history management apparatus 102 may notify the business support apparatus 114 of the address of the smart contract instance in the educational background BC 116a.
- the business support apparatus 114 may acquire the smart contract instance from the educational background BC 116a based on the address notified from the educational history management apparatus 102, and may acquire the educational data of the target individual from the smart contract instance.
- the personal score determination unit 134 determines a personal score to be given to the target individual based on a plurality of types of performance data acquired by the personal attribute acquisition unit 132 and evaluation criteria stored in advance in the evaluation criterion holding unit 128. .
- FIG. 8 shows examples of performance data, evaluation criteria, and personal scores.
- the information item column to the item 4 column (up to the qualification continuation status column in the case of qualification) indicate performance data
- the score column indicates an individual score
- the remarks column indicates a part of the evaluation criteria.
- the information items of work history data include company name, stock listing, capital, number of employees, date of entry, date of departure, department, job title, reward / discipline history, presence / absence of job change. It is.
- the evaluation criteria may include a combination of a condition and a score adjustment value (added value or subtracted value) for each of a plurality of information items related to work history.
- the evaluation criteria may be “+20 points” for companies listed on the first section of the Tokyo Stock Exchange and “+10 points” for other listed companies.
- the evaluation criteria are “+10 points” if the capital is 1 billion yen or more, “+5 points” if the capital is 500 million yen or more, and “+2 points” if the capital is 100 million yen or more. May be determined.
- the evaluation criteria are “+30 points” when the number of employees is 10,000 or more, “+20 points” when the number of employees is 5,000 or more, and “+10 points” when the number of employees is 1,000 or more. It may be determined.
- the personal score determination unit 134 sets “35 points” as shown in the first line of the work history in FIG. 8 based on the presence / absence of stock listing, capital, and the number of employees set in the work history data. Is calculated. Also, the personal score determination unit 134 calculates “57 points” as the work history score in the personal score.
- the information items of the qualification data include the qualification name, the qualification issuing organization (testing institution), the date of qualification acquisition, and the status of qualification continuity.
- the evaluation criteria may include combinations of ranks of qualifications (also referred to as difficulty levels and weights to individual scores), conditions, and score adjustment values.
- the evaluation criteria may define the certified accountant's rank as “S” and the system audit engineer's rank as “A”. Further, the evaluation criteria may set “+25 points” for the rank S qualification and “+10 points” for the rank A qualification.
- the evaluation criteria are set so that the score is subtracted (“ ⁇ 4 points” in FIG. 8) when there is a qualification of the same system (for example, both information technology qualifications are applied information engineers and system audit engineers) May be.
- the personal score determination unit 134 calculates “38 points” as the qualification score in the personal score.
- the information items of the educational history data include school name (may be classified as university / high school), admission date, department, graduation date, disciplinary history, and expulsion date.
- the evaluation criterion may include a combination of a condition and a score adjustment value for each of a plurality of information items related to educational background.
- the evaluation criteria may be “+37 points” for college graduates, “+7 points” for high school graduates, and “+1 points” for middle school graduates.
- the evaluation criteria may determine a score according to the department of the university, for example, a higher score may be determined for a university department with a higher degree of difficulty in the entrance examination.
- the personal score determination unit 134 calculates “59 points” as the educational score in the personal score.
- the personal score determination unit 134 calculates the personal score of the target individual by collecting the work history score, the qualification score, and the educational history score of the target individual.
- the total value of the work history score, the qualification score, and the educational history score is directly used as the individual score of the target individual (the total number “154 points” in FIG. 8).
- the evaluation criterion may include weights assigned in advance to each of the work history score, the qualification score, and the educational history score, and the personal score determination unit 134 may calculate the personal score by reflecting the weight. .
- the personal score determination unit 134 calculates the individual score “211 points” by adding up each score after doubling the occupation history score. May be.
- the information system 100 when there are a plurality of recruiting companies, for example, when the information system 100 includes a plurality of recruiting company apparatuses 110 corresponding to the plurality of recruiting companies, a plurality of evaluation criteria determined for each recruiting company are held as evaluation criteria. It may be stored in the unit 128.
- the resume submission request may include the identification information of the recruiting company, and the personal score determination unit 134 calculates the personal score of the target individual according to the evaluation criteria of the recruiting company specified by the identification information. Also good.
- the business support apparatus 114 receives evaluation standard update data from each of the plurality of business support apparatuses 114, and reflects the update data in the existing evaluation standard of the transmission source recruiting company. May be further provided.
- the evaluation criterion setting unit corresponds to the parameter setting unit 62 in the first embodiment.
- the resume generating unit 136 corresponds to the support information generating unit 54 of the first embodiment, and uses the resume data of the target individual as data for supporting the business of the applicant and the recruiting company. Generate.
- the resume generating unit 136 uses the personal history of the target individual acquired by the personal attribute acquiring unit 132, the personal history of the target individual determined by the personal score determining unit 134, and the resume of the target format. Set to data.
- the format of resume data may be specified in the resume submission request.
- the resume generation unit 136 has a format designated in advance by the resume submission company in a plurality of formats, in other words, Then, resume data according to a format previously associated with the recruiting company of the resume submission destination is generated.
- the resume sending unit 138 corresponds to the support information providing unit 60 of the first embodiment, and sends the resume data generated by the resume generating unit 136 to the job offer company apparatus 110.
- the resume sending unit 138 corresponds to the job offer company of the resume submission destination among the plurality of job offer company devices 110.
- the resume data is transmitted to the recruiting company apparatus 110.
- the operation of the information system 100 configured as above will be described.
- Applicants who wish to apply for recruiting companies request online or offline registration of performance data from educational institutions such as school of origin, companies that have worked in the past, or test institutions that have already acquired qualifications.
- the educational institution management apparatus 102 of the educational institution registers the applicant's educational data in the educational BC 116a.
- the company's work history management apparatus 104 registers the applicant's work history data in the work history BC 116b.
- the qualification management device 106 of the test organization registers the qualification data of the applicant in the qualification BC 116c.
- the applicant device 112 transmits a resume submission request to the business support device 114.
- FIG. 9 is a flowchart illustrating the operation of the business support apparatus 114 according to the second embodiment.
- the request accepting unit 130 accepts the resume submission transmitted from the applicant device 112 (Y in S10)
- the personal attribute obtaining unit 132 obtains the applicant's educational history data and professional history from the educational background BC 116a, professional history BC 116b, and qualification BC 116c. Data and qualification data are acquired (S12).
- the personal score determination unit 134 calculates the applicant's personal score based on the applicant's educational history data, work history data, qualification data, and predetermined evaluation criteria (S14).
- the resume generation unit 136 generates applicant resume data including the applicant's educational history data, work history data, qualification data, and personal score (S16).
- the resume sending unit 138 sends the resume data of the applicant to the recruiting company apparatus 110 (S18). If the resume submission request has not been received (N in S10), the processes in and after S12 are skipped, and the flow of this figure is terminated.
- the business support apparatus 114 repeatedly executes the process shown in FIG. 9 as a server process.
- the business support device 114 of the second embodiment using personal performance data not limited to financial assets, it is the creditworthiness of the individual, in other words, the potential of the individual is accurately evaluated. can do.
- the external entity such as a recruiting company, the external entity can be supported so that the individual can be appropriately evaluated.
- the applicant's resume for the recruiting company is automatically created and automatically submitted to the recruiting company, so the burden on the applicant can be reduced.
- personal performance data set in the resume is registered in the block chain by the management organization of the performance data, and the data on the block chain is difficult to falsify. Therefore, the business support apparatus 114 can provide correct result data (work history, educational background, qualification, etc.) regarding the applicant to the recruiting company, and the recruiting company can easily determine whether or not the applicant is employed.
- the individual performance data may include data indicating a result of using the predetermined social networking service (hereinafter referred to as “SNS”) by the individual.
- SNS includes, for example, services such as blogs, miniblogs, and image posting / sharing provided on various websites.
- the information system 100 is an information processing system that provides an SNS, and may further include one or more SNS systems (not shown) corresponding to one or more SNSs.
- the business support apparatus 114 and the SNS system are connected via a predetermined communication network.
- the business support apparatus 114 and the SNS system may share the same block chain, and the SNS system may register individual performance data in the block chain.
- the personal attribute acquisition unit 132 of the business support apparatus 114 may further acquire performance data using the SNS by the target individual from each SNS system.
- This performance data may include statistical information related to posting to the SNS site by the target individual. This statistical information is, for example, the average number of posts in a predetermined period, the posting frequency, and the number of times the posting is supported (or opposed), and may include the so-called like button press count.
- the evaluation standard holding unit 128 of the business support apparatus 114 is an evaluation standard that defines the degree to which the SNS usage record affects the personal score. In other words, the parameter for reflecting the SNS usage record in the personal score is further added. You may remember.
- the personal score determination unit 134 may calculate the personal score of the target individual based on the educational history data, work history data, qualification data, and SNS usage record of the target individual.
- the resume generation unit 136 may generate resume data including academic history data, work history data, qualification data, SNS usage results, and personal scores.
- SNS usage results reflect the individual's ability or character. For example, if the posting frequency is high, it can be estimated that the personality is meticulous and the ability to perform the task is high. Further, if the number of times of support for posting is large, it can be estimated that the person has a personality that easily obtains the sympathy of the other person, and it can be estimated that the ability to obtain the sympathy of the other person is high. Therefore, by calculating the personal score of the target individual based on the SNS usage record, it is possible to generate and provide a personal score that accurately reflects the personal trust and potential.
- the business support device 114 uses an OpenID Connect mechanism for devices (study history management device 102, SNS system, etc.) that provide personal performance data. Actual data may be acquired.
- the personal attribute acquisition unit 132 of the business support device 114 uses the OpenID Connect, the educational history management device 102 / SNS system or the like as the OpenID Provider, the business support device 114 as the Relying Party, and the performance of the target individual. Data may be acquired from the educational history management apparatus 102, the SNS system, or the like.
- the business support apparatus 114 provides the personal score to the recruiting company, but the provision destination of the personal score is not limited to the recruiting company.
- the business support device 114 may be provided to various entities (for example, a financial institution, a recruitment agency, etc.) whose personal trustworthiness and / or personal potential is to be grasped.
- the third embodiment information that supports a financial institution to combine the configuration of the first embodiment and the configuration of the second embodiment and provide a business more suited to the state of each customer. Propose a system. Specifically, the information system of the third embodiment visualizes not only the current situation of the target person but also the past achievements such as educational background, work history, and acquisition qualifications, and future possibilities based on these information Deriving a personal score indicating gender. This supports accurate prediction of how the status (repayment ability, income, etc.) of the target person will increase in the future.
- a financial institution may determine that income will increase rapidly in the future for those who have a high individual score based on educational background, work history, and qualifications, and may lower the lending interest rate and / or raise the upper limit of the amount to be lent. It becomes possible.
- FIG. 10 shows the configuration of the information system 200 according to the third embodiment.
- the same or corresponding elements as those described in the first embodiment or the second embodiment are denoted by the same reference numerals as those in the first embodiment or the second embodiment. Yes.
- the description already described in the first embodiment or the second embodiment will be omitted as appropriate.
- the information system 200 includes the bank A PC 12a described in the first embodiment, the bank B PC 12b (hereinafter collectively referred to as "PC 12"), the personal attribute information source 16, and the educational background described in the second embodiment.
- a management apparatus 102, a work history management apparatus 104, and a qualification management apparatus 106 are provided, and a business support apparatus 114 connected to these apparatuses via a communication network is further provided. Similar to the second embodiment, the job support apparatus 114 shares the educational history BC 116a, the professional history BC 116b, and the qualified BC 116c with the educational history management device 102, the professional history management device 104, and the qualification management device 106.
- FIG. 11 is a block diagram showing a functional configuration of the business support apparatus 114 of FIG.
- the business support apparatus 114 includes a control unit 120, a storage unit 122, and a communication unit 124.
- the control unit 120 transmits / receives various data to / from the PC 12, the personal attribute information source 16, the educational history management device 102, the work history management device 104, and the qualification management device 106 via the communication unit 124.
- the storage unit 122 includes a BC data holding unit 126, a bank A evaluation standard holding unit 140, and a bank B evaluation standard holding unit 142.
- the bank A evaluation criterion holding unit 140 corresponds to the bank A parameter holding unit 46 of the first embodiment, and stores evaluation criteria (parameters of the first embodiment) predetermined by the bank A.
- the bank B evaluation standard holding unit 142 corresponds to the bank B parameter holding unit 48 of the first embodiment.
- the control unit 120 includes a request reception unit 130, a personal attribute acquisition unit 132, a personal score determination unit 134, a support information generation unit 54 (credit amount determination unit 56, interest rate determination unit 58), a support information provision unit 60, an evaluation criterion setting unit. 144.
- the evaluation criterion setting unit 144 corresponds to the parameter setting unit 62 of the first embodiment.
- the evaluation standard setting unit 144 updates the evaluation standard of the bank A according to the update data transmitted from the PC 12a, and updates the evaluation standard of the bank B according to the update data transmitted from the PC 12b.
- the personal attribute acquisition unit 132 is attribute information associated with the personal number of the search key from each DB included in the personal attribute information source 16 and acquires, for example, asset information, debt information, and income information related to the target individual. In addition, the personal attribute acquisition unit 132 acquires educational history data, professional history data, and qualification data from the educational history BC 116a, professional history BC 116b, and qualification BC 116c.
- the personal score determination unit 134 determines the first personal score related to the target individual based on the asset information, the debt information, and the income information acquired by the personal attribute acquisition unit 132. To do.
- the first individual score is the credit amount adjustment score and the interest rate adjustment score in the first embodiment, and these are also collectively referred to as “financial asset individual score”.
- the personal score determination unit 134 uses the second personal score related to the target individual based on the educational history data, work history data, and qualification data acquired by the personal attribute acquisition unit 132. (Referred to herein as the “non-financial asset personal score”).
- the support information generation unit 54 (credit amount determination unit 56 and interest rate determination unit 58), based on both the financial asset individual score and the non-financial asset individual score determined by the individual score determination unit 134, the financial institution of the target individual. Generate information to support business.
- the bank A evaluation standard holding unit 140 has data (hereinafter also referred to as “financing condition adjustment data”) for adjusting the interest rate and the loanable amount based on the personal score of the non-financial asset, which is predetermined by the bank A. Further stored.
- the bank B evaluation standard holding unit 142 stores loan condition adjustment data predetermined by the bank B.
- FIG. 12 shows an example of loan condition adjustment data.
- there are multiple ranges for the non-financial asset personal score and each of the multiple ranges has an interest rate adjustment value (subtracted value in the embodiment) and a loanable amount adjustment value (added in the embodiment). Value).
- the credit amount determination unit 56 first determines the lent amount based on the individual financial asset score, as in the first embodiment.
- the credit amount determining unit 56 determines the final lent amount for the target individual by adjusting the lent amount based on the lent amount adjustment value corresponding to the non-financial asset individual score.
- the interest rate determination unit 58 first determines the interest rate of the loan based on the financial asset individual score.
- the interest rate determination unit 58 determines the final interest rate for the target individual by adjusting the interest rate based on the interest rate adjustment value corresponding to the non-financial asset individual score.
- the interest rate based on the financial asset individual score is “1.05%” and the lent amount is “40 million yen”.
- the non-financial asset individual score of the loan target individual is calculated as “154 points”.
- the individual score of the non-financial asset is associated with the interest rate adjustment value “0.03%” and the loanable amount adjustment value “8 million yen”.
- the credit amount determination unit 56 may increase the final rentable amount to the loan target individual to “48 million yen”.
- the interest rate determination unit 58 may reduce the final lending interest rate to the loan target individual to “1.02”.
- the operation of the business support apparatus 114 according to the third embodiment is the same as the operation of the business support apparatus 14 according to the first embodiment, and mainly differs from the operation according to the first embodiment in the following. explain.
- the request receiving unit 130 of the business support apparatus 114 receives the analysis request transmitted from the PC 12a
- the personal attribute acquisition unit 132 of the business support apparatus 114 receives the analysis target individual from the plurality of DBs included in the personal attribute information source 16. Get multiple types of attribute information about.
- the personal attribute acquisition unit 132 acquires a plurality of types of performance data related to the analysis target person from the block chain.
- the personal score determination unit 134 of the business support apparatus 114 calculates both the financial asset personal score and the non-financial asset personal score.
- the support information generation unit 54 determines the rentable amount and the interest rate for the individual to be analyzed based on both the financial asset individual score and the non-financial asset individual score. Thereafter, the operation is the same as that of the first embodiment, and the support information generating unit 54 generates web page data of business support information indicating the credit amount and the interest rate of the loan for the individual to be analyzed, and the support information providing unit 60 The web page data is transmitted to the PC 12a and displayed.
- the status of the loan target person (for example, repayment ability, income, etc.) is accurately reflected based on the actual data reflecting the ability or character of the loan target individual.
- the non-financial asset personal score can be calculated.
- the appropriate credit amount and interest rate for each individual according to the asset holding state, the debt holding state, and the income situation for each individual are calculated, and , The credit amount and interest rate are adjusted by the non-financial asset personal score. As a result, a more appropriate credit amount and interest rate for each individual can be calculated and presented to the financial institution.
- This invention can be applied to an information processing apparatus that supports evaluation of an individual.
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Computer Security & Cryptography (AREA)
- General Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Strategic Management (AREA)
- Technology Law (AREA)
- Physics & Mathematics (AREA)
- Economics (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- Computer Hardware Design (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
- Debugging And Monitoring (AREA)
Abstract
Description
既述したように、これまで、金融機関から顧客への融資の金利は、金融機関側の要因で決定されてきた。本発明者は、ローンの多様化や、証券資産の拡大等が見込まれる今後、顧客各々が保有する資産の状態に応じて柔軟に金利を調整することが金融機関にとって重要になると考えた。
分析対象個人向けの与信額 = 基準与信額×担保情報レート×年金レート×保有株式レート×勤務企業ランクレート×勤続年数レート×役職レート×負債レート×収入レート
この計算式の場合、個人スコア決定部52は、分析対象個人向けの与信額を基準与信額より小さくする場合に「0<レート<1」とし、分析対象個人向けの与信額を基準与信額以上とする場合に「1≦レート」となるように各属性情報のスコアを決定する。なお、複数種類の与信額調整スコアの乗算結果が上記範囲になるよう決定してもよい。
分析対象個人向けの金利 = 基準与信額×担保情報レート×年金レート×保有株式レート×勤務企業ランクレート×勤続年数レート×役職レート×負債レート×収入レート
この計算式の場合、個人スコア決定部52は、分析対象個人向けの金利を基準金利より割引く場合に「0<レート<1」とし、分析対象個人向けの金利を基準金利以上とする場合に「1≦レート」となるように各属性情報のスコアを決定する。なお、複数種類の金利調整スコアの乗算結果が上記範囲になるよう決定してもよい。
特開2013-020312号公報、特開2013-020313号公報、特開2013-020314号公報、特開2013-120515号公報、特開2013-120516号公報、国際公開第2013/65133号、国際公開第2013/80290号。
融資に限らず様々な企業活動や社会活動において、或る個人がどれだけ信用に足る人かを把握したい場面がある。或る個人が現在保有している金融資産の額だけで、その人のポテンシャルを評価することは難しく、例えば、その人の将来に亘る収入の伸びを予測することは難しい。
求人企業へ応募しようとする応募者は、出身校等の教育機関、過去勤務した会社、取得済の資格の試験機関に対して、オンラインまたはオフラインにて実績データの登録を依頼する。上記教育機関の学歴管理装置102は、応募者の学歴データを学歴BC116aに登録する。上記会社の職歴管理装置104は、応募者の職歴データを職歴BC116bに登録する。上記試験機関の資格管理装置106は、応募者の資格データを資格BC116cに登録する。応募者の操作に応じて、応募者装置112は、履歴書提出要求を業務支援装置114へ送信する。
まず概要を説明する。金融機関における現在の与信審査では、勤務会社、勤続年数、年収といった、対象者の現在のステータスに基づいて信用供与の可否が判断されている。しかし、対象者の現在のステータスだけでは、その対象者が、現在のステータスに到達するまでにどのような学歴・職歴であったか、また、どのような資格を保有し、どのような分野の能力があるか、といった人としての経歴を知ることは困難である。
業務支援装置114の要求受付部130が、PC12aから送信された分析要求を受信すると、業務支援装置114の個人属性取得部132は、個人属性情報ソース16に含まれる複数のDBから、分析対象個人に関する複数種類の属性情報を取得する。それとともに、個人属性取得部132は、分析対象個人に関する複数種類の実績データをブロックチェーンから取得する。
Claims (8)
- 個人の能力または性格が反映されたデータであって、前記個人が過去成し遂げた実績を示す複数種類の実績データを取得する取得部と、
前記取得部により取得された複数種類の実績データに基づいて、前記個人の信用の高さを示す個人スコアを決定するスコア決定部と、
を備えることを特徴とする情報処理装置。 - 前記個人は、企業の求人への応募者であり、
前記スコア決定部により決定された前記応募者の個人スコアを前記企業へ提供する提供部をさらに備えることを特徴とする請求項1に記載の情報処理装置。 - 前記複数種類の実績データは、前記個人の職歴を示すデータ、前記個人の学歴を示すデータ、前記個人が取得した資格を示すデータのうち少なくとも1つを含むことを特徴とする請求項1または2に記載の情報処理装置。
- 前記複数種類の実績データは、所定のソーシャル・ネットワーキング・サービスを前記個人が利用した実績を示すデータを含むことを特徴とする請求項1から3のいずれかに記載の情報処理装置。
- 前記個人によるこれまでの実績を管理する外部装置であって、本情報処理装置とブロックチェーンを共有する外部装置が、前記ブロックチェーンに前記実績データを登録し、
前記取得部は、前記ブロックチェーンに登録された前記実績データを取得することを特徴とする請求項1から4のいずれかに記載の情報処理装置。 - 前記スコア決定部により決定された前記個人スコアに基づいて、前記個人に対する金融機関の業務を支援するための情報を生成する支援情報生成部をさらに備えることを特徴とする請求項1から5のいずれかに記載の情報処理装置。
- 個人の能力または性格が反映されたデータであって、前記個人が過去成し遂げた実績を示す複数種類の実績データを取得するステップと、
前記取得するステップで取得された複数種類の実績データに基づいて、前記個人の信用の高さを示す個人スコアを決定するステップと、
をコンピュータが実行することを特徴とする情報処理方法。 - 個人の能力または性格が反映されたデータであって、前記個人が過去成し遂げた実績を示す複数種類の実績データを取得する機能と、
前記取得するステップで取得された複数種類の実績データに基づいて、前記個人の信用の高さを示す個人スコアを決定する機能と、
をコンピュータに実現させるためのコンピュータプログラム。
Priority Applications (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201780083183.XA CN110192217A (zh) | 2016-02-18 | 2017-07-26 | 信息处理装置、信息处理方法以及计算机程序 |
CA3039894A CA3039894A1 (en) | 2016-02-18 | 2017-07-26 | Information processing apparatus, method, and computer program for assessing performance record data of an individual |
JP2019500177A JP6771085B2 (ja) | 2016-02-18 | 2017-07-26 | 情報処理装置、情報処理方法およびコンピュータプログラム |
US16/369,940 US20190295164A1 (en) | 2016-02-18 | 2019-03-29 | Information processing apparatus, information processing method, and recording medium |
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
PCT/JP2016/054702 WO2017141398A1 (ja) | 2016-02-18 | 2016-02-18 | 情報処理装置、情報処理方法およびコンピュータプログラム |
JPPCT/JP2017/005321 | 2017-02-14 | ||
PCT/JP2017/005321 WO2017141905A1 (ja) | 2016-02-18 | 2017-02-14 | 情報処理装置、情報処理方法およびコンピュータプログラム |
Related Child Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US16/369,940 Continuation US20190295164A1 (en) | 2016-02-18 | 2019-03-29 | Information processing apparatus, information processing method, and recording medium |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2018150606A1 true WO2018150606A1 (ja) | 2018-08-23 |
Family
ID=59624903
Family Applications (3)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/JP2016/054702 WO2017141398A1 (ja) | 2016-02-18 | 2016-02-18 | 情報処理装置、情報処理方法およびコンピュータプログラム |
PCT/JP2017/005321 WO2017141905A1 (ja) | 2016-02-18 | 2017-02-14 | 情報処理装置、情報処理方法およびコンピュータプログラム |
PCT/JP2017/027037 WO2018150606A1 (ja) | 2016-02-18 | 2017-07-26 | 情報処理装置、情報処理方法およびコンピュータプログラム |
Family Applications Before (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/JP2016/054702 WO2017141398A1 (ja) | 2016-02-18 | 2016-02-18 | 情報処理装置、情報処理方法およびコンピュータプログラム |
PCT/JP2017/005321 WO2017141905A1 (ja) | 2016-02-18 | 2017-02-14 | 情報処理装置、情報処理方法およびコンピュータプログラム |
Country Status (5)
Country | Link |
---|---|
US (2) | US20190005577A1 (ja) |
JP (2) | JP6503509B2 (ja) |
CN (1) | CN110192217A (ja) |
CA (9) | CA3014398A1 (ja) |
WO (3) | WO2017141398A1 (ja) |
Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2020080079A (ja) * | 2018-11-14 | 2020-05-28 | 富士通フロンテック株式会社 | 与信情報付与システム |
JP6713588B1 (ja) * | 2019-02-06 | 2020-06-24 | パーソルキャリア株式会社 | ブロックチェーンを活用した人材マッチングシステム、人材マッチング方法、及び人材マッチング業務管理装置 |
JP2020522033A (ja) * | 2019-03-06 | 2020-07-27 | アリババ・グループ・ホールディング・リミテッドAlibaba Group Holding Limited | ブロックチェーンネットワーク内のスマートコントラクトを使用した所帯スコアの管理 |
WO2020152842A1 (ja) * | 2019-01-25 | 2020-07-30 | 光伸 廣瀬 | 分散型台帳履歴書判定システム、分散型台帳履歴書判定方法及びプログラム |
WO2020161929A1 (ja) * | 2019-02-06 | 2020-08-13 | パーソルキャリア株式会社 | ブロックチェーンを活用した人材マッチングシステム、人材マッチング方法、及び人材マッチング業務管理装置 |
JP2021002170A (ja) * | 2019-06-20 | 2021-01-07 | 株式会社メルカリ | 情報処理方法、情報処理装置、及びプログラム |
WO2022009388A1 (ja) * | 2020-07-09 | 2022-01-13 | 富士通株式会社 | 情報処理システムおよび制御方法 |
JP7411946B1 (ja) | 2023-01-16 | 2024-01-12 | Institution for a Global Society株式会社 | 情報処理システム |
Families Citing this family (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
SG11202008561QA (en) * | 2018-03-07 | 2020-10-29 | Hitachi Ltd | Prediction task assistance apparatus and prediction task assistance method |
JP6490271B1 (ja) * | 2018-03-15 | 2019-03-27 | ヤフー株式会社 | 情報処理装置、情報処理方法及び情報処理プログラム |
US20190333030A1 (en) * | 2018-04-30 | 2019-10-31 | Bank Of America Corporation | Blockchain-based digital token utilization |
JP7164333B2 (ja) * | 2018-06-27 | 2022-11-01 | 株式会社日立製作所 | 個人情報分析システム |
JP6803423B2 (ja) * | 2019-03-15 | 2020-12-23 | セカンドサイト株式会社 | モデル構築システム、情報処理システムおよびプログラム |
JP7059415B1 (ja) | 2021-03-08 | 2022-04-25 | PayPay株式会社 | 情報処理装置、情報処理方法及び情報処理プログラム |
CN113744067A (zh) * | 2021-09-03 | 2021-12-03 | 泰康保险集团股份有限公司 | 基于区块链的业绩基准调整方法、区块链系统及存储介质 |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2004094759A (ja) * | 2002-09-03 | 2004-03-25 | Dainippon Printing Co Ltd | マッチング管理システム、情報提供サーバ、情報管理サーバ、記憶媒体、及び、プログラム |
JP2014206792A (ja) * | 2013-04-10 | 2014-10-30 | テンソル・コンサルティング株式会社 | ソーシャルネットワーク情報処理装置、処理方法、および処理プログラム |
WO2017010455A1 (ja) * | 2015-07-13 | 2017-01-19 | 日本電信電話株式会社 | 契約合意方法、合意検証方法、契約合意システム、合意検証装置、契約合意装置、契約合意プログラム及び合意検証プログラム |
US20170018030A1 (en) * | 2015-07-17 | 2017-01-19 | MB Technology Partners Ltd. | System and Method for Determining Credit Worthiness of a User |
Family Cites Families (24)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7031936B2 (en) * | 1999-12-30 | 2006-04-18 | Ge Capital Commerical Finance, Inc. | Methods and systems for automated inferred valuation of credit scoring |
JP2002288426A (ja) * | 2001-03-26 | 2002-10-04 | Fukui Ginko Ltd | 住宅ローン自動審査管理システム |
JP2003242350A (ja) * | 2002-02-19 | 2003-08-29 | Ufj Bank Ltd | 住宅ローン審査システム、方法及びプログラム |
JP3714468B2 (ja) * | 2002-02-22 | 2005-11-09 | 株式会社八十二銀行 | 資産査定支援システム、方法及びプログラム |
US20080040259A1 (en) * | 2006-03-01 | 2008-02-14 | Sheffield Financial Llc | Systems, Methods and Computer-Readable Media for Automated Loan Processing |
JP5294691B2 (ja) * | 2007-06-26 | 2013-09-18 | スルガ銀行株式会社 | 不動産融資における諾否判断装置 |
US10592989B2 (en) * | 2007-10-24 | 2020-03-17 | Joseph D. Koziol | Insurance transaction system and method |
US8744946B2 (en) * | 2008-06-09 | 2014-06-03 | Quest Growth Partners, Llc | Systems and methods for credit worthiness scoring and loan facilitation |
US8452681B2 (en) * | 2009-02-13 | 2013-05-28 | Thomson Financial, LLC | System and method for improved rating and modeling of asset backed securities |
CN101937541A (zh) * | 2009-06-30 | 2011-01-05 | 商文彬 | 一种用于评价客户信用度的方法及设备 |
CN102117469A (zh) * | 2011-01-18 | 2011-07-06 | 中国工商银行股份有限公司 | 一种对信用风险进行评估的系统和方法 |
US20130262175A1 (en) * | 2012-03-29 | 2013-10-03 | Infosys Limited | Ranking of jobs and job applicants |
AU2013221926A1 (en) * | 2012-08-28 | 2014-03-20 | Clearmatch Holdings (Singapore) PTE. LTD. | Methods and systems for consumer lending |
US20140310151A1 (en) * | 2013-04-15 | 2014-10-16 | Rawllin International Inc. | Management of a line of credit or finance-related offer |
US10032218B1 (en) * | 2013-10-16 | 2018-07-24 | Wells Fargo Bank, N.A. | Customized lending product system and method |
JP6236281B2 (ja) * | 2013-10-18 | 2017-11-22 | 株式会社野村総合研究所 | 個人番号管理装置および個人番号管理方法 |
US20160267586A1 (en) * | 2015-03-09 | 2016-09-15 | Tata Consultancy Services Limited | Methods and devices for computing optimized credit scores |
US20160323247A1 (en) * | 2015-04-30 | 2016-11-03 | Adam Stein | Systems and methods for anonymously obtaining data |
BR112018007449B1 (pt) * | 2015-10-17 | 2024-02-20 | Banqu, Inc | Dispositivo de computação, método implementado por computador e dispositivo de memória legível por computador |
CN105260933A (zh) * | 2015-11-10 | 2016-01-20 | 魏楠 | 一种普惠金融的贷款评估方法 |
US20170161855A1 (en) * | 2015-12-08 | 2017-06-08 | C2C Solutions, Inc. | Optimized small screen device to display visual elements in a real property dashboard involving predictive analytics |
CN105761143B (zh) * | 2016-02-01 | 2019-04-05 | 上海凭安网络科技有限公司 | 一种基于区块链的多方共建信用记录的方法 |
CN106230808A (zh) * | 2016-07-28 | 2016-12-14 | 杭州云象网络技术有限公司 | 一种基于区块链技术的个人征信系统建设方法 |
CN106296389A (zh) * | 2016-07-28 | 2017-01-04 | 联动优势科技有限公司 | 一种用户信用度的评估方法及装置 |
-
2016
- 2016-02-18 CA CA3014398A patent/CA3014398A1/en active Pending
- 2016-02-18 WO PCT/JP2016/054702 patent/WO2017141398A1/ja active Application Filing
-
2017
- 2017-02-14 CA CA3026291A patent/CA3026291C/en active Active
- 2017-02-14 JP JP2018500120A patent/JP6503509B2/ja active Active
- 2017-02-14 WO PCT/JP2017/005321 patent/WO2017141905A1/ja active Application Filing
- 2017-02-14 CA CA3081076A patent/CA3081076C/en active Active
- 2017-02-14 CA CA3176778A patent/CA3176778C/en active Active
- 2017-02-14 CA CA3081079A patent/CA3081079A1/en active Pending
- 2017-02-14 CA CA3137858A patent/CA3137858A1/en active Pending
- 2017-02-14 CA CA3181759A patent/CA3181759A1/en active Pending
- 2017-02-14 CA CA3102678A patent/CA3102678C/en active Active
- 2017-07-26 WO PCT/JP2017/027037 patent/WO2018150606A1/ja active Application Filing
- 2017-07-26 CA CA3039894A patent/CA3039894A1/en active Pending
- 2017-07-26 CN CN201780083183.XA patent/CN110192217A/zh not_active Withdrawn
- 2017-07-26 JP JP2019500177A patent/JP6771085B2/ja active Active
-
2018
- 2018-08-17 US US16/104,643 patent/US20190005577A1/en not_active Abandoned
-
2019
- 2019-03-29 US US16/369,940 patent/US20190295164A1/en not_active Abandoned
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2004094759A (ja) * | 2002-09-03 | 2004-03-25 | Dainippon Printing Co Ltd | マッチング管理システム、情報提供サーバ、情報管理サーバ、記憶媒体、及び、プログラム |
JP2014206792A (ja) * | 2013-04-10 | 2014-10-30 | テンソル・コンサルティング株式会社 | ソーシャルネットワーク情報処理装置、処理方法、および処理プログラム |
WO2017010455A1 (ja) * | 2015-07-13 | 2017-01-19 | 日本電信電話株式会社 | 契約合意方法、合意検証方法、契約合意システム、合意検証装置、契約合意装置、契約合意プログラム及び合意検証プログラム |
US20170018030A1 (en) * | 2015-07-17 | 2017-01-19 | MB Technology Partners Ltd. | System and Method for Determining Credit Worthiness of a User |
Cited By (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2020080079A (ja) * | 2018-11-14 | 2020-05-28 | 富士通フロンテック株式会社 | 与信情報付与システム |
WO2020152842A1 (ja) * | 2019-01-25 | 2020-07-30 | 光伸 廣瀬 | 分散型台帳履歴書判定システム、分散型台帳履歴書判定方法及びプログラム |
JP6713588B1 (ja) * | 2019-02-06 | 2020-06-24 | パーソルキャリア株式会社 | ブロックチェーンを活用した人材マッチングシステム、人材マッチング方法、及び人材マッチング業務管理装置 |
WO2020161929A1 (ja) * | 2019-02-06 | 2020-08-13 | パーソルキャリア株式会社 | ブロックチェーンを活用した人材マッチングシステム、人材マッチング方法、及び人材マッチング業務管理装置 |
JP2020522033A (ja) * | 2019-03-06 | 2020-07-27 | アリババ・グループ・ホールディング・リミテッドAlibaba Group Holding Limited | ブロックチェーンネットワーク内のスマートコントラクトを使用した所帯スコアの管理 |
US10984492B2 (en) | 2019-03-06 | 2021-04-20 | Advanced New Technologies Co., Ltd. | Managing housing scores using smart contracts in blockchain networks |
JP2021002170A (ja) * | 2019-06-20 | 2021-01-07 | 株式会社メルカリ | 情報処理方法、情報処理装置、及びプログラム |
WO2022009388A1 (ja) * | 2020-07-09 | 2022-01-13 | 富士通株式会社 | 情報処理システムおよび制御方法 |
JP7411946B1 (ja) | 2023-01-16 | 2024-01-12 | Institution for a Global Society株式会社 | 情報処理システム |
Also Published As
Publication number | Publication date |
---|---|
CA3039894A1 (en) | 2018-08-23 |
JPWO2017141905A1 (ja) | 2018-10-18 |
CA3102678C (en) | 2021-12-21 |
CA3081076A1 (en) | 2017-08-24 |
WO2017141398A1 (ja) | 2017-08-24 |
CA3176778C (en) | 2023-09-19 |
CA3181759A1 (en) | 2017-08-24 |
WO2017141905A1 (ja) | 2017-08-24 |
JP6771085B2 (ja) | 2020-10-21 |
US20190295164A1 (en) | 2019-09-26 |
CA3081076C (en) | 2023-08-15 |
CA3102678A1 (en) | 2017-08-24 |
CA3081079A1 (en) | 2017-08-24 |
JPWO2018150606A1 (ja) | 2019-11-07 |
JP6503509B2 (ja) | 2019-04-17 |
CN110192217A (zh) | 2019-08-30 |
CA3014398A1 (en) | 2017-08-24 |
CA3026291C (en) | 2022-12-06 |
US20190005577A1 (en) | 2019-01-03 |
CA3176778A1 (en) | 2017-08-24 |
CA3137858A1 (en) | 2017-08-24 |
CA3026291A1 (en) | 2017-08-24 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
JP6771085B2 (ja) | 情報処理装置、情報処理方法およびコンピュータプログラム | |
Sethi et al. | Enhancing the role and effectiveness of corporate social responsibility (CSR) reports: The missing element of content verification and integrity assurance | |
Dorfleitner et al. | From credit risk to social impact: On the funding determinants in interest-free peer-to-peer lending | |
Chen et al. | Optimal board monitoring in family‐owned companies: Evidence from Asia | |
Anshari et al. | Financial technology with AI-enabled and ethical challenges | |
AU2017210311A1 (en) | Systems and methods for managing a talent based exchange | |
US20150088564A1 (en) | Engine, system and method of providing cloud-based business valuation and associated services | |
Michael et al. | Audit data analytics of unregulated voluntary disclosures and auditing expectations gap | |
US20120310798A1 (en) | Engine, system and method of providing cloud-based business valuation and associated services | |
KR100902164B1 (ko) | 인터넷을 이용한 부동산 담보대출 계약 중개 방법 | |
Asnakew et al. | Valuation inaccuracy, approaches, basis and procedures for judgment execution in Ethiopia | |
Dressler et al. | Doing the right thing? The voting power effect and institutional shareholder voting | |
Chahine et al. | The role of auditors in merger and acquisition completion time | |
TWI814707B (zh) | 有助於金融交易之方法和系統 | |
Matytsin | Concept and types of distance digital investment transactions in the information space | |
Harper et al. | Managerial ability and bond rating changes | |
Smondel | SMEs’ soft information and credit rationing in France | |
Elouaourti et al. | Unveiling the drivers of Africa's digital financial inclusion journey | |
Li et al. | Voluntary verifiable information disclosure and loan funding performance: Evidence from Paipaidai in China | |
Greene et al. | When do CEOs delegate authority? Evidence from mergers and acquisitions | |
US20120310797A1 (en) | Engine, system and method of providing cloud-based business verification and associated services | |
Olsen | Beyond the hype: Exploring blockchain Technology in Land Administration | |
King | The Relationship between Fair Value Accounting Experience and Professional Skepticism among Auditors | |
Weihs | Online Peer-to-Peer Lending as an Alternative to Traditional Lending for Small Business Financing | |
Win | CUSTOMER ADOPTION OF INTERNET BANKING SERVICES IN MAB BANK |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 17896361 Country of ref document: EP Kind code of ref document: A1 |
|
ENP | Entry into the national phase |
Ref document number: 3039894 Country of ref document: CA |
|
ENP | Entry into the national phase |
Ref document number: 2019500177 Country of ref document: JP Kind code of ref document: A |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 17896361 Country of ref document: EP Kind code of ref document: A1 |