JP5592861B2 - Claim evaluation support system, claim evaluation support method and claim evaluation support program - Google Patents

Description

  The present invention relates to an account management for a claim, specifically, a claim evaluation support system, a claim evaluation support method, and a claim evaluation support program for creating a collection schedule for claims and evaluating the market value of claims.

  Generally, when a financial institution provides a loan, it is necessary to evaluate the risk of the borrower. In this case, for example, the possibility of default (default) due to bankruptcy of the borrower is predicted. Therefore, a system for predicting the bankruptcy probability has been studied (for example, see Patent Documents 1 and 2). In the system described in Patent Document 1, the regression based on the quantification theory 1 is performed on the bankruptcy probability actual value after logit conversion obtained by logit transforming the bankruptcy probability actual value for the category data for each category set. Analysis is performed to calculate a score value for each item category. And for the specified item category, logit value [score category score value + industry category score value + growth rate category score value + interest rate category score value + exchange category score value + price category score value + government category score value + constant ] And the bankruptcy probability is calculated using a predetermined function formula.

  In the system described in Patent Document 2, credit risk evaluation is performed by reflecting changes in the business environment of the target company. Specifically, the credit risk evaluation server acquires the company information of the evaluation target company and the predicted number of bankruptcies of the group of companies to which the evaluation target company belongs, and determines the credit risk based on the acquired company information and the predicted number of bankruptcies. .

  In addition, financial institutions manage individual scheduled repayment cash flows for loan receivables (credit receivables) such as housing loans and corporate loans. A system for predicting the future of cash flow reflecting the advance payment risk, default risk, and delinquency risk of such loan receivables is also being studied (for example, see Patent Document 3). In the technique described in Patent Document 3, the cause of the result data is analyzed based on the past result cash flow. Based on the analysis processing result, the uncollectible rate in each repayment year “i” for each credit type and the repayment time change probability that the actual payment becomes “i” year from the repayment scheduled year “j” are obtained. In addition, based on the uncollectible rate and the repayment time change probability, the future cash flow for every bond or bond type is predicted.

JP 2008-250466 A (first page, FIG. 1) JP 2002-279174 A (first page, FIG. 1) Japanese Unexamined Patent Publication No. 2003-141356 (first page, FIG. 1)

  As described above, credit receivables also have a default risk that makes them uncollectible due to default. In addition, due to prepayment, the planned future cash flow may differ. Furthermore, various credit products are often provided such as cashing revolving payment, shopping bonus payment, shopping installment payment, and shopping revolving payment. In this case, there are cases where a plurality of credit products are used and there are cases where the user group varies depending on the credit products, and it is difficult to collectively evaluate the default risk and the prepayment risk.

  In addition, when introducing international accounting standards, it is necessary to calculate the fair value (market price) of financial assets that do not have market prices. For example, there is a DCF method (Discounted Cash Flow method) as a method for evaluating the market value of a bond. In the DCF method, when a profitable asset is kept, the discounted present value of the cash flow generated by the asset is used as a theoretical price. When calculating this present value, it is necessary to consider the default rate. However, in the past, accurate market value assessment of receivables that correspond to international accounting standards has not been fully studied.

  The present invention has been made to solve the above-mentioned problems, and its object is to provide a claim evaluation support system, a claim evaluation support method, and a claim evaluation support program for accurately performing accounting management of claims. It is in.

In order to solve the above-mentioned problems, the invention described in claim 1 is characterized in that the debtor information storage means that records the debtor's attribute information in association with the debtor identifier, and the recovery risk is associated with the debtor identifier. A depreciable receivable information storage means for recording depreciable receivable information together with information for identifying whether it has occurred, an existing receivable information storage means for recording receivable information with a receivable balance in association with the debtor identifier, and accounting management processing A debt evaluation support system comprising: a control means for executing the control, wherein the control means uses the depreciable claim information storage means to identify a debtor identifier in which a collection risk has occurred, and the debtor information storage means The creditor recorded in the amortized claim information storage means for each of the items included in the attribute information or the item included in the claim information from the means for obtaining the debtor attribute information of the debtor identifier Means for calculating a recovery risk factor with, for said items, said calculating the correlation index for the collection risk ratio, means for identifying an item is correlated in the correlation index for the identified item, receivables To classify item values of individual items
Means for creating a collection risk rate map in which a collection risk rate of a bond is calculated for each elapsed period using information identifying whether or not a collection risk recorded in the amortized bond information storage means has occurred in each map element of And using the claim information of the claim recorded in the existing claim information storage means, calculate the scheduled collection time and the scheduled collection amount, identify the map element to which the claim belongs, and for each map element of the item, In accordance with the scheduled collection time, a collection schedule is created by collecting the scheduled collection amount, and the map element to which the bond belongs is specified using the bond information recorded in the existing bond information storage means, and the map using said recovery plan amounts and collection risk ratio corresponding to the elapsed time in the element, Bei and means for performing accounting processing for calculating a recovery plan amounts considering collection risk And summarized in that it was.

According to a second aspect of the invention, the claims evaluation support system according to claim 1, wherein the recovery plan with recovery expected amount for each harvest time included in the table to calculate the present value, the current for each of the recovery time The gist is to sum the values.

According to a third aspect of the present invention, in the claim evaluation support system according to the first or second aspect , an output unit and an input unit are connected to the control unit, and items having correlation are output from the output unit. The gist is to create a collection risk rate map using the items output to the means and selected using the input means.

According to a fourth aspect of the present invention, in the claim evaluation support system according to any one of the first to third aspects, the depreciable claim information storage means stores claim information associated with product information of a plurality of credit products. When the ratio of the number of obligors who use all credit products of the combination is high with respect to the total number of obligors who use each credit product of the combination in a combination of a plurality of specific credit products. The gist is to collect the credit information of the credit products and create a collection risk rate map.

According to a fifth aspect of the present invention, in the claim evaluation support system according to any one of the first to fourth aspects, the depreciable claim information storage means depreciates each analysis period within each analysis period. The gist of the present invention is to obtain the bond information and calculate a correlation index with the recovery risk rate for the item for each analysis period.

The invention described in claim 6 is the claim evaluation support system according to any one of claims 1 to 5 , further comprising history information storage means for recording a past collection risk rate map, wherein the depreciable claim information storage The collection risk rate recorded in the collection risk rate map is calculated by calculating the collection risk rate results for the map elements included in the collection risk rate map recorded in the history information storage unit using the bond information recorded in the means. And a means for judging whether or not the collection risk rate map can be reused according to the comparison result.

The invention described in claim 7 includes a debtor information storage unit that records the debtor's attribute information in association with the debtor identifier, and information that specifies whether a recovery risk has occurred in association with the debtor identifier. A depreciable receivable information storage means for recording amortized receivable information, a receivable information storage means for recording receivable information with a receivable balance in association with a debtor identifier, and a control means for executing accounting management processing. A method for supporting a loan evaluation using a bond evaluation support system, wherein the control means uses the depreciable bond information storage means to identify a debtor identifier in which a collection risk has occurred, and stores the debtor information Means for acquiring the obligor attribute information of the obligor identifier, and recorded in the depreciable receivable information storage means for each classification of items included in the attribute information or receivable information Calculating a collection risk factor for right for the items, the calculated correlation index between collection risk ratio, the method comprising: identifying an item is correlated in the correlation index for the identified item, receivables In each map element for classifying item values of individual items, information identifying whether or not a collection risk recorded in the amortized bond information storage means has occurred is used to determine the collection risk rate of the bond for each elapsed period. Using the step of creating the calculated collection risk rate map and the claim information of the claim recorded in the existing claim information storage means, the scheduled collection time and the scheduled collection amount are calculated, and the map element to which the claim belongs is specified. , to each map element of the item, the recovery in accordance with the scheduled time, to create a collection schedule obtained by aggregating the recovery plans amount of money, record of the existing credit information storage means By using the receivable information to identify the map elements the receivable belongs, using said the collection risk ratio corresponding to the elapsed time in the map element and the recovery plan amount, calculated recovery plan amounts considering collection risk And performing the accounting management process.

The invention according to claim 8 is a debtor information storage means that records the debtor's attribute information in association with the debtor identifier, and information that specifies whether or not a recovery risk has occurred in association with the debtor identifier. A depreciable receivable information storage means for recording amortized receivable information, a receivable information storage means for recording receivable information with a receivable balance in association with a debtor identifier, and a control means for executing accounting management processing. A program for supporting a loan evaluation using a bond evaluation support system, wherein the control means uses the amortized claim information storage means to identify a debtor identifier in which a collection risk has occurred, and the debtor Means for acquiring attribute information of the debtor identifier from the information storage means, and recorded in the depreciable claim information storage means for each classification of items included in the attribute information or claim information. Means for calculating a collection risk factor for loans, for the items, the correlation index for the collection risk index is calculated, and means for identifying an item is correlated in the correlation index, the the specified items, individual creditors In each map element for classifying item values of items, the collection risk rate of receivables was calculated for each elapsed period using information specifying whether or not the collection risk recorded in the depreciable receivable information storage means occurred Means for creating a collection risk rate map, using the claim information of the claims recorded in the existing claim information storage means, calculating the scheduled collection time and the scheduled collection amount, specifying the map element to which the claim belongs, for each map element of, it said in response to the recovery plan time, to create a collection schedule obtained by aggregating the recovery planned amount, was recorded in the existing credit information storage means Using authority information, the receivables to identify the map element belonging, using said the collection risk ratio corresponding to the elapsed time in the map element and the recovery plan amount, and calculates the recovery plan amounts considering collection risk The gist is to function as a means for performing accounting management processing.

(Function)
According to the invention described in claim 1, 7 , or 8 , the control means uses the amortized claim information storage means to identify the debtor identifier in which the collection risk has occurred, and from the debtor information storage means, Acquires the attribute information of the debtor with the identifier. Next, a recovery risk rate is calculated for the claims recorded in the amortized claim information storage means for each category of items included in the attribute information or the claim information. Next, a correlation index with the recovery risk rate is calculated for the item, a correlation item is identified in the correlation index, and a recovery risk rate map is calculated as a map element of the specified item. create. Then, the accounting management process is performed using the balance of receivables recorded in the existing receivable information storage means and the collection risk rate map. Thereby, it is possible to predict the recovery risk rate based on the attributes of the creditor and the debtor, and to perform more accurate accounting management in consideration of the recovery risk rate.

According to the present invention, in the accounting management process, using the claim information of the claim recorded in the existing claim information storage means, the estimated collection time and the estimated collection amount are calculated, the map element to which the claim belongs is specified, For each map element, a collection schedule table is created in which the collection amount is collected according to the scheduled collection period. Thereby, the collection schedule corresponding to the item which has a correlation with a collection risk rate can be created.

According to the present invention, in the accounting management process, for each map element of the recovery risk rate map, a cash flow composed of the recovery amount and the recovery time is further calculated using the recovery risk rate and the recovery schedule. Thereby, it is possible to calculate a cash flow corresponding to an item having a correlation with the recovery risk rate.

According to the second aspect of the present invention, in the accounting management process, the present value is calculated for each collection period included in the collection schedule using the scheduled collection amount, and the present value for each collection period is summed. Thereby, it is possible to calculate the present value more suitable for the accounting standards in consideration of the item having a correlation with the recovery risk rate.

According to the third aspect of the present invention, the correlated item is output to the output unit, and the collection risk rate map is created using the item selected using the input unit. Thereby, it is possible to create a map in which the recovery risk rate is predicted using items specified by determining that there is a correlation.

According to the invention of claim 4 , in the combination of a plurality of specific credit products, the total number of debtors who use each credit product of the combination is the number of debtors who use all the credit products of the combination. If the ratio is high, collect the credit information of credit products and create a collection risk rate map. Thereby, even when a plurality of credit products are used, it is possible to calculate the recovery risk rate in consideration of the usage status.

According to the invention described in claim 5 , the debt information depreciated within each analysis period is acquired from the amortized claim information storage means for each of the plurality of analysis periods, and the recovery risk rate for each item for each analysis period. A correlation index is calculated. As a result, the correlation can be determined in consideration of different analysis periods, and the account management for the bond can be performed using this correlation.

According to the sixth aspect of the present invention, by using the claim information recorded in the amortized claim information storage means, the recovery risk rate results are calculated for the map elements included in the recovery risk rate map recorded in the history information storage means. To do. Then, the recovery risk rate recorded in the recovery risk rate map is compared with the actual recovery risk rate, and whether or not the recovery risk rate map can be reused is determined according to the comparison result. Thereby, a collection risk rate map can be created efficiently using the past evaluation result.

  According to the present invention, in a credit product, taking into account the risk of collection of receivables, a receivable evaluation support system, a receivable evaluation support method and a receivable evaluation support method for performing accurate accounting management processing such as preparation of a collection schedule and evaluation of the market value of receivables A loan evaluation support program can be provided.

The system schematic of embodiment of this invention. It is explanatory drawing of the information storage part of embodiment of this invention, Comprising: (a) is a user information storage part, (b) is a depreciable loan information storage part, (c) is recorded in the claim information storage part classified by goods Explanatory drawing of data. Explanatory drawing of the process sequence of this embodiment. Explanatory drawing of the process sequence of this embodiment. It is explanatory drawing of the process sequence of this embodiment, Comprising: (a) is a correlation evaluation process, (b) is explanatory drawing of a map creation process. Explanatory drawing of the process sequence of this embodiment. Explanatory drawing of the process sequence of other embodiment. Explanatory drawing of the process sequence of other embodiment. Explanatory drawing of the process sequence of other embodiment. Explanatory drawing of the process sequence of other embodiment.

  Hereinafter, an embodiment embodying the present invention will be described with reference to FIGS. In the present embodiment, a collection schedule is created based on the balance of various credit products, and a credit evaluation support system, a credit evaluation support method, and a credit evaluation support program for evaluating the market value of a bond will be described. In the present embodiment, it is assumed that the market value of a bond is evaluated for a plurality of credit products provided by a company in consideration of collection risk (default or prepayment).

In the present embodiment, as shown in FIG. 1, a client terminal 10 and a bond evaluation support server 20 are connected via a network.
The client terminal 10 is a computer terminal used by a person in charge who manages a bond held by a company. The client terminal 10 includes an output unit (such as a display) and an input unit (such as a keyboard and a pointing device).

  The claim evaluation support server 20 is a computer system for evaluating the balance of claims of each credit product and calculating the market price. As shown in FIG. 1, the claim evaluation support server 20 includes a control unit 21, an original data storage unit 22, a user information storage unit 23, a depreciable bond information storage unit 24, a product-specific bond information storage unit 25, and a collection risk rate map. A storage unit 26, a collection schedule storage unit 27, and an evaluation basic information storage unit 28 are provided.

  Based on an instruction from the client terminal 10, the control unit 21 performs various accounting management processes such as a market value evaluation of the credit for the credit balance of the credit product. The control unit 21 includes a CPU, a RAM, a ROM, and the like as control means, and performs later-described processing (correlation evaluation processing stage, map creation processing stage, collection schedule creation process, market price evaluation processing stage, etc.). Do. By executing the credit evaluation support program for this purpose, the control unit 21, as shown in FIG. 1, the credit information acquisition means 211, evaluation management means 212, correlation evaluation means 213, map creation means 214, schedule table creation It functions as the means 215, the market price calculation means 216, etc.

The bond information acquisition unit 211 executes a process of acquiring a load file from the client terminal 10 and editing it into bond information for performing market value evaluation of the bond.
The evaluation management means 212 executes a process for managing various processes for evaluating the market value of the bond.

  Correlation evaluation means 213 executes processing for evaluating the correlation between users (debtors) of various credit products and individual items included in the contents of claims and default rates and prepayment rates. The correlation evaluation unit 213 includes a memory that temporarily stores individual items having a correlation with the default rate and the prepayment rate as grouping elements.

The map creation means 214 executes a process for creating a map showing the distribution of the default rate and the prepayment rate using the combination of attributes specified based on the correlation.
The schedule table creation means 215 executes processing for creating a credit bond collection schedule table.
The market price calculation means 216 uses the collection schedule table to calculate a cash flow considering the default rate and the prepayment rate, and executes a process of calculating the present value of the bond by a known DCF method.

  The original data storage unit 22 stores original data (load file) used for the market value evaluation of the bond. This load file is recorded when data used for market price evaluation is acquired from the client terminal 10. This load file includes an amortization file and a balance file. The amortization file includes data on receivables that have already been amortized, including receivable codes, user codes, product codes, balances, repayment conditions, amortization status, and amortization date. The contents of this depreciation file are the same as the data recorded in the depreciable bond information storage unit 24 described later.

  In the balance file, for each user of each credit product, user attribute information, product code for specifying the credit product being used, bond code, balance, and data on repayment conditions are recorded.

  The user information storage unit 23 functions as debtor information storage means. In the user information storage unit 23, as shown in FIG. 2A, a user management record 230 is recorded as debtor information regarding the user of each credit product. This user management record 230 is recorded when the load file recorded in the original data storage unit 22 is edited. In the user management record 230, data relating to the user code and attribute information is recorded.

In the user code data area, data relating to an identifier (obligor identifier) for identifying the user (debtor) of each credit product is recorded.
In the attribute information data area, data relating to the user attribute is recorded. In the present embodiment, data relating to age, sex, address (prefecture), score (credibility), and the like is recorded as attribute information.

  The amortized claim information storage unit 24 functions as a depreciable claim information storage unit. As shown in FIG. 2B, the depreciable loan information storage unit 24 records a depreciable loan management record 240 as receivable information that has been depreciated by complete payment, prepayment (prepayment), and credit loss (default). . The depreciable claim management record 240 is recorded when the load file acquired from the client terminal 10 is edited. The amortized claim management record 240 includes data relating to a claim code, a user code, a product code, a contract date, a balance, a repayment condition, a depreciation status, and a depreciation date.

In the bond code data area, data relating to an identifier for specifying each amortized bond is recorded.
In the user code data area, data relating to an identifier for identifying the user (debtor) of the credit product that is the cause of the occurrence of the depreciable loan is recorded.

In the product code data area, data relating to an identifier (product information) for specifying the credit product that is the cause of the occurrence of the depreciable loan is recorded.
In the contract date data area, data relating to the contract time (year / month / day) of the credit product is recorded. The date of occurrence of the claim can be specified by this contract date.

  In the balance data area, data relating to the balance of receivables at the time of amortization is recorded. “0” is recorded in the case of amortization by payment or prepayment, and the default balance is recorded in the case of credit loss.

In the repayment condition data area, data relating to the repayment conditions in the depreciable receivable is recorded. In the present embodiment, data relating to the repayment method, repayment time, and applicable interest rate is recorded.
In the depreciation status data area, a flag for specifying the depreciation status of the bond is recorded. In the present embodiment, a flag that specifies any of payment, prepayment, and default is recorded.
In the amortization date data area, data related to the time (year / month / day) when the bond is amortized is recorded.

  The product-specific claim information storage unit 25 functions as an existing claim information storage unit. As shown in FIG. 2C, the product-specific claim information storage unit 25 records a credit management record 250 as credit information with a credit balance as a target of market value evaluation for each credit product. The bond management record 250 is recorded when the load file recorded in the original data storage unit 22 is edited. The credit management record 250 is recorded in a separate file for each credit product, and data on the credit code, user code, contract date, balance, and repayment conditions is recorded. In FIG. 2C, the claim management records 250 for the products (1) to (n) are recorded separately.

In the bond code data area, data relating to an identifier for specifying each bond for collecting the repayment money is recorded.
In the user code data area, data relating to an identifier for identifying the user (debtor) of the credit product that is the cause of the bond is recorded.
In the contract date data area, data relating to the contract time (year / month / day) of the credit product is recorded.

In the balance data area, data relating to the balance of the bond is recorded.
In the repayment condition data area, data relating to the repayment condition for the bond is recorded. In the present embodiment, data relating to the repayment method, repayment time, and applicable interest rate is recorded.

  The collection risk rate map storage unit 26 stores a default rate map and a prepayment rate map used for the market price evaluation of bonds. This default rate map and prepayment rate map are recorded when a map creation process described later is performed. In this default rate map, the default rate in each map element is recorded using individual items designated for grouping as variables. In addition, the prepayment rate map records the prepayment rate for each map element, with individual items designated for grouping as variables. Here, the default rate map and the prepayment rate map have the elapsed period as a variable, the ratio of defaulting (default rate) and the rate of prepayment (prepayment rate) when a predetermined period elapses from the current time, respectively. Is represented in time series.

  In the collection schedule table storage unit 27, a collection schedule table used for the market price evaluation of the bond is recorded. This collection schedule is recorded when a collection schedule creation process described later is performed. This collection schedule is created for each individual item designated for grouping, and the scheduled collection time and the scheduled collection amount are recorded.

  The basic evaluation information storage unit 28 stores basic information used for the market price evaluation of bonds. This basic information is registered in advance before the execution of each process. In this embodiment, analysis period candidates, risk free rates and risk premiums, correlation reference values, and increments of individual items are recorded as basic information.

  The analysis period candidate is used to extract the amortized claim management record 240 that is the target of the correlation evaluation. In this embodiment, it is also possible to record a plurality of analysis period candidates. Also, in the designation of the period, the designation of the period has been changed, such as “Last 1 year”, “Last 6 months”, or the start and end periods have been changed, such as “Simultaneous 6 months of 1 year ago” You can also specify.

The risk free rate and the risk premium are parameters used in the DCF method.
The correlation reference value is a reference value used for determining whether or not there is a correlation between an individual item and a recovery risk rate. In the present embodiment, the presence / absence of correlation between the individual item and the default rate is evaluated.
The increment of each individual item records a variable range for classifying item values of individual items of receivables, and is used to classify receivables in the correlation evaluation process.

  A processing procedure in the case of performing a market price evaluation on the balance of each credit product using the system configured as described above will be described. In the following, an outline of the processing procedure (FIG. 3), a market price evaluation process (FIG. 4), a correlation evaluation process (FIG. 5A), a map creation process (FIG. 5B), a collection schedule table creation process (FIG. Description will be made in the order of 6).

(Outline of processing procedure)
First, the outline of the processing procedure will be described with reference to FIG.
Here, the control unit 21 of the bond evaluation support server 20 executes a load file registration process (step S1-1). Specifically, when performing market value evaluation of a credit related to a credit product, the person in charge accesses the bond evaluation support server 20 using the client terminal 10. Then, the client terminal 10 transmits an instruction to start the market price evaluation process. In this case, the bond information acquisition unit 211 of the control unit 21 of the bond evaluation support server 20 outputs a request for evaluation target data on the display of the client terminal 10. When the evaluation target data is input to the client terminal 10, the bond information acquisition unit 211 of the control unit 21 acquires the evaluation target data (load file) from the client terminal 10. Then, the bond information acquisition unit 211 registers the acquired load file in the original data storage unit 22.

Next, the control unit 21 of the bond evaluation support server 20 executes a division process for each credit product (step S1-2). Specifically, the bond information acquisition unit 211 of the control unit 21 generates the depreciable bond management record 240 based on the depreciation file of the load file recorded in the original data storage unit 22 and stores it in the depreciable bond information storage unit 24. sign up. Furthermore, the claim information acquisition unit 211 divides the claim information included in the balance file for each credit product. Then, the claim information acquisition unit 211 assigns the user code recorded in the balance file, generates a claim management record 250 for each credit product, and registers it in the product-specific claim information storage unit 25.
Next, the control unit 21 of the bond evaluation support server 20 executes a market price evaluation process to be described later for each credit product (step S1-3).

(Market value processing)
Next, the market price evaluation process will be described with reference to FIG.
First, the control unit 21 of the bond evaluation support server 20 executes analysis period candidate specifying processing (step S2-1). Specifically, the evaluation management unit 212 of the control unit 21 acquires analysis period candidates from the evaluation basic information storage unit 28. Then, in each identified analysis period candidate, the analysis period to be processed is specified, and the following process is repeated.

  Here, the control unit 21 of the bond evaluation support server 20 executes an analysis target extraction process (step S2-2). Specifically, the evaluation management unit 212 of the control unit 21 extracts the depreciable claim management record 240 in which the depreciation date included in the analysis period to be processed is recorded from the depreciable claim information storage unit 24 as an analysis target.

  Next, the control unit 21 of the bond evaluation support server 20 executes a correlation evaluation process (step S2-3). Specifically, the correlation evaluation unit 213 of the control unit 21 executes a correlation evaluation process described later. And the process of said step S2-2 and S2-3 is repeated about all the analysis period candidates.

  When the correlation evaluation process for all analysis period candidates is completed, the control unit 21 of the bond evaluation support server 20 executes a correlation evaluation result output process (step S2-4). Specifically, the evaluation management unit 212 of the control unit 21 outputs a correlation evaluation result screen on the display of the client terminal 10. In this correlation evaluation result screen, for each analysis period candidate, each individual item identified as a grouping element in the correlation evaluation process (an individual item correlated with the default rate) and a calculated correlation coefficient (correlation index) Is displayed.

  Next, the control unit 21 of the bond evaluation support server 20 executes a map creation process (step S2-5). Specifically, the map creation unit 214 of the control unit 21 executes map creation processing described later.

  Next, the control unit 21 of the bond evaluation support server 20 executes a collection schedule table creation process (step S2-6). Specifically, the schedule table creation means 215 of the control unit 21 executes a collection schedule table creation process to be described later.

  Next, the control unit 21 of the bond evaluation support server 20 executes a market price calculation process (step S2-7). Specifically, the market price calculation means 216 of the control unit 21 acquires a risk free rate and a risk premium from the basic evaluation information storage unit 28, and acquires a prepayment rate and a default rate from the collection risk rate map storage unit 26. To do. Here, as will be described later, the prepayment rate and the default rate are grouped by individual items having a correlation with the default rate, and are expressed in a time series corresponding to the elapsed period from the present time. Then, the market price calculation means 216 calculates a cash flow in consideration of the time series prepayment rate and the default rate for the scheduled collection amount recorded in the collection schedule table grouped according to the map element. Specifically, the market price calculation means 216 acquires a prepayment rate and a default rate corresponding to an elapsed period until the scheduled collection time from a default rate map and a prepayment rate map stored in the collection risk rate map storage unit 26. To do. Then, the market price calculation unit 216 calculates a cash flow in consideration of the recovery risk by multiplying the planned recovery amount by a ratio obtained by subtracting the acquired prepayment rate and default rate from “1”. Further, the market price calculation means 216 calculates the present value of the bond by a known DCF method using the cash flow, the risk free rate and the risk premium. Here, the present value of the cash flow corresponding to each collection schedule is summed up. Then, the market price calculation means 216 outputs to the display of the client terminal 10.

(Correlation evaluation process)
Next, the correlation evaluation process will be described with reference to FIG. Here, the individual item used for the collection risk rate map mentioned later is specified by the correlation between the default rate and the user attribute. Specifically, the individual items to be processed are identified in the individual items included in the receivable details (balance, repayment conditions, etc.) and user attributes (age, prefecture, etc.), and the following processing is repeated.

  First, the control unit 21 of the bond evaluation support server 20 executes a default rate calculation process (step S3-1). Specifically, the correlation evaluation means 213 of the control unit 21 acquires the value (item value) of the individual item to be processed in the depreciable claim management record 240 to be analyzed. Here, in the case of an individual item related to the content of a claim, information recorded in the depreciable claim management record 240 is acquired as an item value. Further, in the case of individual items related to user attributes, the user management record 230 is extracted from the user information storage unit 23 using the user code recorded in the depreciable claim management record 240, and the attribute information is stored as the item. Get as a value. Next, the correlation evaluation unit 213 classifies each bond using the increments of the individual items recorded in the evaluation basic information storage unit 28. Then, the correlation evaluation unit 213 counts the total number of receivables and the number of default receivables included in each step, and calculates a default rate obtained by dividing the number of default receivables by the total number of receivables.

  Next, the control unit 21 of the bond evaluation support server 20 executes a correlation coefficient calculation process (step S3-2). Specifically, the correlation evaluation unit 213 of the control unit 21 calculates a correlation coefficient between the individual item and the default rate using a known correlation coefficient calculation function. For prefectures, the correlation coefficient is calculated using the linear distance from Tokyo to the location of the prefectural office.

  Next, the control unit 21 of the bond evaluation support server 20 executes a determination process as to whether or not there is a correlation (step S3-3). Specifically, the correlation evaluation unit 213 of the control unit 21 acquires a correlation reference value from the basic evaluation information storage unit 28. When the calculated absolute value of the correlation coefficient is higher than the correlation reference value, it is determined that there is a correlation.

  When it is determined that there is a correlation (in the case of “YES” in step S3-3), the control unit 21 of the bond evaluation support server 20 executes a grouping element specifying process (step S3-4). Specifically, the correlation evaluation unit 213 of the control unit 21 temporarily stores the individual items in the memory as grouping elements.

  On the other hand, when the correlation coefficient is lower than the correlation reference value and it is determined that there is no correlation (in the case of “NO” in step S3-3), the control unit 21 of the bond evaluation support server 20 Terminates processing for the item. The above process is repeated until all the individual items are completed.

(Map creation process)
Next, a map creation process for the default rate and the prepayment rate will be described with reference to FIG.

  Here, the control unit 21 of the bond evaluation support server 20 executes a grouping designation process (step S4-1). Specifically, the person in charge checks the grouping elements (individual items) included in the correlation evaluation result screen output in step S2-4 using the client terminal 10. In this correlation evaluation result screen, individual items used for grouping for creating a default rate map are designated. In this designation, a plurality of individual items can be selected. When the confirmation input of the individual items to be grouped is performed at the client terminal 10, the map creation unit 214 of the control unit 21 of the claim evaluation support server 20 acquires information on the individual items specified at the client terminal 10. To do.

  Next, the control unit 21 of the bond evaluation support server 20 executes map element generation processing by grouping designation (step S4-2). Specifically, the map creation unit 214 of the control unit 21 acquires a step for the individual item specified in the client terminal 10 from the basic evaluation information storage unit 28. Then, the map creation means 214 creates a matrix (map) composed of map elements in which the increments of the individual items are combined. Here, an n-dimensional map (for example, a two-dimensional map when two individual items are selected) is created when n individual items are selected.

Next, the following processing is repeated for the generated map element.
The control unit 21 of the bond evaluation support server 20 executes a default rate calculation process in the map element (step S4-3). Specifically, the map creation means 214 of the control unit 21 extracts the depreciable bond management record 240 included in the step of each individual item variable in the map element in the designated analysis period. Next, the map creation means 214 calculates the total number of receivables in this depreciable receivable management record 240. Next, the map creation means 214 calculates the default number of receivables for each elapsed period (months) from the contract date to the amortization date in the default receivables. Then, the map creation unit 214 calculates a time-series default rate corresponding to the elapsed period from the current time for the map element to be processed by dividing the default number of claims for each elapsed period by the total number of claims.

  Next, the control unit 21 of the bond evaluation support server 20 executes a prepayment rate calculation process in the map element (step S4-4). Specifically, the map creation means 214 of the control unit 21 calculates the number of prepayment claims for each lapse period (months) from the contract date to the amortization date in the prepayment claims. Then, the map creating means 214 calculates a time-series prepayment rate according to the elapsed period from the present time for the map element to be processed by dividing the number of prepaid claims for each elapsed period by the total number of claims.

  When the calculation process of the default rate and the prepayment rate is finished for all the map elements, the control unit 21 of the bond evaluation support server 20 executes the collection process of the collection risk rate map (step S4-5). Specifically, the map creation unit 214 of the control unit 21 records a default rate map in which the calculated default rate (time series) is set in each map element in the collection risk rate map storage unit 26. Further, the map creating means 214 records a prepayment rate map in which the calculated prepayment rate (time series) is set in each map element in the collection risk rate map storage unit 26.

(Recovery schedule creation process)
Next, the collection schedule table creation process will be described with reference to FIG.
In this process, the bond management record 250 recorded in the bond information storage unit 25 for each product is specified as a process target, and the following process is repeated.

  Here, first, the control unit 21 of the bond evaluation support server 20 executes a collection schedule calculation process (step S5-1). Specifically, the schedule table creation means 215 of the control unit 21 calculates the recovery schedule time and the recovery amount at each recovery schedule time based on the balance and repayment conditions recorded in the bond management record 250.

  Next, the control unit 21 of the claim evaluation support server 20 executes a grouping designation specifying process to which the claim belongs (step S5-2). Specifically, the schedule table creation means 215 of the control unit 21 acquires the item values of the individual items designated for grouping in the bond management record 250. If an item related to user attribute information is included in the individual items designated for grouping, the user management record is stored in the user information storage unit 23 using the user code recorded in the claim management record 250. 230 is extracted and the item value of attribute information is acquired. Then, the schedule table creating means 215 specifies the map element to which the item value of the individual item designated for grouping belongs.

  Next, the control unit 21 of the bond evaluation support server 20 executes a process for adding the scheduled collection amount (step S5-3). Specifically, the schedule creation means 215 of the control unit 21 first calculates the credit collection amount in the collection schedule corresponding to the scheduled collection time in the collection schedule grouped by the specified map element. Add the collected amount.

  When the above processing is completed for all the claims, the control unit 21 of the claim evaluation support server 20 executes a collection schedule table output process (step S5-4). Specifically, the schedule table creating means 215 of the control unit 21 outputs a collection schedule table grouped by map elements for each credit product on the display of the client terminal 10.

According to this embodiment, the following effects can be obtained.
(1) In the present embodiment, the control unit 21 of the claim evaluation support server 20 creates a map for the default rate (step S2-5), a collection schedule table creation process (step S2-6), and a market price calculation process (step S2-6). Step S2-7) is executed. Thereby, the market value evaluation of the receivable can be performed in consideration of the default rate and the prepayment rate.

  (2) In the present embodiment, the control unit 21 of the bond evaluation support server 20 executes a correlation evaluation process (step S2-3) and a correlation evaluation result output process (step S2-4). Thereby, the default rate and the prepayment rate can be predicted in consideration of the contents of the bond and the user attribute.

  In addition, the control unit 21 of the bond evaluation support server 20 executes analysis period candidate identification processing (step S2-1) and analysis target extraction processing (step S2-2). Thereby, it is possible to specify an individual item having a correlation with the default rate in consideration of the analysis period.

  (3) In the present embodiment, the control unit 21 of the bond evaluation support server 20 has a default rate calculation process (step S3-1), a correlation coefficient calculation process (step S3-2), and whether there is a correlation. The determination process about whether (step S3-3) is performed. When it is determined that there is a correlation (in the case of “YES” in step S3-3), the control unit 21 of the bond evaluation support server 20 executes a grouping element specifying process (step S3-4). Then, the control unit 21 of the bond evaluation support server 20 executes a grouping designation process (step S4-1). Thereby, the individual item used for calculating the market value of the bond can be selected in consideration of the correlation.

  (4) In the present embodiment, the control unit 21 of the bond evaluation support server 20 performs a collection schedule calculation process (step S5-1), a grouping designation specifying process to which the bond belongs (step S5-2), and a collection schedule. An amount addition process (step S5-3) is executed. Thereby, the collection schedule table can be created in consideration of the map elements of the default rate map and the prepayment rate map.

In addition, you may change each said embodiment as follows.
In the above embodiment, the market value of a bond is evaluated using the client terminal 10 and the bond evaluation support server 20 connected via a network. The hardware configuration for performing the market value evaluation of the bond is not limited to this, and a stand-alone bond management support apparatus including an input unit and an output unit may be used.

  In the above embodiment, the market price evaluation process is executed using the newly acquired load file. Instead of this, a collection risk rate map may be created using past evaluation results. In this case, the bond evaluation support server 20 is provided with an evaluation history information storage unit as history information storage means. In this evaluation history information storage unit, grouping designations (individual items) used for past (previous) market price calculation and a default rate map created in the past are recorded. Further, the evaluation basic information storage unit 28 includes a prediction evaluation reference value for determining whether or not the difference (absolute value) between the prediction of the default rate and the actual result is within the allowable range, and the change in the user configuration is within the allowable range. The user attribute reference value for determining whether or not is stored. The market price evaluation process of this embodiment will be described with reference to FIG.

  First, the control unit 21 of the bond evaluation support server 20 executes a grouping designation result acquisition process (step S6-1). Specifically, the evaluation management unit 212 of the control unit 21 acquires the grouping designation (grouping designation result) recorded in the evaluation history information storage unit. Here, for example, the grouping designation used for the previous market price evaluation is acquired from the evaluation history information storage unit.

  Next, the control unit 21 of the bond evaluation support server 20 executes a comparison process between the prediction and the actual result (step S6-2). Specifically, the evaluation management unit 212 of the control unit 21 instructs the map creation unit 214 to create a default performance map for the target period of the previous market price evaluation. In this case, the map creating means 214 extracts the depreciable claim management record 240 for the period subject to the previous market price evaluation from the amortized claim information storage unit 24. Next, the map creation means 214 executes a default rate calculation process for map elements, as in step S4-3. Next, the map creation means 214 creates a default rate result map in which the calculated default rate (time series) is set for each map element. Then, the map creation unit 214 provides the created default rate map to the evaluation management unit 212. In this case, the evaluation management unit 212 acquires the previously created default rate map from the evaluation history information storage unit and compares it with the default rate result map.

  Next, the control unit 21 of the bond evaluation support server 20 executes a determination process as to whether or not it is within an allowable range (step S6-3). Specifically, the evaluation management unit 212 of the control unit 21 calculates the difference (absolute value) of the default rate in each map element in the previously created default rate map and default rate result map, and the total value of the differences Is calculated. When the total value of the differences is equal to or less than the predicted evaluation reference value recorded in the evaluation basic information storage unit 28, it is determined that the difference is within the allowable range.

  When it is determined that the actual result is within the allowable range of prediction (in the case of “YES” in step S6-3), the control unit 21 of the bond evaluation support server 20 determines whether the change in the user configuration is within the allowable range. Is executed (step S6-4). Specifically, the evaluation management unit 212 of the control unit 21 calculates a statistical value of the attribute information of the user management record 230 used in the previous market price evaluation. Further, the correlation evaluation unit 213 acquires from the user information storage unit 23 the user management record 230 for the previous receivable for market price evaluation and the current receivable for market price evaluation. Then, the correlation evaluation unit 213 calculates the statistical value of the previous attribute information and the statistical value of the current attribute information, and calculates the difference (absolute value) between the two. If the statistical value difference is less than or equal to the user attribute reference value, it is determined that the change in the user configuration is within the allowable range.

  When it is determined that the change in the user configuration is within the allowable range (in the case of “YES” in Step S6-4), the control unit 21 of the bond evaluation support server 20 executes a reuse process of the collection risk rate map (Step S6-4). S6-5). Specifically, the evaluation management means 212 of the control unit 21 employs the previous collection risk rate map.

On the other hand, when it is determined that the actual results are not within the allowable range of prediction, or when it is determined that the change in the user configuration is not within the allowable range (in the case of “NO” in steps S6-3 and S6-4), the bond evaluation support The control unit 21 of the server 20 re-executes the calculation of the correlation coefficient. Specifically, analysis period candidate specification processing (step S2-1) to map creation processing (step S2-5) are newly executed. Then, the control unit 21 of the claim evaluation support server 20 uses the newly created collection risk rate map or the previous collection risk rate map, as in steps S2-6 and S2-7, to collect the collection schedule table. (Step S6-6), a market price calculation process (Step S6-7) is executed.
Accordingly, it is possible to determine the appropriateness of the collection risk rate map used in the past and the presence / absence of changes in the debtor, and to efficiently evaluate the market value of the bond.

  In the above embodiment, a map is created using the increments of each individual item recorded in the evaluation basic information storage unit 28. Here, the step need not be fixed, and may be changed according to the situation. In this case, the evaluation basic information storage unit 28 records a plurality of increments of different sizes for each individual item. This correlation evaluation process will be described with reference to FIG.

  Here, as in steps S3-1 to S3-4, the control unit 21 of the bond evaluation support server 20 calculates the default rate (step S7-1) and the correlation coefficient (step S7-2). Then, a determination process (step S7-3) as to whether or not there is a correlation and a grouping element identification process (step S7-4) are executed.

  Next, the control unit 21 of the bond evaluation support server 20 executes a determination process as to whether any individual item has a correlation (step S7-5). Specifically, the correlation evaluation unit 213 of the control unit 21 determines whether there is an individual item whose calculated correlation coefficient is higher than the correlation reference value.

  When it is determined that any individual item has a correlation (in the case of “YES” in step S7-5), the correlation evaluation process is terminated. In this case, a default rate map is created using individual items specified as grouping elements.

  On the other hand, when it is determined that none of the individual items has a correlation (in the case of “NO” in step S7-5), the control unit 21 of the bond evaluation support server 20 performs a determination process as to whether re-evaluation is possible. Execute (Step S7-6). Specifically, the correlation evaluation unit 213 of the control unit 21 determines that re-evaluation is possible when there is an unused step remaining in the step recorded in the evaluation basic information storage unit 28. .

When it is determined that re-evaluation is possible (in the case of “YES” in step S7-6), the control unit 21 of the bond evaluation support server 20 executes a change process of the increment (step S7-7). Specifically, the correlation evaluation unit 213 of the control unit 21 re-executes from the process of step S7-1 using the increments not yet used in the evaluation basic information storage unit 28. On the other hand, when it is determined that re-evaluation is impossible (in the case of “NO” in step S7-6), the correlation evaluation process is terminated. In this case, there is no correlation between the default rate and the individual items.
Thereby, by changing the increment, the correlation can be detected and the default rate map can be created.

  -In the correlation evaluation process of the said embodiment, a default rate is calculated for every credit goods in a default rate calculation process (step S3-1). Here, the same user may use a plurality of credit products. Therefore, a case where the correlation evaluation process is performed in consideration of users of a plurality of credit products will be described with reference to FIG.

  First, the control unit 21 of the claim evaluation support server 20 executes a default rate change history calculation process for each credit product (step S8-1). Specifically, the correlation evaluation unit 213 of the control unit 21 extracts the depreciable claim management record 240 from the depreciable claim information storage unit 24 every predetermined period. Then, the correlation evaluation means 213 calculates the total number of receivables using this depreciable receivable management record 240 for each credit product. Further, the correlation evaluation unit 213 calculates the number of default receivables for each default period for each elapsed period (months) from the contract date to the amortization date. Then, the correlation evaluation unit 213 calculates a default rate change history composed of default rates obtained by dividing the default number of claims by the total number of claims for each elapsed period.

  Next, the control unit 21 of the bond evaluation support server 20 executes a calculation process of a correlation coefficient of default rates between credit products (step S8-2). Specifically, the correlation evaluation unit 213 of the control unit 21 calculates the correlation coefficient by introducing the default rate change history of each credit product into the correlation coefficient calculation function.

  Next, the control unit 21 of the claim evaluation support server 20 executes a process for specifying a combination of credit products having a correlation (step S8-3). Specifically, the correlation evaluation unit 213 of the control unit 21 specifies a combination of credit products whose correlation coefficient is equal to or greater than a reference value.

Next, the control unit 21 of the claim evaluation support server 20 collects claims of highly relevant products and executes a default rate calculation process (step S8-4). Specifically, the correlation evaluation unit 213 of the control unit 21 collects the credits of the specified credit product and executes the correlation evaluation process. It should be noted that the correlation evaluation process is executed independently for credit products that have low relevance to other credit products.
Thereby, it is possible to perform a correlation evaluation process for credit products having high correlation in the default rate change history and create a common default rate map.

  -In the correlation evaluation process of the said embodiment, a default rate is calculated for every credit goods in a default rate calculation process (step S3-1). Here, the same user may use a plurality of credit products. Therefore, in the combination of a plurality of credit products, when many of the debtors using each credit product are common, the correlation evaluation process is performed collectively. Specifically, in a combination of a plurality of specific credit products, the ratio of the number of obligors who use all credit products of this combination is high with respect to the total number of obligors who use each credit product of this combination. Suppose. In this case, in the basic evaluation information storage unit 28, a common use reference value for determining the level of this ratio is recorded. This process will be described with reference to FIG.

  First, the control unit 21 of the bond evaluation support server 20 executes a process for identifying users of a plurality of products (Step S9-1). Specifically, the correlation evaluation unit 213 of the control unit 21 generates a combination of a plurality of credit products. And the correlation evaluation means 213 specifies the debtor who is using the credit product included in this combination using the product-specific claim information storage unit 25. Then, the correlation evaluation unit 213 calculates the number of obligors (the number of users) who use all the credit products included in this combination.

  Next, the control unit 21 of the claim evaluation support server 20 executes a calculation process of the ratio of the number of users of all credit products to the total number of users of each credit product (step S9-2). Specifically, the correlation evaluation unit 213 of the control unit 21 uses the product-specific claim information storage unit 25 to identify all debtors who use at least one product among the credit products included in the combination. The total number of users is calculated. Then, the correlation evaluation unit 213 calculates a common user ratio obtained by dividing the number of users of all credit products included in the combination by the total number of users of each credit product included in the combination.

  Next, the control unit 21 of the claim evaluation support server 20 executes a highly relevant credit product specifying process (step S9-3). Specifically, the correlation evaluation unit 213 of the control unit 21 specifies a combination of credit products (a highly relevant credit product) in which the calculated common user ratio exceeds the common usage reference value.

  Next, the control unit 21 of the claim evaluation support server 20 collects claims of highly relevant products and executes a default rate calculation process (step S9-4). Specifically, the correlation evaluation unit 213 of the control unit 21 collects the credits of the specified credit product and executes the correlation evaluation process. Thereby, it is possible to create a common default rate map by performing a correlation evaluation process on credit products that are highly related to each other.

In the above embodiment, a default rate map is created for each credit product. Instead of this, a default rate map may be created by designating any combination of credit products according to the usage status of credit products. In this case, the credit management record 250 is recorded in the product-specific credit information storage unit 25 for each combination of credit products used. And a correlation evaluation process is performed for every combination.
Thereby, the correlation with a default rate is computable according to the user who uses a plurality of goods, and the contents of a claim.

  In the above embodiment, the map element is determined by specifying grouping using the default rate. Alternatively, the map element may be determined by specifying grouping using the prepayment rate. In this case, the prepayment rate is used in the correlation evaluation process.

  In addition, grouping designation may be performed by combining individual items correlated with the default rate and individual items correlated with the prepayment rate. In this case, the prepayment rate and the default rate are used in the correlation evaluation process. Then, an individual item having a high correlation with the prepayment rate or the default rate is specified as a grouping element. Here, the map element may be determined by mixing individual items highly correlated with the default rate and individual items highly correlated with the prepayment rate.

  DESCRIPTION OF SYMBOLS 10 ... Client terminal, 20 ... Claims evaluation support server, 21 ... Control part, 211 ... Claim information acquisition means, 212 ... Evaluation management means, 213 ... Correlation evaluation means, 214 ... Map creation means, 215 ... Schedule table creation means, 216 ... Market value calculation means, 22 ... Original data storage section, 23 ... User information storage section, 24 ... Depreciable loan information storage section, 25 ... Debt information storage section by product, 26 ... Collection risk rate map storage section, 27 ... Collection A schedule table storage unit, 28 ... an evaluation basic information storage unit.

Claims (8)

A debtor information storage means for recording the attribute information of the debtor in association with the debtor identifier;
A depreciable receivable information storage means for recording depreciated receivable information together with information for identifying whether a collection risk has occurred in association with the debtor identifier,
An existing claim information storage means for recording the claim information with a credit balance in association with the debtor identifier;
A loan evaluation support system comprising a control means for executing accounting management processing,
The control means is
Using the depreciable claim information storage means, identify the debtor identifier in which recovery risk has occurred, means for obtaining the debtor attribute information of the debtor identifier from the debtor information storage means;
Means for calculating a recovery risk rate for a claim recorded in the depreciable claim information storage means for each classification of items included in the attribute information or claim information;
A means for calculating a correlation index with the recovery risk rate for the item, and identifying an item having a correlation in the correlation index;
With respect to the specified item , in each map element for classifying item values of individual items of receivables, information that specifies whether or not a collection risk recorded in the depreciable receivable information storage means has occurred, an elapsed period A means to create a collection risk rate map that calculates the collection risk rate for each bond ;
Using the claim information of the claim recorded in the existing claim information storage means, calculate the scheduled collection time and the scheduled collection amount,
Identify the map element to which the bond belongs, and for each map element of the item, create a collection schedule that sums up the scheduled collection amount according to the scheduled collection period,
Using the claim information recorded in the existing claim information storage means, identify the map element to which the claim belongs, and use the recovery risk rate corresponding to the elapsed period in the map element and the recovery scheduled amount to collect And a means for performing accounting management processing for calculating a recovery scheduled amount in consideration of risks . In the accounting process, the recovery plan with recovery expected amount for each harvest time included in the table to calculate the present value, according to claim 1, characterized in that summing the current value of each of the recovery time Debt assessment support system. An output means and an input means are connected to the control means,
3. The claim evaluation support according to claim 1, wherein a correlated item is output to the output means, and a collection risk rate map is created using the item selected using the input means. system. In the depreciable loan information storage means, bond information is recorded in association with product information of a plurality of credit products,
In a combination of a plurality of specific credit products, when the ratio of the number of debtors who use all credit products of the combination is high with respect to the total number of debtors who use each credit product of the combination, the credit products The claim evaluation support system according to any one of claims 1 to 3 , wherein a collection risk rate map is created by collecting the claim information of the claims. From the depreciable claim information storage means, for each of a plurality of analysis periods, obtains the claim information depreciated within each analysis period,
Wherein each analysis period, receivables evaluation support system according to any one of claims 1-4 for the said items, and calculates a correlation index of the collection risk ratio. It further comprises a history information storage means for recording a past collection risk rate map,
Using the claim information recorded in the depreciable claim information storage means, calculate the recovery risk rate results for the map elements included in the recovery risk rate map recorded in the history information storage means,
Compare the recovery risk rate recorded in the recovery risk rate map with the actual recovery risk rate,
The claim evaluation support system according to any one of claims 1 to 5 , further comprising means for determining whether or not the collection risk rate map can be reused according to the comparison result. A debtor information storage means for recording the attribute information of the debtor in association with the debtor identifier;
A depreciable receivable information storage means for recording depreciated receivable information together with information for identifying whether a collection risk has occurred in association with the debtor identifier,
An existing claim information storage means for recording the claim information with a credit balance in association with the debtor identifier;
A method for supporting a credit assessment using a credit assessment system comprising a control means for executing an accounting management process,
The control means is
Using the depreciable claim information storage means to identify a debtor identifier in which a recovery risk has occurred, obtaining from the debtor information storage means the attribute information of the debtor of the debtor identifier;
Calculating a recovery risk rate for a claim recorded in the depreciable claim information storage means for each classification of items included in the attribute information or claim information;
For the item, calculating a correlation index with the recovery risk rate, and identifying a correlated item in the correlation index;
With respect to the specified item , in each map element for classifying item values of individual items of receivables, information that specifies whether or not a collection risk recorded in the depreciable receivable information storage means has occurred, an elapsed period Creating a collection risk rate map that calculates the collection risk rate for each bond ;
Using the claim information of the claim recorded in the existing claim information storage means, calculate the scheduled collection time and the scheduled collection amount,
Identify the map element to which the bond belongs, and for each map element of the item, create a collection schedule that sums up the scheduled collection amount according to the scheduled collection period,
Using the claim information recorded in the existing claim information storage means, identify the map element to which the claim belongs, and use the recovery risk rate corresponding to the elapsed period in the map element and the recovery scheduled amount to collect And a stage of performing an accounting management process for calculating a scheduled collection amount in consideration of the risk . A debtor information storage means for recording the attribute information of the debtor in association with the debtor identifier;
A depreciable receivable information storage means for recording depreciated receivable information together with information for identifying whether a collection risk has occurred in association with the debtor identifier,
An existing claim information storage means for recording the claim information with a credit balance in association with the debtor identifier;
A program for supporting a loan evaluation using a bond evaluation support system comprising a control means for executing accounting management processing,
The control means;
Using the depreciable claim information storage means, identify a debtor identifier in which recovery risk has occurred, means for obtaining attribute information of the debtor of the debtor identifier from the debtor information storage means,
Means for calculating a recovery risk rate for a claim recorded in the amortized claim information storage means for each classification of items included in the attribute information or claim information;
Means for calculating a correlation index with the recovery risk rate for the item, and identifying an item having a correlation in the correlation index;
With respect to the specified item , in each map element for classifying item values of individual items of receivables, information that specifies whether or not a collection risk recorded in the depreciable receivable information storage means has occurred, an elapsed period A means to create a collection risk rate map that calculates the collection risk rate for each bond ,
Using the claim information of the claim recorded in the existing claim information storage means, calculate the scheduled collection time and the scheduled collection amount,
Identify the map element to which the bond belongs, and for each map element of the item, create a collection schedule that sums up the scheduled collection amount according to the scheduled collection period,
Using the claim information recorded in the existing claim information storage means, identify the map element to which the claim belongs, and use the recovery risk rate corresponding to the elapsed period in the map element and the recovery scheduled amount to collect A claim evaluation support program that functions as a means for performing accounting management processing for calculating a recovery scheduled amount in consideration of risks .

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