JP4421797B2 - Bond data processing method - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a claim data processing method, and more particularly to a claim data processing method for processing claim data in a claim evaluation method for evaluating a claim pool in which a plurality of claims related to a plurality of debtors are pooled.
[0002]
[Prior art]
In recent years, the need for asset securitization has increased, and institutional maintenance and operation system construction have been promoted. Asset securitization refers to the creation of liquid products, typically securitization, backed by assets such as lease receivables and credit receivables held by the originator company. FIG. 1 shows a conventional mechanism for asset securitization. The basic mechanism of asset securitization is to transfer assets held by originator 1 to special purpose company (hereinafter referred to as SPC) 2 and pay cash flows generated from the separated assets to investors 3a-3c. It is a source of funds.
[0003]
In this way, products that do not depend on the corporate credit risk of the originator 1 can be configured to support not the creditworthiness of the originator 1 that raises the funds, but the creditworthiness of the assets that are separately transferred from the originator 1. . In addition, by separating and transferring excellent assets, the investors 3a to 3c can receive a stable cash flow. On the other hand, by incorporating a large number of assets, the risk of individual assets is diversified, and asset recovery becomes difficult due to bankruptcy of debtors (lease receivables, credit receivables) 4a-4c of individual assets Credit enhancement in preparation for
[0004]
In such a system, if the transferred receivables are not diversified enough to estimate the risk, but a considerable number of receivables are pooled, the rating of each obligor is checked and the risk of the entire receivable pool Need to be estimated.
[0005]
[Problems to be solved by the invention]
However, in order to estimate the risk of the entire pool, even if the rating of each obligor is weighted and the entire pool is evaluated, a quantitative loss amount can be calculated or an acceptable risk can be Therefore, there is a problem that it is difficult to determine the excess collateral ratio.
[0006]
In addition to the assessment of the entire pool, if the debtor included in the pool is a good company, the debts associated with this debtor can be excluded, or the ratio of the total debts by debtor to the total debt pool. There is also a problem that it is difficult to re-evaluate the entire pool according to individual obligors or receivables by performing processing such as making it below a certain ratio.
[0007]
The present invention has been made in view of such problems, and an object, based on the rating of the individual debtor, in order to evaluate the loans by calculating the quantitative喫損amount to provide a receivable data processing method for processing loans data.
[0008]
[Means for Solving the Problems]
In order to achieve such an object, the invention according to claim 1 is included in the claim pool in order to evaluate a claim pool in which a plurality of claims concerning a plurality of debtors are pooled. A plurality of receivable data including a debtor name and a receivable amount of a receivable are stored in a receivable data storage unit, a credit rating is performed for each obligor, a bankruptcy probability is calculated for each credit rated credit data, and the receivable data a first processing for processing, by executing the simulation of calculating the distribution of喫損amount based on the default probability of receivable data processed by the first processing, the second process of determining the excess collateral ratio in receivable evaluation method of performing bets, before performing the second processing, the receivable data processing method for processing loans data stored in the receivable data storage unit, the control unit, the receivable data From憶部, the extracts debtor name included in the receivable data, conversion to double-byte from byte, conversion to uppercase lowercase, and the debtor by performing conversion to official name from abbreviation according to a predetermined rule name normalized receivables numbers normalized debtor name to associate the same claim data, and appended to each receivable data, a first step of storing in the temporary storage unit of the data processing unit, said plurality of The control section searches for a company information storage unit storing special company information indicating whether each debtor is a good company or not by the normalized debtor name, and indicates that the company is a good company. If present, the debt data having the normalized debtor name that is the same as the debtor name indicating that the company is a superior company is included in the debt pool, the second step of deleting from the temporary storage unit Bonds Against receivables pool total is total loans data (S0), the total amount of loans receivables data associated with receivables numbers in said temporary storage unit that has been removed the receivable data in the second step when the ratio of the one company total (X) is greater than a predetermined ratio (P), said data processing unit, so that the ratio of the one company total for the loan pool total is the predetermined ratio , X1 smaller than S0 × P = X0, X1 which is (S0− (X−X1)) × P = X1 is calculated, and the bond data associated with the bond number stored in the temporary storage unit And a third step of deleting the claim amount data corresponding to X-X1 and subtracting the claim amount.
[0013]
The invention described in claim 2 is a computer-readable recording medium recording a program for causing a computer to execute the steps described in claim 1 .
[0014]
The invention described in claim 3 is a program for causing a computer to execute the steps described in claim 1 .
[0015]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
[0016]
FIG. 2 is a block diagram showing the configuration of the bond evaluation system according to the embodiment of the present invention. The debt assessment system 11 is a system that operates in the SPC, acquires debt data from the originator, evaluates the debt, determines the excess collateral ratio, and executes a series of processes until registering the transferred debt To do. The bond evaluation system 11 includes a control unit 12 that controls the system, a data processing unit 13 that processes and evaluates bond data, an input / output unit 14 that inputs and outputs data, and various databases. I have. The database includes, for example, a bond data master 21 for storing bond data, a credit rating master 22 for performing credit rating, a score master 23 for assigning a rating of an external credit research company, and a special data storing company data. And a company master 24.
[0017]
A network 31 is connected to the input / output unit 14 and, for example, bond data can be acquired from an information processing system included in the originator. The input / output unit 14 is connected to a display device 32 such as a liquid crystal display and an input device 33 such as a mouse and a keyboard. Further, the input / output unit 14 can be connected to an output device such as a printer (not shown), and can output the result of bond evaluation in a form format.
[0018]
FIG. 3 is a flowchart showing a bond evaluation method according to an embodiment of the present invention. First, the claim evaluation system 11 acquires the claim data of each claim in order to estimate the risk of the entire claim pool (S201). For example, the control unit 12 acquires bond data from the information processing system of the originator via the input / output unit 14 and the network 31 and stores the bond data in the bond data master 21. FIG. 4 shows a list of bond data stored in the bond data master 21. The bond data master 21 stores each bond as one record. One record includes, for example, a claim number 401, a debtor name 402, a debtor address 403, a claim amount 404, and the like.
[0019]
Since the debtor may have multiple debts, it is necessary to collect the debts for each debtor. This process is called name identification (S202). The control unit 12 searches the bond data master 21 and normalizes the pooled bond data for performing the bond evaluation. Normalization is, for example, conversion of characters according to a predetermined rule, such as conversion of half-width / full-width, uppercase / lowercase, conversion of “(stock)” / “corporation”, etc. I do. The control unit 12 collects bond data for each debtor based on the normalized debtor name. FIG. 5 shows a list of bond data after name identification. The credit data after name identification is stored in the temporary storage area of the data processing unit 13 as one record for each debtor. By name identification, the total amount of debt can be calculated for each debtor.
[0020]
Next, the control unit 12 of the bond evaluation system 11 searches the credit rating master 22 for each obligor and performs a credit rating (S203). FIG. 6 shows a list of bond data after credit rating. As shown in FIG. 6, the credit rating master 22 stores, for example, “Iroha Corporation”, a credit rating registered in advance for each branch. In the present embodiment, the control unit 12 further searches the score master 23 for each obligor and assigns a score that is rating information provided by an external credit check company (S204). FIG. 7 shows a list of bond data after the rating of the external credit check company is given. In this manner, the rating may be performed based on a plurality of credit rating information, or the rating may be performed based on any one of the credit rating information.
[0021]
FIG. 8 shows a list of credit data that has been credit-rated and credit data that has been assigned a rating of an external credit research company. As described above, by performing a rating based on a plurality of credit rating information, a more accurate evaluation without omission can be performed. The result of the rating is added to the bond data shown in FIG. 5 or the bond data shown in FIG. 8 is newly stored in the temporary storage area of the data processing unit 13.
[0022]
Next, the claim evaluation system 11 calculates a bankruptcy probability for each debtor (S205). The bankruptcy probability is a parameter used when performing a simulation described later. FIG. 9 shows a list of bond data after calculating the bankruptcy probability. The data processing unit 13 converts the rating 904 of the external credit research company into an external rating 905 based on a pre-registered table, and the credit rating data 903 or the external rating 905 is determined in advance for each rated credit data. The bankruptcy probability 906 is calculated by the registered calculation formula.
[0023]
The process of extracting a special company from bond data (S206) will be described. Special companies are good companies that do not need to be included in the pool of receivables. If the debtor is a good company, the debt pool is evaluated after excluding it from the debt pool. The control unit 12 of the bond evaluation system 11 searches the special company master 24 to determine whether or not there is a special company in the bond data. If there is, it is stored in the temporary storage area of the data processing unit 13. The corresponding record is deleted from the received bond data.
[0024]
Next, one company restriction (S207) will be described. FIG. 10 shows a list of bond data after one company restriction. One company restriction means that the overall ratio 1004, which is the ratio of the total debts 1003 of each debtor 1002, to the total debt pool total is limited to a certain ratio. In FIG. 10, the fixed ratio is 25%. A method for keeping the ratio constant will be briefly described below.
[0025]
“Iroha Corporation” has an overall ratio of over 40%. In order to make this within 25% of the total amount S0 of the entire receivable pool, the total amount of debt of “Iroha Corporation” is reduced to S0 × 0.25 = X0. Then, the total amount of the pool of receivables also decreases, so the overall ratio does not fall within 25%. Therefore, for example, the total debt of “Iroha Corporation” is set to X1 smaller than X0. At this time, S1 × 0.25 = X1 with respect to the total amount S1 of the entire receivable pool when the total amount of debt of “Iroha Corporation” is X1. Calculate the overall ratio of each obligor and check whether the overall ratio of each obligor is within 25%. If there is a debtor whose overall ratio exceeds 25%, the above calculation is repeated for that debtor. The data processing unit 13 performs such calculation to calculate the total amount 1005 after the restriction and the overall ratio 1006 after the restriction.
[0026]
When the above-described processing of bond data is completed, the bond evaluation system 11 performs a simulation (S208). A Monte Carlo simulation is performed based on the bankruptcy probability 906 and the total amount 1005 after the restriction. Usually, about 1 to 30,000 times are performed, and the distribution of the amount of lost money is calculated. FIG. 11 shows the distribution of the amount of lost money as a result of the simulation. The result of 30,000 trials based on the bond data shown in FIGS.
[0027]
The control unit 12 determines the excess collateral ratio from the simulation result based on the failure probability registered in advance (S209). For example, if the probability of loss is 0.1%, it can be seen from the graph shown in FIG. 11 that the amount of loss that is 30 times / 30,000 times = 0.1% is 25 million yen. If the total amount of 124 million yen in the entire receivable pool shown in FIG. 10 is 25 million yen, the excess collateral ratio is approximately 20%.
[0028]
The control unit 12 can display the simulation results and evaluation results such as the probability of failure, the amount of loss, and the excess collateral ratio on the display device 32 via, for example, the input / output unit 14, such as a printer in a form format Can also be output. In this way, it is possible to easily determine the excess collateral ratio while changing the loss probability and the amount of the charge according to the allowable risk.
[0029]
In this way, when the receivable evaluation is completed and the receivable is transferred from the originator to the SPC, the receivable evaluation system 11 prepares for registration associated with the receivable transfer (S210). Specifically, a document for registration is created on the basis of the receivable data subjected to the receivable evaluation. The control unit 12 creates a document by inserting necessary bond data into a previously registered document format.
[0030]
The present invention supplies a storage medium storing software program codes for realizing the functions of the above-described embodiments to a bond evaluation system, and the control unit of the bond evaluation system stores the program codes stored in the storage medium. Needless to say, this can also be achieved by executing read. In this case, the program code itself read from the storage medium realizes the novel function of the present invention, and the storage medium storing the program code constitutes the present invention.
[0031]
Further, it goes without saying that the present invention is achieved by a computer reading and executing a program code from a storage medium storing a program code of software for realizing the bond evaluation method.
[0032]
Furthermore, it goes without saying that the present invention can also be applied to a case where a software program for realizing the functions of the above-described embodiments is distributed to a requester via a communication line such as personal computer communication.
[0033]
【The invention's effect】
As explained above, according to the present invention, the risk of the entire receivable pool is accurately estimated by rating individual obligors, calculating a quantitative loss amount, and determining an excess collateral ratio. It becomes possible.
[Brief description of the drawings]
FIG. 1 is a diagram for explaining a conventional mechanism for asset securitization;
FIG. 2 is a block diagram showing a configuration of a bond evaluation system according to an embodiment of the present invention.
FIG. 3 is a flowchart showing a bond evaluation method according to an embodiment of the present invention.
FIG. 4 is a diagram showing a list of bond data stored in a bond data master.
FIG. 5 is a diagram showing a list of bond data after name identification.
FIG. 6 is a diagram showing a list of bond data after credit rating is performed.
FIG. 7 is a view showing a list of bond data after assigning a score of an external credit research company.
FIG. 8 is a diagram showing a list of credit data that has been credit-rated and credit data that has been assigned a rating of an external credit research company.
FIG. 9 is a diagram showing a list of bond data after calculating the probability of bankruptcy.
FIG. 10 is a diagram showing a list of bond data after one company restriction.
FIG. 11 is a diagram showing a distribution of loss amounts as a result of simulation.
[Explanation of symbols]
1 Originator 2 Special Purpose Company (SPC)
3a to 3c Investors 4a to 4c Debtor 11 Bond evaluation system 12 Control unit 13 Data processing unit 14 Input / output unit 21 Bond data master 22 Rating master 23 Rating master 24 Special enterprise master 31 Network 32 Display device 33 Input device

Claims (3)

In order to evaluate a receivable pool in which a plurality of receivables related to a plurality of debtors are pooled, a plurality of receivable data including a debtor name and a receivable amount of the receivables included in the receivable pool are stored in a receivable data storage unit, wherein performs credit rating for each debtor, the bankruptcy probability for each credit rating receivables data calculated, a first processing for processing the loan data, the first default probability of receivable data processed in the processing In the claim evaluation method for executing the second process for determining the excess collateral ratio by executing a simulation for calculating the distribution of the amount of the loss based on the claim data , before executing the second process, the claim data In the claim data processing method for processing the claim data stored in the storage unit,
The control unit extracts the obligor name included in the bond data from the bond data storage unit, converts from half-width to full-width, lower-case to upper-case, and conversion from abbreviations to official names according to predetermined rules. the debtor name normalized receivables numbers normalized debtor name to associate the same claim data, and appended to each receivable data by performing, first stored in the temporary storage unit of the data processing unit One step,
The control unit searches for a company information storage unit storing special company information indicating whether or not each of the plurality of debtors is a good company, by the normalized debtor name, A second step of deleting, from the temporary storage unit, receivable data having the normalized debtor name that is the same as the debtor name indicating that the company is a good company,
Receivable pool total (S0) , which is the total amount of receivable data included in the receivable pool, is associated with the receivable number in the temporary storage unit from which the receivable data has been deleted in the second step . when the ratio of the one company total (X) is a total amount of loans receivables data exceeds the predetermined ratio (P), said data processing unit, the proportion of the one company total for the loan pool capitalization the X1 which is (S0− (X−X1)) × P = X1 is calculated for X1 which is smaller than S0 × P = X0 so that the predetermined ratio is obtained, and the credit stored in the temporary storage unit A claim data processing method comprising: a third step of deleting claim data corresponding to X-X1 from claim data associated with a number and subtracting the claim amount.   A computer-readable recording medium recording a program for causing a computer to execute the steps according to claim 1.   The program for making a computer perform each step of Claim 1.

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