KR20140029994A - Method for verifying sutability of loss given default/exposure at default - Google Patents

Method for verifying sutability of loss given default/exposure at default Download PDF

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Publication number
KR20140029994A
KR20140029994A KR1020120096797A KR20120096797A KR20140029994A KR 20140029994 A KR20140029994 A KR 20140029994A KR 1020120096797 A KR1020120096797 A KR 1020120096797A KR 20120096797 A KR20120096797 A KR 20120096797A KR 20140029994 A KR20140029994 A KR 20140029994A
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South Korea
Prior art keywords
collateral
default
collection
rate
information
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KR1020120096797A
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Korean (ko)
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김영조
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중소기업은행
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Priority to KR1020120096797A priority Critical patent/KR20140029994A/en
Publication of KR20140029994A publication Critical patent/KR20140029994A/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02—Banking, e.g. interest calculation or account maintenance

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  • Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
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  • General Business, Economics & Management (AREA)
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  • Entrepreneurship & Innovation (AREA)
  • Physics & Mathematics (AREA)
  • Finance (AREA)
  • General Physics & Mathematics (AREA)
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  • Accounting & Taxation (AREA)
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  • Game Theory and Decision Science (AREA)
  • Operations Research (AREA)
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  • Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)

Abstract

Disclosed are a method and system for verifying the suitability of loss given default (LGD)/exposure at default (EAD). After classifying segments into collateral type, obligor type, and product type segments based on an obligor′s EAD, collateral details, and collection details during a past given period of time, a collection rate, a recovery rate, an additional usage rate, and a subrogate conversion rate of each segment by default year are calculated; an estimate, which is applied when calculating a BIS ratio, is determined based on the calculated values; and the estimate is verified by comparing the estimate with a real value which is actually realized. [Reference numerals] (200) Default information; (202) Exposure information; (204) Collateral information; (206) Collection costs; (208) Collection transaction details; (210) Collection information for each collateral; (212) Recovery information; (214) Collateral distribution details; (216) Checked collection transaction details; (218) Real estate collateral collection rate calculation; (220) Collateral distribution + collection details (splitting an account); (222) Collection rate calculation; (224) Recovery rate; (226) Credit; (228) Product; (230) Real estate; (232) Warranty; (234) Deposit; (236) AL/EL aggregate; (238) Statistics; (240) Credit/recovery rate; (242) Cumulative distribution; (244) For BIS calculation; (246) Collateral; (248) Credit; (250) Recovery; (AA) Source information; (BB) Intermediate table; (CC) Suitability verification

Description

Method for verifying suitability for LCD / EAD and its system {Method for verifying sutability of Loss Given Default / Exposure at Default}

The present invention relates to a method for monitoring quantitative suitability and performing statistical verification for LGD / EAD input to the risk amount calculation of the BIS.

The BIS ratio is the bank's equity ratio as set forth by the International Settlement Bank, which represents the bank's equity and identifies risk-weighted assets (for example, assets that are at risk of loss, such as loans and securities investments). To calculate. Therefore, a system for properly estimating and statistically verifying LGD / EAD used for calculating the amount of risk in BIS is required. However, in the past, the system is only performing one-time verification using Excel.

The technical problem to be achieved by the present invention is to provide a method and system that can monitor the adequacy of LGD / EAD input to the risk amount calculation of the BIS, and can perform statistical verification through automation.

In order to achieve the above technical problem, an example of the quantitative conformity verification method of the LGD / EAD according to the present invention, based on the exposure, collateral and collection history of the default borrower for a certain period of time, by mortgage type, borrower type, Classifying segments by product type; Calculating the recovery rate, recovery rate, additional usage rate, and now conversion rate for each segment by the default year; And determining an expected value to be applied when calculating the BIS ratio based on the calculated value, and comparing the actual value with the actual value.

According to the present invention, the adequacy of the LGD / EAD input factors can be monitored at all times. In addition, it is possible to enhance work efficiency and enhance execution ability by automating statistical verification tasks, and to develop self-development of algorithms for calculating thresholds of Z distribution, T distribution, and F distribution, and to set the upper limit or the lower limit automatically for estimation Can support verification work.

1 is a diagram illustrating an example of an LGD / EAD quantitative conformity verification system according to the present invention;
2 is a diagram illustrating an example of an LGD / EAD quantitative conformity verification process according to the present invention, and
3 is a flowchart of an example of a LGD / EAD quantitative conformity verification method according to the present invention.

Hereinafter, with reference to the accompanying drawings will be described in detail the LGD / EAD quantitative conformity verification method according to the present invention.

1 is a diagram illustrating an example of an LGD / EAD quantitative conformity verification system according to the present invention.

Referring to FIG. 1, the LGD / EAD quantitative conformity verification system includes a database 100, a segment unit 110, a calculation unit 120, and a verification unit 130, which loads information on past infringement.

The database 100 obtains and loads default information such as exposure information, collateral, and recovery history of the default borrower for a predetermined period of time.

The segment unit 110 may be classified by collateral type (for example, real estate mortgage, deposit mortgage, guarantee mortgage, etc.), by borrower type (corporate, small business, individual, etc.) based on the default information of the defaulted borrower loaded in the database 100, Classify by product type (credit product, collateral product, etc.). The segment unit 110 may classify the default information and the like by other various types as necessary.

The calculation unit 120 calculates parameter values, such as a recovery rate, a recovery rate, an additional usage rate, and a payment conversion rate, for each segment classified by the segment unit 110 for each sub-year. The calculator 120 predicts values such as LGD (Loss Given Default) and EAD (Exposure at Defalut) input to calculate the risk amount of the BIS using the calculated values.

For example, as a parameter value for estimating the LGD, values such as a recovery rate, a recovery rate, a credit recovery rate, and a default asset may be used. Here, the recovery rate indicates the rate at which companies, small businesses, and individuals recover from the default, and the recovery rate is identified through auction data on real estate, the recovery rate of deposit collateral, and the recovery rate of guarantee collateral. As a parameter value for estimating the EAD, an additional utilization rate and an egg conversion rate may be used. There may be several parameter elements to estimate LGD and EAD.

The verifier 130 verifies the validity of the predicted value by comparing the estimated values of the EAD and LGD estimated using the parameters of the recovery rate and the recovery rate calculated by the calculator 120 with the actual values of the currently realized EAD and LGD. And correct.

2 is a diagram illustrating an example of an LGD / EAD quantitative conformity verification process according to the present invention.

Referring to FIG. 2, as source information for the LGD / EAD quantitative conformity verification process, the borrower's default information 200, exposure information 202, collateral information 204, recovery cost 206, recovery transaction history ( 208), collateral-specific recovery information 210, and the like. According to an embodiment, such source information may be added or subtracted.

The source information is processed to generate an intermediate table classified by collateral type, borrower type, and product type, and then identify various parameters for calculating the expected values (eg, LGD, EAD) that are applied when calculating the BIS ratio.

More specifically, based on the exposure information 202 of the source information, the recovery information 212 of the default owner is calculated. The collateral distribution details 214 are calculated based on the default information 200, the exposure information 202, and the collateral information 204 of the default borrower. The confirmed recovery transaction history 216 is calculated based on the recovery transaction history 208 and the recovery information 210 for each security. The real estate security recovery rate 218 is calculated based on the recovery information 210 for each security.

Based on the collateral distribution history 214, the confirmed recovery transaction history 216, and the recovery cost 206, the collateral distribution and recovery history 220 divided for each account are calculated, and various parameters including the recovery rate are calculated based on the collateral distribution history 214, and the recovery transaction history 216. Obtain (222).

Each parameter obtained for calculating the BIS ratio includes a recovery rate (224), a credit recovery rate (226), a product (e.g., credit or draft) (228), real estate collateral (230), guarantee collateral (232), deposit collateral 234 and the like, and the like. From these parameters, estimates such as collateral 246, credit 248, recovery rate, recovery rate 250, etc. are used to calculate the BIS ratio. The estimated values are then monitored and verified against actual actual values. Various obtained parameters and data are provided through a web screen for the user to easily view.

3 is a flowchart of an example of a LGD / EAD quantitative conformity verification method according to the present invention.

Referring to FIG. 3, the system obtains and loads various kinds of default information of the default borrower (S300). The system classifies the information of the past borrower for a certain period of time into segments such as collateral type, borrower type, and product type (S310), and then assigns parameters such as recovery rate, recovery rate, additional usage rate, and payment rate for each segment to the default year. It calculates each (S320). The system then uses the calculated parameters to make estimates of the various values applied to the BIS ratio calculation, and then monitors the actual values actually realized and performs statistical verification (S330).

The present invention can also be embodied as computer-readable codes on a computer-readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored. Examples of the computer-readable recording medium include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage, and the like. The computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion.

So far I looked at the center of the preferred embodiment for the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the disclosed embodiments should be considered in an illustrative rather than a restrictive sense. The scope of the present invention is defined by the appended claims rather than by the foregoing description, and all differences within the scope of equivalents thereof should be construed as being included in the present invention.

Claims (1)

Classifying segments by collateral type, borrower type, and product type based on exposure, collateral, and recovery history of the default borrower for a certain period of time;
Calculating the recovery rate, recovery rate, additional usage rate, and now conversion rate for each segment by the default year; And
Determining an expected value to be applied when calculating the BIS ratio based on the calculated value, and comparing the actual value with the actual value, and verifying the estimated value.
KR1020120096797A 2012-08-31 2012-08-31 Method for verifying sutability of loss given default/exposure at default KR20140029994A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020027605A1 (en) * 2018-08-01 2020-02-06 한국원자력연구원 Image processing method and apparatus for stereoscopic images of nearby object in binocular camera system of parallel axis type
WO2023123933A1 (en) * 2021-12-30 2023-07-06 深圳前海微众银行股份有限公司 User type information determination method and device, and storage medium

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020027605A1 (en) * 2018-08-01 2020-02-06 한국원자력연구원 Image processing method and apparatus for stereoscopic images of nearby object in binocular camera system of parallel axis type
WO2023123933A1 (en) * 2021-12-30 2023-07-06 深圳前海微众银行股份有限公司 User type information determination method and device, and storage medium

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