{"title":"信用风险建模策略:通往奴役之路?","authors":"Dirk-Emma Baestaens","doi":"10.1002/(SICI)1099-1174(199912)8:4%3C225::AID-ISAF162%3E3.0.CO;2-V","DOIUrl":null,"url":null,"abstract":"This paper aims at presenting some practical issues in modeling default risk of a single commercial credit counterparty from the perspective of a large retail bank. We define default risk as the probability that a counterparty’s intrinsic credit quality deteriorates within a given time horizon such that contractual agreements cannot be honored. This work gives an insight into using scoring/rating models in a credit environment of a large European bank. Contrary to many banks, we did not define the segments in a first step with a view to developing the rating tools in a second step. Our approach has, to some extent, followed a different path. Iteratively, we both defined the borders for a particular segment and selected an appropriate rating tool. More particularly, customer segmentation has been carried out on the basis of various rating tools’ goodness-of-fit criteria. The topics cover customer segmentation using goodness-of-fit measures, data measurement levels and optimization algorithms, rating tool calibration to the central default tendency and communication to the end user. Copyright © 1999 John Wiley & Sons, Ltd.","PeriodicalId":153549,"journal":{"name":"Intell. Syst. Account. Finance Manag.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Credit risk modeling strategies: the road to serfdom?\",\"authors\":\"Dirk-Emma Baestaens\",\"doi\":\"10.1002/(SICI)1099-1174(199912)8:4%3C225::AID-ISAF162%3E3.0.CO;2-V\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper aims at presenting some practical issues in modeling default risk of a single commercial credit counterparty from the perspective of a large retail bank. We define default risk as the probability that a counterparty’s intrinsic credit quality deteriorates within a given time horizon such that contractual agreements cannot be honored. This work gives an insight into using scoring/rating models in a credit environment of a large European bank. Contrary to many banks, we did not define the segments in a first step with a view to developing the rating tools in a second step. Our approach has, to some extent, followed a different path. Iteratively, we both defined the borders for a particular segment and selected an appropriate rating tool. More particularly, customer segmentation has been carried out on the basis of various rating tools’ goodness-of-fit criteria. The topics cover customer segmentation using goodness-of-fit measures, data measurement levels and optimization algorithms, rating tool calibration to the central default tendency and communication to the end user. Copyright © 1999 John Wiley & Sons, Ltd.\",\"PeriodicalId\":153549,\"journal\":{\"name\":\"Intell. Syst. Account. Finance Manag.\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Intell. Syst. Account. Finance Manag.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/(SICI)1099-1174(199912)8:4%3C225::AID-ISAF162%3E3.0.CO;2-V\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intell. Syst. Account. Finance Manag.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/(SICI)1099-1174(199912)8:4%3C225::AID-ISAF162%3E3.0.CO;2-V","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Credit risk modeling strategies: the road to serfdom?
This paper aims at presenting some practical issues in modeling default risk of a single commercial credit counterparty from the perspective of a large retail bank. We define default risk as the probability that a counterparty’s intrinsic credit quality deteriorates within a given time horizon such that contractual agreements cannot be honored. This work gives an insight into using scoring/rating models in a credit environment of a large European bank. Contrary to many banks, we did not define the segments in a first step with a view to developing the rating tools in a second step. Our approach has, to some extent, followed a different path. Iteratively, we both defined the borders for a particular segment and selected an appropriate rating tool. More particularly, customer segmentation has been carried out on the basis of various rating tools’ goodness-of-fit criteria. The topics cover customer segmentation using goodness-of-fit measures, data measurement levels and optimization algorithms, rating tool calibration to the central default tendency and communication to the end user. Copyright © 1999 John Wiley & Sons, Ltd.