Data Mining for Credit Scoring

Data Mining for Credit Scoring

Indranil Bose, Cheng Pui Kan, Chi King Tsz, Lau Wai Ki, Wong Cho Hung
ISBN13: 9781599049519|ISBN10: 1599049511|EISBN13: 9781599049526
DOI: 10.4018/978-1-59904-951-9.ch148
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MLA

Bose, Indranil, et al. "Data Mining for Credit Scoring." Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications, edited by John Wang, IGI Global, 2008, pp. 2449-2463. https://doi.org/10.4018/978-1-59904-951-9.ch148

APA

Bose, I., Kan, C. P., Tsz, C. K., Ki, L. W., & Hung, W. C. (2008). Data Mining for Credit Scoring. In J. Wang (Ed.), Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications (pp. 2449-2463). IGI Global. https://doi.org/10.4018/978-1-59904-951-9.ch148

Chicago

Bose, Indranil, et al. "Data Mining for Credit Scoring." In Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications, edited by John Wang, 2449-2463. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-951-9.ch148

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Abstract

Credit scoring is one of the most popular uses of data mining in the financial industry. Credit scoring can be defined as a technique that helps creditors decide whether to grant credit to customers. With the use of credit scoring decisions about granting of loans can be made in an automated and faster way in order to assist the creditors in managing credit risk. This chapter begins with an explanation of the need for credit scoring followed by the history of credit scoring. Then it discusses the relationship between credit scoring and data mining. The major applications of credit scoring in three areas, which include credit card, mortgage and small business lending, are introduced. This is followed by a discussion of the models used for credit scoring and evaluation of seven major data mining techniques for credit scoring. A study of default probability estimation is also presented. Finally the chapter investigates the benefits and limitations of credit scoring as well as the future developments in this area.

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