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• W37348292 abstract "Consumer credit risk assessment involves the use of risk assessment tools to manage a borrower’s account from the time of pre-screening a potential application through to the management of the account during its life and possible write-off. The riskiness of lending to a credit applicant is usually estimated using a logistic regression model though researchers have considered many other types of classifier and preliminary evidence suggest support vector machines seem to be the most accurate. The training of a classifier on a sample of accepted applicants rather than on a sample representative of the applicant population seems not to result in bias though it does result in difficulties in setting the cut off. Profit scoring is a promising line of research and the Basel 2 accord has had profound implications for the way in which credit applicants are assessed and bank policies adopted." @default.
• W37348292 created "2016-06-24" @default.
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• W37348292 date "2006-01-01" @default.
• W37348292 modified "2023-09-28" @default.
• W37348292 title "Developments in consumer credit risk assessment" @default.
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