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- W3125760562 abstract "We propose a Bayesian methodology that enables banks to improve their credit scoring models by imposing prior information. As prior information, we use coefficients from credit scoring models estimated on other data sets. Through simulations, we explore the default prediction power of three Bayesian estimators in three different scenarios and find that they perform better than standard maximum likelihood estimates. We recommend that banks consider Bayesian estimation for internal and regulatory default prediction models." @default.
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- W3125760562 date "2005-05-31" @default.
- W3125760562 modified "2023-09-27" @default.
- W3125760562 title "Bayesian Methods for Improving Credit Scoring Models" @default.
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