Marshall, A.P. and Tang, L. and Milne, Alistair (2010) Variable reduction, sample selection bias and bank retail credit scoring. Journal of Empirical Finance, 17 (3). 501–512.Full text not available in this repository. (Request a copy from the Strathclyde author)
This paper investigates the effect of including the customer loan approval process to the estimation of loan performance and explores the influence of sample selection bias in predicting the probability of default. The bootstrap variable reduction technique is applied to reduce the variable dimension for a large dataset drawn from a major UK retail bank. The results show a statistically significant correlation between the loan approval and performance processes. We further demonstrate an economically significant improvement in forecasting performance when taking into account sample selection bias. We conclude that financial institutions can obtain benefits by correcting for sample selection bias in their credit scoring models.
|Keywords:||bootstrap variable selection, credit scoring, loan performance forecasting, sample selection bias, Finance, Finance, Economics and Econometrics|
|Subjects:||Social Sciences > Finance|
|Department:||Strathclyde Business School > Accounting and Finance|
|Depositing user:||Miss Donna McDougall|
|Date Deposited:||22 Jan 2010 11:38|
|Last modified:||22 Mar 2017 10:28|