Strathprints Home | Open Access | Browse | Search | User area | Copyright | Help | Library Home | SUPrimo

Variable reduction, sample selection bias and bank retail credit scoring

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)

Abstract

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.

Item type: Article
ID code: 15107
Keywords: bootstrap variable selection, credit scoring, loan performance forecasting, sample selection bias, Finance
Subjects: Social Sciences > Finance
Department: Strathclyde Business School > Accounting and Finance
Related URLs:
    Depositing user: Miss Donna McDougall
    Date Deposited: 22 Jan 2010 11:38
    Last modified: 19 Jun 2012 16:47
    URI: http://strathprints.strath.ac.uk/id/eprint/15107

    Actions (login required)

    View Item