Would Two-Stage Scoring Models Alleviate Bank Exposure to Bad Debt?

Abdou, H. A., Mitra, S., Fry, J. & Elamer, A. A. (2019) Would two-stage scoring models alleviate bank exposure to bad debt?, Expert Systems with Applications. Accepted 15th March, 2019. DOI/10.1016/j.eswa.2019.03.028.

35 Pages Posted: 11 Apr 2019

See all articles by Hussein Abdou

Hussein Abdou

The Lancashire School of Business & Enterprise; Department of Management, Faculty of Commerce, Mansoura University

Shatarupa Mitra

University of Salford - Salford Business School

John Fry

Manchester Metropolitan University

Ahmed A. Elamer

Brunel University London - Brunel Business School; Department of Accounting, Faculty of Commerce, Mansoura University

Date Written: March 15, 2019

Abstract

The main aim of this paper is to investigate how far applying suitably conceived and designed credit scoring models can properly account for the incidence of default and help improve the decision-making process. Four statistical modelling techniques, namely, discriminant analysis, logistic regression, multi-layer feed-forward neural network and probabilistic neural network are used in building credit scoring models for the Indian banking sector. Notably actual misclassification costs are analysed in preference to estimated misclassification costs. Our first-stage scoring models show that sophisticated credit scoring models, in particular probabilistic neural networks, can help to strengthen the decision-making processes by reducing default rates by over 14%. The second-stage of our analysis focuses upon the default cases and substantiates the significance of the timing of default. Moreover, our results reveal that State of residence, equated monthly installment, net annual income, marital status and loan amount, are the most important predictive variables. The practical implications of this study are that our scoring models could help banks avoid high default rates, rising bad debts, shrinking cash flows and punitive cost-cutting measures.

Keywords: Credit; Indian Banks; Neural Networks; Actual Misclassification Costs; Timing of Default

Suggested Citation

Abdou, Hussein and Mitra, Shatarupa and Fry, John and Elamer, Ahmed Ahmed, Would Two-Stage Scoring Models Alleviate Bank Exposure to Bad Debt? (March 15, 2019). Abdou, H. A., Mitra, S., Fry, J. & Elamer, A. A. (2019) Would two-stage scoring models alleviate bank exposure to bad debt?, Expert Systems with Applications. Accepted 15th March, 2019. DOI/10.1016/j.eswa.2019.03.028.. Available at SSRN: https://ssrn.com/abstract=3354373

Hussein Abdou

The Lancashire School of Business & Enterprise ( email )

The Lancashire Law School
Corporation Street
Preston, PR1 2HE
United Kingdom
00441772894700 (Phone)

Department of Management, Faculty of Commerce, Mansoura University ( email )

Mansoura, 35516
Egypt

Shatarupa Mitra

University of Salford - Salford Business School ( email )

Salford, Greater Manchester M5 4WT
United Kingdom

John Fry

Manchester Metropolitan University ( email )

All Saints
Manchester, M15 6BH
United Kingdom

Ahmed Ahmed Elamer (Contact Author)

Brunel University London - Brunel Business School ( email )

Kingston Lane
Eastern Gateway Building
Uxbridge, Middlesex UB8 3PH
United Kingdom

Department of Accounting, Faculty of Commerce, Mansoura University ( email )

Faculty of Commerce, Mansoura University
Elgomhouria St.
Mansoura, Mansoura 35516
Egypt

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