Credit risk estimation using payment history data: a comparative study of Turkish retail stores

Our paper presents a comparative study applying logistic regression and multiple criteria decision analysis tools to the operations of wholesalers to assess the credit risk of their retailers using payment history data and to cluster the risky customers by ranking their risk levels. Our sample compr...

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Bibliographic Details
Published in:Central European journal of operations research 2013-03, Vol.21 (2), p.479-494
Main Authors: Karan, Mehmet Baha, Ulucan, Aydın, Kaya, Mustafa
Format: Article
Language:English
Subjects:
Analysis
Banking
Bankruptcy
Business and Management
Business failures
Business to business commerce
Comparative analysis
Corporate purchasing
Credit ratings
Credit risk
Customers
Decision-making
Default
Developing countries
Economic models
Economic statistics
Economic theory
Estimation theory
Finance
LDCs
Logistics
Macroeconomics
Methods
Multiple criteria decision making
Operations research
Operations Research/Decision Theory
Original Paper
Payments
Regression analysis
Retail industry
Retail stores
Retailing industry
Risk assessment
Small & medium sized enterprises-SME
Small business
Studies
Wholesalers
Wholesaling
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Summary:Our paper presents a comparative study applying logistic regression and multiple criteria decision analysis tools to the operations of wholesalers to assess the credit risk of their retailers using payment history data and to cluster the risky customers by ranking their risk levels. Our sample comprises approximately 6,000 retailer customers and 600.000 transactions of one of the major wholesalers of Turkey. Our findings emphasize the importance of using payment history and some non-financial factors data for predicting the creditworthiness of a firm.
ISSN:1435-246X
1613-9178
DOI:10.1007/s10100-012-0242-y