Loan payment prediction using rough sets

Authors:
Bahadtin Ruzgar;Nursel Selver Ruzgar
Affiliations:
Banking and Insurance School, Actuaries Department, Marmara University, Kadikoy, Istanbul, Turkey;Vocational School of Social Sciences, Marmara University, Eminonu, Istanbul, Turkey
Venue:
MATH'08 Proceedings of the American Conference on Applied Mathematics
Year:
2008

Citing 2
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Rough Sets: Theoretical Aspects of Reasoning about Data

Rough Sets: Theoretical Aspects of Reasoning about Data
Genetic programming for the prediction of insolvency in non-life insurance companies

Computers and Operations Research

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Abstract

In small business loans, there is always a risk for nonpayment or non-refunding of loans though very detailed examinations are made about the company. In this study, behaviors that increase the risk in loans or causing non-refunding are tried to be determined by using the rough set approach. This paper will demonstrate that rough sets model is applicable to a wide range of practical problems pertaining to loan payment prediction. Moreover, the results show that the rough sets model is a promising alternative to the conventional methods for financial prediction.