A Case-Based Reasoning System for Indirect Bank Lending

Abstract

By implementing case-based reasoning (CBR) systems, business organizations can utilize past cases—a key data resource—for future decision making. CBR is particularly suitable for business domains that have available a large amount of historical data. One such domain is indirect bank lending. In this paper, we present a case-based system that operates in the bank lending domain. The system recommends whether an indirect loan application should be approved or denied, based on past experiences. We describe how the system was developed and explain how the system functions. The system was empirically evaluated using actual loan cases. The positive results of the evaluation confirm our hypothesis that CBR is an attractive decision-making methodology for the bank lending domain.