Use of an Analytical Hierarchy Process (AHP) to Improve the Quality of a Credit Scoring Model

• Main Authors: Huang, Wen-Yen, 黃文彥
• Other Authors: Yang, Chyan
• Format: Others
• Language: en_US
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/pt6g9x

博士 === 國立交通大學 === 經營管理研究所 === 105 === A credit scoring model integrates a statistical method with the opinions of an expert group and therefore contains a combination of risk factors and weights. The assignment of weights in the modeling processes is a central interest of and a prime challenge for most financial institutions. Traditionally, an expert group determines the weights in accordance with the experts’ views on the importance of the various risk factors. However, the group’s members often have conflicting objectives (i.e., risk minimization vs. market share maximization) and can be dominated by a single dominating opinion maker, which leads to bias and poor model performance. The analytic hierarchy process (AHP) is a multiple-criteria decision-making tool that has been successfully used in various fields. This study is the pioneer to apply the AHP method to the credit scoring process to create a model that increases the predictive power. The study then tests the AHP model in a case study and compares the results with existing scoring techniques. The findings suggest that the AHP scoring model significantly improves the credit scoring model’s predictive ability.