콘텐츠 본문
논문 국내 국내전문학술지(KCI급) Detecting Credit Loan Fraud Based on Individual-Level Utility
- 학술지 구분 국내전문학술지(KCI급)
- 게재년월 2012
- 저자명 Keunho Choi, Gunwoo Kim, and Yongmoo Suh
- 학술지명 지능정보연구
- 발행처명 한국지능정보시스템학회
- 발행국가 국내
- 논문언어 외국어
- 전체저자수 3
논문 초록 (Abstract)
As credit loan products significantly increase in most financial institutions, the number of fraudulent transactions is also growing rapidly. Therefore, to manage the financial risks successfully, the financial institutions should reinforce the qualifications for a loan and augment the ability to detect a credit loan fraud proactively. In the process of building a classification model to detect credit loan frauds, utility from classification results (i.e., benefits from correct prediction and costs from incorrect prediction) is more important than the accuracy rate of classification. The objective of this paper is to propose a new approach to building a classification model for detecting credit loan fraud based on an individual-level utility. Experimental results show that the model comes up with higher utility than the fraud detection models which do not take into account the individual-level utility concept. Also, it is shown that the individual-level utility computed by the model is more accurate than the mean-level utility computed by other models, in both opportunity utility and cash flow perspectives. We provide diverse views on the experimental results from both perspectives.
