Classification Model for Detecting and Managing Credit Loan Fraud Based on Individual-Level Utility Concept
- Authors
- Choi, Keunho; Kim, Gunwoo; Suh, Yongmoo
- Issue Date
- 8월-2013
- Publisher
- ASSOC COMPUTING MACHINERY
- Keywords
- Utility-Sensitive Classification; Individual-Level Utility; Credit Loan Fraud; Fraud Detection
- Citation
- DATA BASE FOR ADVANCES IN INFORMATION SYSTEMS, v.44, no.3, pp.49 - 67
- Indexed
- SSCI
SCOPUS
- Journal Title
- DATA BASE FOR ADVANCES IN INFORMATION SYSTEMS
- Volume
- 44
- Number
- 3
- Start Page
- 49
- End Page
- 67
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/102553
- ISSN
- 0095-0033
- 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 and manage 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 two-fold: (1) to propose a new approach to building a classification model for detecting credit loan fraud based on an individual-level utility, and (2) to suggest customized interest rate for each customer - from both opportunity utility and cash flow perspectives. Experimental results show that our proposed 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 from our model is more accurate than the mean-level utility used in previous researches, from both opportunity utility and cash flow perspectives. Implications of the experimental results from both perspectives are provided.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - Korea University Business School > Department of Business Administration > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.