FRAUD PREDICTION IN BANK CREDIT ADMINISTRATION: A SYSTEMATIC LITERATURE REVIEW
Loading...
Date
2019-06
Journal Title
Journal ISSN
Volume Title
Publisher
Journal of Theoretical and Applied Information Technology
Abstract
Any business or organization that intends to be far from bankruptcy or crime strives daily to ensure crime
perpetration does not occur in the organization unabated. Traditional methods of fraud detection in credit
administration are available but limited in capacity to check current sophistication in fraud perpetration;
those approaches did not offer the best for time-consumption and efficiency; also, frauds are better
predicted rather than a detection after the deal is done. This work presents an extensive review of literature
and related works in fraud prediction in credit administration. The primary focus of this research work is to
identify and dwell on the major concepts and techniques used for financial fraud prediction in credit
administration as well as related works that have been done in this domain of study; while the work
recommends the ensemble approach as a better alternative in this domain. The existing systematic literature
reviews in this domain are not in the context of credit fraud prediction alone.
Description
Staff Publication
Keywords
Fraud,, Supervised learning,, Credit,, Ensemble,, Machine learning