Fraud Detection in Payments Transactions: Overview of Existing Approaches and Usage for Instant Payments

2019
Alexander Diadiushkin, Kurt Sandkuhl, Alexander Maiatin

Financial industries are undergoing a digital transformation of their products, services, overall business models. Part of this digitalization in banking aims at automating most of the manual work in payment handling and integrating the workflows of involved service providers. The focus of the work presented in this paper is on fraud discovery and steps to fully automate it. Fraud discovery in financial transactions has become an important priority for banks. Fraud is increasing significantly with the expansion of modern technology and global communication, which results in substantial damages for the banks. Instant payment (IP) transactions cause new challenges for fraud detection due to the requirement of short processing time. The paper investigates the possibility to use artificial intelligence in IP fraud detection. The main contributions of our work are (a) an analysis of problem relevance from business and literature perspective, (b) a proposal for technological support for using AI in fraud detection of instant payment transactions, and (c) a feasibility study of selected fraud detection approaches.

Keywords
Artificial Intelligence; Enterprise Modeling; Digital Transformation; Instant Payment
DOI
10.7250/csimq.2019-20.04
Hyperlink
https://csimq-journals.rtu.lv/article/view/csimq.2019-20.04

Diadiushkin, A., Sandkuhl, K., Maiatin, A. Fraud Detection in Payments Transactions: Overview of Existing Approaches and Usage for Instant Payments. Complex Systems Informatics and Modeling Quarterly, 2019, No. 20, pp. 72-88. e-ISSN 2255-9922. Available from: doi:10.7250/csimq.2019-20.04

Publication language
English (en)