Abstract
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.
Highlights
Financial industries are currently undergoing a change process that many researchers consider as digital transformation
As the problem relevance investigation confirms the need for changes in Instant payment (IP) fraud detection, we propose an initial design of the envisioned technological support, i.e. the Artificial intelligence (AI) component
Since the resulting score is a multiplication of all scores and amount value, it is correct to assume that detection time for the global profile is constant, as it only depends on how results of the profile creation are stored
Summary
Financial industries are currently undergoing a change process that many researchers consider as digital transformation. From a business-centric perspective, digital transformation focuses in general on the transformation of products, processes, and organizational aspects triggered by new technologies [1] This opens up a variety of opportunities for changing business models and value chains in order to meet constantly increasing customer requirements and offer services faster, more intelligently and more efficiently. Examples for new products and services are robot advisory and auto-trading, value-added services based on account information and transaction history, or ad-hoc loans in online-banking.
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