{"type":"ScholarlyArticle","title":"Fraud Risk Mitigation in Real-Time Payments: A Strategic Agent-Based Analysis","authors":[{"name":"Katherine Mayo","slug":"katherine-mayo","given":"Katherine","family":"Mayo","affiliation":"University of Michigan"},{"name":"Nicholas Grabill","slug":"nicholas-grabill","given":"Nicholas","family":"Grabill","affiliation":"University of Michigan"},{"name":"Michael P. Wellman","slug":"michael-p-wellman","given":"Michael P.","family":"Wellman","affiliation":"University of Michigan"}],"abstract":"Whereas standard financial mechanisms for payment may take days to finalize, real-time payments (RTPs) provide immediate processing and final receipt of funds. The speed of settlement benefits customers, but raises vulnerability to fraud. We seek to understand how bank nodes may strategically mitigate fraud risk in RTPs, through investment in fraud detection and restricting payments eligible for real-time processing. To study this, we introduce an agent-based model of the payment network supporting both real-time and standard payments, and define a game among banks and fraudsters. Using empirical game-theoretic analysis, we identify Nash equilibria in nine game configurations defined by network attributes. Our analysis finds that as banks become more liable for fraud, they continue to allow RTPs but are more likely to employ both restrictions and a high level of fraud detection. Fraudsters, in response, switch from targeting only RTPs to attempting fraud with any type of payment and tend to exploit banks where they have historically been most successful. We also conduct a strategic feature gains assessment to further understand the benefit offered by each of the bank's risk mitigation measures, which confirms the importance of selective RTP restrictions. Finally, we find that in equilibrium bank strategic decisions negatively affect fraudsters while minimally impacting customers.","doi":"10.24963/ijcai.2024/18","url":"https://ijcai.org/proceedings/2024/18","pdf":"https://ijcai.org/proceedings/2024/0018.pdf","markdown":"https://ijcai.org/proceedings/2024/18.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/18","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Agent-based and Multi-agent Systems","track":"Main Track","number":18,"pages":{"first":157,"last":165},"keywords":["Multidisciplinary Topics and Applications: MTA: Finance","Multidisciplinary Topics and Applications: MTA: Economics","Agent-based and Multi-agent Systems: MAS: Applications"],"videos":[],"references":[{"position":1,"raw":"[Arshadi, 2019] Nasser Arshadi. 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