Synthetic Data for Payment Systems: AI-Powered Privacy-Preserving Testing
In modern banking, ensuring that new payment systems operate accurately and securely requires extensive testing. However, testing with real-world data introduces privacy risks, and synthetic data offers a promising alternative. This paper explores the potential of Generative AI for producing realistic, privacy‑compliant synthetic transaction data. The proposed approach addresses challenges such as data privacy, diverse dataset creation, and the ability to simulate rare or edge-case scenarios—thus enhancing the robustness of payment systems.
Authors
- Prajwalkumar B Bhatkar
Institutions
- Bank of America (US)
- Centre for European Reform (GB)
Publication Details
- Journal
- International Journal of Management Technology
- Published
- 2025-01-15
- DOI
- https://doi.org/10.37745/ijmt.2013/vol12n16776
- Primary Topic
- Privacy-Preserving Technologies in Data
- Type
- article
- Field-Weighted Citation Impact
- 0.00