SynDEc: A Synthetic Data Ecosystem
Fabian Sven Karst (),
Mahei Manhai Li () and
Jan Marco Leimeister ()
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Fabian Sven Karst: University of St.Gallen, Institute of Information Systems and Digital Business
Mahei Manhai Li: University of St.Gallen, Institute of Information Systems and Digital Business
Jan Marco Leimeister: University of St.Gallen, Institute of Information Systems and Digital Business
Electronic Markets, 2025, vol. 35, issue 1, No 7, 28 pages
Abstract:
Abstract Given the critical role of data availability for growth and innovation in financial services, especially small and mid-sized banks lack the data volumes required to fully leverage AI advancements for enhancing fraud detection, operational efficiency, and risk management. With existing solutions facing challenges in scalability, inconsistent standards, and complex privacy regulations, we introduce a synthetic data sharing ecosystem (SynDEc) using generative AI. Employing design science research in collaboration with two banks, among them UnionBank of the Philippines, we developed and validated a synthetic data sharing ecosystem for financial institutions. The derived design principles highlight synthetic data setup, training configurations, and incentivization. Furthermore, our findings show that smaller banks benefit most from SynDEcs and our solution is viable even with limited participation. Thus, we advance data ecosystem design knowledge, show its viability for financial services, and offer practical guidance for privacy-resilient synthetic data sharing, laying groundwork for future applications of SynDEcs.
Keywords: Synthetic data; Data sharing platform; Data ecosystem; Financial services; Data scarcity (search for similar items in EconPapers)
JEL-codes: M15 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s12525-024-00746-8
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