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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.<\/jats:p>","DOI":"10.1007\/s12525-024-00746-8","type":"journal-article","created":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T23:51:24Z","timestamp":1737762684000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["SynDEc: A Synthetic Data Ecosystem"],"prefix":"10.1007","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-4432-3557","authenticated-orcid":false,"given":"Fabian Sven","family":"Karst","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahei Manhai","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan Marco","family":"Leimeister","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,1,25]]},"reference":[{"issue":"7","key":"746_CR1","doi-asserted-by":"publisher","first-page":"7","DOI":"10.3390\/jtaer16070180","volume":"16","author":"AE Abbas","year":"2021","unstructured":"Abbas, A. 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