Federated Machine Learning Outperforms Centralized Machine Learning for Fraud Detection: Evidence From 284,807 Real-World Transactions
Samuel Sambasivam
- Published
- Publisher
- Informing Science Institute
- Journal / collection
- Issues in Informing Science and Information Technology
- Research area
- AI & compute
- Source type
- Journal article
- DOI
- 10.28945/5799
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Cite this source
Samuel Sambasivam. Federated Machine Learning Outperforms Centralized Machine Learning for Fraud Detection: Evidence From 284,807 Real-World Transactions. Issues in Informing Science and Information Technology. 2026. https://doi.org/10.28945/5799