Study Overview
This research proposes a novel decentralized platform enabling privacy-preserving data collaboration and analytics across organizations with private data sources. The platform integrates advanced cryptographic techniques like secure multi-party computation and federated learning to facilitate secure cross-entity data analysis and machine learning for accurate financial auditing, fraud/laundering detection while ensuring data privacy. Its decentralized approach breaks data silos, empowering collaborative insights extraction without compromising privacy and security. The platform simplifies development of privacy-preserving applications, reduces costs, and promotes regulatory compliance. It has broader applications beyond finance for secure cross-organizational analytics through privacy-preserving decentralized computing.
Study Results
Pending
IBSI Funding Acknowledgement: Lab for Inclusive FinTech (LIFT)