In January 2022, National FinTech Evaluation Center (NFEC, also well-known as Bank Card Test Center or BCTC) completed the first batch of federated learning financial application evaluation. The evaluation is tested for federated learning functions, security, and performance, of which 9 products have passed the federated learning financial application product evaluation.
Federated Learning and Assessment Services
Federated learning, as an important branch of privacy computing, can effectively solve the contradiction between data circulation sharing and privacy security. On the premise of meeting the requirements of security, privacy protection and regulatory compliance, the data can realize the data integration and circulation, multi-party coordination, and fully release the value of the data.
Currently, federated learning is widely used in the financial industry. BCTC, together with many manufacturers in the field of privacy computing security, has developed the Federated Learning Financial Application Technical Requirements (Q/BCTC 0002-2022) after a year of joint efforts. The requirements for federated learning products in terms of function, security, and performance are proposed in this specification, which provides a reference basis for the evaluation of federated learning financial application products.
BCTC will continue to carry out multi-party secure computing products, federated learning products, and other privacy computing-related financial measurement services. BCTC will continue to explore the construction of technical systems including Differential Privacy, Trusted Execution Environment, and Consortium Blockchain. BCTC welcomes more companies to participate and work together to ensure the stable development of financial data security convergence applications.