SCALNYX and CEA List presented their joint research at the Lambda Mu 22 e-congress on risk management, in the digital-transformation session. The paper was entitled: "Privacy-preserving Machine-Learning-as-a-Service (MLaaS) based on homomorphic encryption – Issues and Challenges."
The research
The work examines how Fully Homomorphic Encryption (FHE) can enable Machine-Learning-as-a-Service while keeping the underlying data encrypted throughout the computation. It sets out the main issues and open challenges of building confidential MLaaS — from performance and efficiency to practical deployment in sensitive, regulated environments such as finance.
Building confidential computing for finance
SCALNYX is building one of the fastest and most efficient confidential-computing platforms based on FHE. The collaboration with CEA List — a leading French technological research institute — combines cutting-edge cryptographic research with real-world financial use cases.
Do you have a specific use case in the financial industry, or would you like to know more about this breakthrough technology? We would be happy to partner.