Financial institutions operate under strict privacy, audit, and governance rules. Transaction data cannot be shared across banks; customer histories cannot be moved freely; and external compute environments must be tightly controlled. Many risk, fraud, and credit-scoring models contain proprietary logic that institutions prefer not to expose. At the same time, effective AI often requires broader visibility than any one organization possesses.
Super allows banks, payment networks, and financial partners to run joint or sensitive AI workloads without sharing raw transactions or exposing model internals. Each institution keeps its data within its own systems while participating in shared analytics or model training in a protected way. Workloads can run in cloud or hybrid environments while maintaining technical separation from the underlying platform, and proprietary models can be deployed to partners without revealing internal structure.
Financial institutions can collaborate on fraud, risk, and compliance workloads and adopt cloud-based AI without exposing customer data, model IP, or internal processes.
