The biggest concern for financial institutions when adopting AI is whether the "model is reliable." Once the risk control system makes a mistake, it can trigger systemic risk, and the black-box nature of AI reasoning makes it difficult to meet strict compliance and auditing requirements.
Lagrange's DeepProve precisely addresses this pain point. It can generate zero-knowledge proofs for each AI inference, proving that the results indeed come from established logic rather than tampering or errors. This allows banks and securities firms to validate AI outputs without disclosing sensitive data. For example, a trading risk control AI can come with proof showing that its signals indeed originate from real market data inputs.
This mechanism significantly lowers the adoption threshold for the financial industry. It transforms AI from an uncontrollable black box into an auditable and verifiable risk control engine. As compliance requirements become increasingly stringent, DeepProve is expected to become an essential tool for financial institutions deploying AI.
