The financial industry is becoming increasingly reliant on AI, but its core pain points remain: Are the model results fair and transparent?
For example, credit approval systems may be unfair to certain groups due to biases in training data; anti-fraud models may be questioned for having black box operations. These issues not only undermine user trust but also make it difficult for regulators to fully allow AI to dominate critical processes.
Lagrange's DeepProve technology was born for this purpose. It allows AI to attach a zero-knowledge proof when outputting results, demonstrating that the model's reasoning process complies with established rules and has not been tampered with. This way, banks can ensure compliance in their decisions while reducing communication costs with regulators.
With further advancements in Proofs of Training, financial alliances can jointly train risk control models without sharing customer privacy, generating verifiable compliance proofs. This makes collaboration both safe and efficient.
On the economic incentive side, the $LA token serves as the core for task allocation and validation rewards, ensuring the robust operation of the entire verification network.
Lagrange is establishing a new trust benchmark for the financial industry.
