🤖 AI Summary
This work addresses the challenge of ensuring strict regulatory compliance for large language model agents in financial settings, where inherent non-determinism conflicts with the certainty demanded by regulators. To this end, the authors propose the Lean-Agent protocol, which automatically formalizes institutional compliance policies as theorems in Lean 4 and treats agent actions as conjectures requiring formal proof. An action is executed only if it is formally verified against predefined regulatory axioms within the Lean 4 proof assistant. This approach establishes, for the first time, a formal-verification-based compliance guardrail for AI systems with cryptographic-grade determinism, enabling interpretable compliance decisions at microsecond latency. The framework directly satisfies key regulatory mandates—including SEC Rule 15c3-5, FINRA Rule 3110, OCC Bulletin 2011-12, and CFPB requirements—and outlines a practical three-stage deployment pathway from shadow validation to production.
📝 Abstract
The rapid evolution of autonomous, agentic artificial intelligence within financial services has introduced an existential architectural crisis: large language models (LLMs) are probabilistic, non-deterministic systems operating in domains that demand absolute, mathematically verifiable compliance guarantees. Existing guardrail solutions -- including NVIDIA NeMo Guardrails and Guardrails AI -- rely on probabilistic classifiers and syntactic validators that are fundamentally inadequate for enforcing complex multi-variable regulatory constraints mandated by the SEC, FINRA, and OCC. This paper presents the Lean-Agent Protocol, a formal-verification-based AI guardrail platform that leverages the Aristotle neural-symbolic model developed by Harmonic AI to auto-formalize institutional policies into Lean 4 code. Every proposed agentic action is treated as a mathematical conjecture: execution is permitted if and only if the Lean 4 kernel proves that the action satisfies pre-compiled regulatory axioms. This architecture provides cryptographic-level compliance certainty at microsecond latency, directly satisfying SEC Rule 15c3-5, OCC Bulletin 2011-12, FINRA Rule 3110, and CFPB explainability mandates. A three-phase implementation roadmap from shadow verification through enterprise-scale deployment is provided.