Limits of Artificial Intelligence in Trust-Critical Financial Systems: Deterministic Verification as a Complementary Control Layer

Artificial intelligence (AI) is increasingly applied to fraud detection, compliance monitoring, and risk assessment in financial systems. While effective at pattern recognition and probabilistic inference, AI-based approaches are inherently non-deterministic and retrospective, limiting their suitability as primary trust or compliance mechanisms in regulated, adversarial environments. This paper formally distinguishes the guarantees AI systems can and cannot provide, and introduces deterministic verification architectures—illustrated through a rule-layer validation framework—as a complementary control layer capable of delivering provable trust, accountability, and auditability. The analysis establishes a clear functional boundary between probabilistic intelligence and enforceable governance.