Enhancing Model Accountability via Automated Lineage Tracking and Cryptographic Proofs of Decision Integrity in Financial AI
DOI:
https://doi.org/10.66280/cis.v4i1.128Abstract
The proliferation of high-frequency algorithmic decision-making within global financial markets has outpaced existing regulatory frameworks, creating an accountability gap that threatens systemic stability and public trust. As financial institutions increasingly deploy opaque artificial intelligence models for credit scoring, risk assessment, and autonomous trading, the inability to reconstruct the exact state of a system at the moment of a specific decision poses significant legal and operational risks. This paper proposes a comprehensive socio-technical architecture designed to enhance model accountability through two primary technological pillars: automated lineage tracking and cryptographic proofs of decision integrity. Automated lineage tracking ensures a continuous, immutable record of data provenance, hyperparameter configurations, and model versions, allowing for granular historical reconstruction. Concurrently, the integration of cryptographic primitives, such as zero-knowledge proofs and secure hardware enclaves, provides a mechanism for verifying that a specific decision was generated by an authorized version of a model without necessitating the exposure of proprietary algorithmic logic. We analyze the structural trade-offs inherent in deploying such a high-integrity infrastructure, specifically the tensions between computational latency, storage overhead, and regulatory transparency. The discussion extends to the governance implications of these technologies, emphasizing how they facilitate "accountability by design" and support compliance with emerging international standards. By examining the intersection of distributed systems, financial regulation, and machine learning, this research offers a robust framework for ensuring that autonomous financial agents remain tethered to human oversight and institutional responsibility, ultimately fostering a more resilient and fair financial ecosystem.
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