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Blockchain-enforced data lineage architectures with formal verification workflows enabling auditable AI decision chains across regulated fintech compliance regimes and supervisory reporting
Deloitte, Lagos, Nigeria.
Review
International Journal of Science and Research Archive, 2023, 09(02), 1201-1217.
Article DOI: 10.30574/ijsra.2023.9.2.0559
Publication history:
Received on 06 June 2023; revised on 24 July 2023; accepted on 29 July 2023
Abstract:
Blockchain-enforced data lineage architectures are emerging as a foundational framework for creating transparent, traceable, and tamper-resistant AI decision pipelines in regulated financial environments. At a broad level, these architectures leverage distributed ledger technology to record, timestamp, and cryptographically secure data transformations across the entire lifecycle of model development, deployment, and monitoring. This immutable lineage ensures that every dataset, parameter update, model version, and inference output can be independently validated and audited. Such transparency is critical as fintech ecosystems increasingly rely on algorithmic decision-making for credit scoring, fraud detection, payments compliance, and automated supervisory reporting. Formal verification workflows complement blockchain-based lineage by providing mathematically rigorous methods for validating model behavior, data handling processes, and regulatory rule adherence. These workflows introduce provable guarantees that decision logic aligns with sector-specific compliance mandates, including explainability requirements, anti-money laundering directives, consumer protection obligations, and stress-testing standards. By combining cryptographic audit trails with verified decision rules, organizations can produce auditable AI decision chains that withstand scrutiny from both internal assurance teams and external regulators. Within supervisory reporting contexts, blockchain-enforced lineage enables real-time attestations of data provenance, model accuracy benchmarks, and control effectiveness. This reduces reliance on manual reconciliation procedures, minimizes compliance gaps, and improves the reliability of regulatory disclosures. Ultimately, the integration of blockchain-backed transparency and formal verification strengthens trust among financial institutions, regulators, and consumers. It provides a robust path toward responsible AI adoption, promoting accountability while preserving the efficiency and predictive value of advanced machine learning systems. This architecture supports scalable, compliant, and secure AI governance in complex global fintech environments.
Keywords:
Blockchain Data Lineage; Formal Verification; Auditable AI; Fintech Compliance; Supervisory Reporting; Algorithmic Accountability
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
