AegisOS Comply exports audit trails in regulator-accepted formats for financial institutions operating across 8+ jurisdictions. Every AI spend decision is documented to the exact standard your regulator expects.
The Reserve Bank of India mandates that financial entities using AI or ML models for customer-facing or automated financial decisions maintain explainable, auditable records of every model output and the rationale behind it.
SEBI requires broker-dealers and financial intermediaries using algorithmic or AI-driven systems for order placement or financial decisions to maintain detailed logs of every system-generated action.
The EU AI Act classifies AI systems used in credit scoring, insurance risk assessment, and financial decisioning as high-risk, triggering mandatory requirements under Articles 9–15 and Article 13 (transparency).
GDPR Article 30 requires data controllers and processors to maintain records of processing activities involving personal data. AI-driven financial decisioning that processes personal data falls under this obligation.
SOX Sections 302 and 404 require public companies to maintain and evaluate internal controls over financial reporting. AI-driven spend decisions that affect financial statements must be traceable, controlled, and auditable.
SOC 2 evaluates controls across Security, Availability, Processing Integrity, Confidentiality, and Privacy. AI spend governance platforms must demonstrate that automated processing is complete, accurate, and authorised.
The SEC has issued guidance requiring investment advisers and broker-dealers to document and disclose conflicts of interest arising from AI-driven decisioning, and to maintain records of all AI-assisted investment or spend decisions.
The FCA Consumer Duty requires firms to deliver good outcomes for retail customers, including ensuring AI-driven systems do not cause foreseeable harm. Firms must monitor, evidence, and report on AI outcomes.
Under SMCR, a named Senior Manager must own accountability for AI-driven systems that affect regulated activities. AegisOS Comply's role-based approval trails support clear accountability mapping.
The MAS TRM Guidelines require financial institutions to establish robust governance and controls over technology systems, including AI models used in financial decisioning.
The MAS FEAT principles provide voluntary but widely adopted standards for responsible use of AI in financial services, focusing on fairness, ethical use, accountability, and transparency of AI-driven decisions.
CPS 234 requires APRA-regulated entities (banks, insurers, superannuation funds) to maintain information security capabilities proportionate to the threats they face, with robust logging of all automated financial system actions.
The CBUAE requires licensed financial institutions to establish governance frameworks for AI systems, ensuring human accountability, explainability, and auditability of AI-driven financial decisions.
Firms operating within the ADGM and DIFC free zones are subject to their own financial services regulators (FSRA and DFSA respectively), both of which require documented governance of AI and automated financial systems.
OSFI B-13 sets expectations for federally regulated financial institutions in Canada regarding the governance, risk management, and controls over technology systems — including AI and algorithmic decisioning.