The Global Drive for AI Governance
Policymakers worldwide are moving from discussion to implementation of AI rules. The push is driven by concerns about safety, market stability, systemic risk and consumer protection. For finance and technology leaders, regulatory moves are not an academic issue. They alter product roadmaps, vendor choices and capital allocation.
Contrasting Regulatory Frameworks
EU AI Act’s Benchmark Approach
The EU AI Act uses a risk-based model that assigns obligations according to the potential harm of a system. High-risk AI systems face mandatory risk management, documentation, transparency measures and pre-market conformity assessments. Penalties for non-compliance can be substantial, and the Act is fast becoming a de facto standard for international suppliers who want access to EU markets. For financial firms, this means early classification of models and documented controls for decisioning, scoring and automated advice.
US Strategy – Innovation and Responsibility
The US has favored a mix of federal guidance, agency action and Executive-level directives that prioritise innovation and national security while calling for responsible deployment. Agencies such as NIST, the FTC and sectoral regulators like the SEC have issued or signalled expectations on model risk management, bias mitigation and transparency. The result is a more sector-specific, less prescriptive landscape than the EU, but states and agencies are filling gaps, creating a patchwork of obligations firms must track.
Industry Impact and Future Outlook
For financial services the immediate implications are practical: stronger model governance, audit trails for training data, third-party vendor oversight and clearer explainability for customers and regulators. Compliance costs may rise, but so will demand for governance tools and certification services. In the short to medium term expect more harmonisation on technical standards, rising enforcement actions and clearer supervisory expectations.
Actionable priorities for leaders: map AI assets and risk tiers, implement documented model governance, update vendor contracts for compliance clauses and monitor evolving standards. Firms that align governance with product strategy will be better positioned to compete as regulatory expectations mature.
