Today, Finance Watch, a non-profit association
dedicated to reforming finance in the interest of European citizens, published
a new report: 'Artificial intelligence in finance:
how to trust a black box?' authored by its Chief Economist Thierry
Philipponnat.
As AI-powered systems increasingly drive financial
decision-making in areas such as creditworthiness assessments, insurance pricing and
investment products, the report asserts that the core principles of financial regulation
accountability, responsibility, and transparency are being tested.
Against this backdrop, the report identifies several
critical concerns:
- Lack
of transparency: AI models operate as “black
boxes”, generating outputs without clear explanations of their reasoning,
making human oversight and intervention impossible.
- Consumer protection under threat: In retail finance, the deployment of AI could lead to opaque creditworthiness assessments (see for an example here), pricing discrimination, discriminatory lending, and misleading financial advice.
- Supervisors
face AI challenges: Supervisors tasked with enforcing
regulation face challenges in keeping pace with financial institutions'
deployment of AI and delivering on their mandates.
- Market stability is at risk: Increasingly dependent on third-party AI providers, financial institutions face operational risks from unregulated external systems and concentration risks, where a handful of dominant AI firms control critical models and infrastructure, creating systemic vulnerabilities.
As a response, the report urges a reassessment of the
financial regulation framework:
- Expand
the scope of the AI
Act to cover all financial services
- Establish
a clear liability
regime that holds providers of AI-powered services
accountable for damages caused by an output of an AI system
- Conduct a regulatory gap analysis to ensure all AI-driven financial activities are adequately regulated.
