FSB finalizes 12 AI practices for financial firms
Several financial institutions use AI to support robo-advisory services, from customer profiling and investment planning to portfolio management and rebalancing. Some large asset managers use AI tools to speed up compliance reviews of marketing materials.
One case study features a global asset manager whose AI tool reviews investment documents, checks proposals against approved mandate rules and produces an initial risk assessment within hours. A person still makes the call. The tool “does not approve or reject investments and final accountability remains with the risk manager.” The FSB says its case studies are illustrations, not benchmarks.
The client risks worth a second look
The report also flags consumer protection and market conduct risks that may apply to investor protection as well. One item deals directly with advice: “Potential for mis-selling and unsuitable recommendations: The use of AI in customer-facing applications, including robo-advisory and product targeting, may lead to recommendations that are unsuitable or not aligned with customers’ risk profiles, particularly where models rely on incomplete, outdated or improperly calibrated data.”
Leaning harder on AI in marketing, advisory and customer engagement may also blur who is responsible for what, the FSB says, which may make misconduct harder to catch quickly. And if firms don’t clearly disclose AI’s role, customers may struggle to understand or challenge decisions that affect them.
Autonomous AI agents get attention too. The report says they may take unauthorized or erroneous actions, and that sound practices specific to agentic AI and multi-agent systems “remain nascent.”
