DeepVest, the agentic front office for financial advisors, today announced the release of a new white paper, “When AI Meets the Examiner: A Practical Benchmark for Evaluating AI Tools Under the SEC’s FY2027 Priorities and Treasury’s AI Risk Framework.” The research provides registered investment advisors (RIAs) and wealth management professionals with a definitive, three-question framework to help assess the regulatory readiness and reliability of any AI tool before implementation.

With the rapid adoption of general-purpose AI tools across the financial services industry, regulatory scrutiny is intensifying. The SEC’s FY2027 Examination Priorities direct examiners to determine whether a firm’s representations about their automated tools are fair and accurate, and whether firms have proper monitoring procedures in place. Concurrently, the U.S. Treasury’s Financial Services AI Risk Management Framework provides the industry’s most detailed recommendations on adequate AI risk management, including third-party vendor oversight.

“Advisors rushing to adopt general-purpose AI tools to save time are heading into a period of more focused examiner attention,” said Toby Wade, CEO of DeepVest. “The SEC and Treasury have made it clear what they expect regarding AI risk management, but until now, busy fiduciaries lacked a simplified checklist for practical application. We built this benchmark to give advisors a clear view of the big-picture requirements so they can adopt AI confidently, based on evidence, rather than taking vendor marketing claims on faith.”

The white paper addresses a critical gap in the market: the failure of general-purpose AI tools to meet the strict demands of fiduciary accountability. DeepVest’s previous research demonstrated that these tools fail 85% of investment tasks, producing incorrect calculations, hallucinated data or no results at all, and also struggle to provide consistent answers to identical prompts or calculations. “When AI Meets the Examiner” reduces complex regulatory recommendations into a practical benchmark centered on three core principles:

  • Explain It: Can the tool show why it produced an answer, and does it separate what it knows from what it’s guessing?

  • Verify It: Does the tool give the same answer consistently, does performance hold up across different types of clients and market conditions, and is its error rate known?

  • Supervise It: Does the vendor commit in writing to client data protection, independent security audits (such as SOC 2), and complete audit trails?

The benchmark helps advisors collect necessary compliance evidence before an examiner asks, providing a scalable approach depending on the risk level of the AI use case, from low-risk meeting transcriptions to high-risk client proposals. DeepVest applies this exact benchmark to its own platform, utilizing verified institutional data for perfect calculation consistency and SOC 2-certified security protocols that explicitly exclude client portfolio data from model training.

For more information on the white paper and its findings, advisors can contact DeepVest at hello@deepvest.ai or visit deepvest.ai.

About DeepVest:

DeepVest is the agentic front office for wealth management teams. Most firms run their front office on a patchwork of disconnected tools for research, planning, market data, proposals and monitoring. DeepVest unifies that work in a single workspace with five capabilities: AdvisorLab for personalized, compliance-ready client proposals, PlanLab for interconnected financial planning, DataLab for cross-asset market data, AgentLab for conversational investment research and MonitorLab for continuous portfolio and market monitoring. AI runs the workflow while deterministic calculations produce the numbers, so every output is transparent, auditable and traceable to verified institutional data. Advisors, investment teams and compliance work from one source of truth, deliver institutional-depth work for every client and grow the firm faster. For more information, visit deepvest.ai.

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