1. United States
2. N.Y.
3. Letter

I am writing as a concerned constituent to urge Congress to take a proactive role in regulating the use of artificial intelligence in credit underwriting, risk modeling, and capital markets—particularly as it relates to private equity financing. We are currently seeing a dangerous convergence of trends that should feel uncomfortably familiar. Private equity firms are being extended enormous amounts of credit at bond rates that assume A+–level risk, despite underlying leverage, opaque structures, and aggressive assumptions. Increasingly, these risk assessments are being driven or materially influenced by AI models that are not transparent, not standardized, and not subject to meaningful regulatory scrutiny. This mirrors the structural failures that led to the subprime mortgage crisis. Then, complex models, flawed assumptions, and incentive misalignment resulted in systemic underestimation of risk. Today, AI is accelerating that same dynamic—at greater speed and scale. When AI models are trained on historical data that does not reflect current market stress, liquidity constraints, or correlated downside risk, they can amplify rather than mitigate systemic fragility. The concern is not AI itself. The concern is unchecked reliance on AI in high-stakes financial decision-making without: • Clear standards for model governance and validation • Transparency into inputs, assumptions, and limitations • Accountability for firms that outsource risk judgment to automated systems • Regulatory visibility into how these tools are shaping credit ratings and capital allocation If left unaddressed, this creates moral hazard. Capital providers believe risk has been “priced correctly,” while real exposure is quietly concentrated. When the cycle turns, losses will not stay contained within private markets—they will spill into pensions, insurance portfolios, and public markets, just as they did in 2008. I urge Congress to consider targeted legislation and oversight that addresses: 1. The use of AI in credit and risk modeling for leveraged finance 2. Disclosure requirements around AI-driven rating and underwriting processes 3. Stress-testing and independent validation standards for AI models used at scale 4. Inter-agency coordination to monitor systemic risk emerging from private markets Waiting until a crisis forces action will be too late. We have an opportunity to learn from history rather than repeat it—with faster tools and higher stakes. Thank you for your time and for taking this issue seriously. I would welcome any efforts your office undertakes to explore this risk further.