AI Workflows Are Reshaping Capital Markets Finance and Risk Management

A capital markets CFO cannot wait for quarter-end to determine the return on the balance sheet. [1] The balance sheet continually carries market, funding, and liquidity risk, which is priced position by position throughout the day. [1] Various numbers originate from different systems, including desk P&L, treasury funding curves, and risk engines. [1] Increasingly, these numbers are shaped by AI-informed workflows that span pricing, funding, and risk. [1]

Volatility has increased, and trading books are turning over faster. [1] Additionally, Basel III Endgame and the Fundamental Review of the Trading Book (FRTB) elevate the capital needed to support market risk. [1] Depending on modeling approaches, jurisdiction, and portfolio composition, the FRTB standardized approach can materially impact market-risk capital requirements. [1] AI agents are now embedded across the trading book in processes like pricing workflows, funding recommendations, and surveillance, affecting funding, capital, liquidity, and valuation decisions concurrently. [1]

The integration of AI into capital markets finance indicates a shift toward more complex, interconnected risk and funding models. As regulatory frameworks like FRTB and Basel III Endgame place stricter capital requirements on trading books, firms are relying on AI to manage the resulting data complexity across various intraday systems. This evolution demands that finance teams not only understand traditional risk metrics but also the AI agents generating them. What the sources don't address: How regulators plan to audit or oversee the AI agents that are increasingly shaping these critical capital and liquidity decisions.