Bank of America is exploring the use of artificial intelligence to reshape its underwriting operations, a move that could fundamentally change how the bank evaluates risk and processes deals. The effort comes as financial institutions increasingly look to machine learning to speed up decision-making and cut costs.
Why underwriting matters
Underwriting is the core of lending and insurance — the process of assessing whether a borrower or investment is worth the risk. For Bank of America, one of the largest U.S. lenders, even small efficiency gains in underwriting can translate into millions of dollars in savings and faster loan approvals for clients. AI could help the bank analyze vast amounts of data — from financial statements to market trends — in a fraction of the time a human analyst would take.
How AI changes the equation
Traditional underwriting relies heavily on manual review and static models. AI systems, by contrast, can continuously learn from new data and spot patterns humans might miss. That could mean more accurate risk assessments, fewer defaults, and a smoother experience for borrowers. The bank hasn't said which specific AI tools it's testing or how far along the exploration is, but the potential is clear: a system that updates its risk models in real-time could give the bank an edge over rivals still using older methods.
Competitive pressure in financial services
Bank of America isn't the only player eyeing AI for underwriting. A growing number of fintech firms and traditional banks are investing in similar technology. If the bank successfully integrates AI, it could tighten its grip on corporate lending, mortgage underwriting, and other product lines where speed and accuracy matter. Analysts following the sector say the shift could widen the gap between early adopters and laggards, though the bank hasn't publicly discussed a timeline for deployment.
What's still unknown
Bank of America hasn't disclosed which underwriting segments might see AI first, nor how the technology would be regulated. Financial regulators have raised questions about bias and transparency in AI-driven credit decisions. The bank will likely need to show that its models comply with fair lending laws before rolling them out broadly. For now, the project remains in the exploratory phase, with no announced pilot or launch date.
