When AI Disrupts the Borrower: Why Banks Are Rethinking Lending Risk
Artificial intelligence is transforming industries at breathtaking speed—but for lenders, that rapid disruption is creating a new kind of uncertainty.
At a recent Bloomberg Invest conference, Mahesh Saireddy, co-head of the Capital Solutions Group at Goldman Sachs, warned that AI-driven disruption could make corporate lending decisions significantly more complicated over the next two years. (Reuters)
AI Is Rewriting Business Models—and Risk Models
Traditionally, banks evaluate loans based on predictable factors: company revenues, market stability, industry outlook, and historical performance. But AI is now reshaping entire industries faster than financial models can adapt.
Saireddy noted that uncertainty around how AI will transform businesses is making it harder for lenders to assess risk. For the next 6 to 24 months, banks may face a period of “unknowns” that complicate underwriting decisions. (Reuters)
The concern isn’t limited to technology companies. AI disruption is expected to ripple across multiple sectors—from software and finance to manufacturing and services—forcing lenders to reassess which business models remain sustainable. (Reuters)
The Shock Is Already Reaching Financial Markets
The ripple effects are already visible in capital markets. According to market observers, fears about AI-driven disruption have spread from equity markets into credit markets and corporate financing. (Investing.com Australia)
Some software stocks and asset managers heavily exposed to AI-related investments have seen volatility, raising questions about future earnings and loan repayment capacity. As a result, lenders must now consider a new risk factor: technological obsolescence caused by AI.
In essence, banks must ask a new question before approving loans: Will this company still be relevant in an AI-powered economy?
AI’s Paradox for Finance
Ironically, while AI complicates lending decisions, it is also transforming banking operations themselves.
Major banks—including Goldman Sachs—are experimenting with AI tools to automate processes such as client onboarding, document drafting, and financial analysis. In some cases, executives have suggested that AI could perform a large share of routine banking work in the future. (Yahoo Finance)
This creates a paradox: AI is both a productivity engine and a risk amplifier.
Banks must embrace AI internally while simultaneously evaluating how it may disrupt their borrowers’ industries.
A New Era of Credit Risk
The next phase of finance may require lenders to develop entirely new frameworks for evaluating companies—ones that factor in technological disruption, AI adoption readiness, and competitive resilience.
For banks and investors alike, the real challenge isn’t just understanding AI itself. It’s predicting who will survive the transformation AI brings.
In the coming years, credit analysis may evolve from purely financial modeling into something closer to technological foresight.
Glossary
Artificial Intelligence (AI) Computer systems capable of performing tasks that normally require human intelligence, such as learning, reasoning, and decision-making.
Underwriting The process banks use to evaluate the risk of lending money to a borrower.
Credit Markets Financial markets where companies and governments raise funds through debt instruments such as bonds or loans.
Capital Solutions Group A banking division that structures financing deals and provides lending to corporate clients.
Source: https://www.techinasia.com/news/goldman-sachs-executive-ai-may-complicate-lending-decisions
