Visa, Mastercard to Use AI Credit Scoring for SMB Loans
Visa and Mastercard are moving to use AI-based, non-financial credit scoring to widen access to small-business loans, a shift that could bring more merchants into the formal lending system while changing how banks, lenders and payments networks assess risk.
The immediate economic significance is that credit decisions for small firms — often starved of collateral, audited accounts or long operating histories — may become faster and less dependent on traditional balance-sheet tests. For banks and alternative lenders, that could expand the addressable market at a time when competition for higher-quality borrowers is intense and growth in consumer credit is more cyclical. For the broader economy, easier funding for small businesses can support hiring, inventory purchases and cash-flow management, particularly in markets where MSME lending remains constrained.
The move fits a broader push across financial services to fold AI into underwriting and customer engagement. Revolut has launched an AI financial assistant, while digital lenders such as JuanHand are expanding top-up loan capacity. In emerging markets, governments are also pushing to improve MSME financing, underscoring how access to credit has become a policy as well as a commercial issue. The attraction for lenders is obvious: non-financial data — transaction histories, payment behavior, cash-flow patterns and platform usage — can improve model precision where conventional credit files are thin or stale.
That said, the opportunity comes with trade-offs. AI-driven underwriting can broaden inclusion, but it also raises questions about explainability, model drift and regulatory scrutiny, especially if automated decisions are based on data sets that are harder for borrowers to challenge. Fraud risks may also rise as AI tools proliferate through the credit chain. For incumbent lenders, the upside is better loss selection and a larger origination funnel; the downside is pressure on margins if the new models become a commodity and the easiest credit is already being picked over.
For Visa and Mastercard, the story is less about becoming lenders themselves than about embedding deeper into the credit workflow. That matters because the payments giants benefit when more merchants transact, borrow and repay through their networks. The more their data can help lenders make decisions, the more central they become to small-business finance. Investors should watch whether pilot programs turn into scale, and whether the gains in origination are matched by stable credit performance.
If the pilots prove effective, the winner could be small businesses that have been turned away by conventional underwriting, along with lenders seeking better risk pricing. The losers may be slower-moving banks, as well as borrowers whose data privacy or credit outcomes become more opaque.
| Entity | Gains | Losses |
|---|---|---|
| Small businesses | ▲Easier loan access | ▼More data scrutiny |
| Visa/Mastercard | ▲Deeper network role | ▼Higher regulatory exposure |
| Banks/lenders using AI | ▲Better underwriting reach | ▼Margin pressure |
| Traditional credit models | ▲— | ▼Relevance and pricing power |