Regional and community banks and credit unions surveyed by PYMNTS Intelligence now report behavioral analytics and artificial intelligence adoption approaching the levels seen with large banks, although their financial results remain uneven.
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The research underlying September’s “Scams Get Personal: Why Banks Pay More to Fight Fraud” shows behavioral analytics use among these institutions rising from 74% in 2025 to 100% in 2026. Machine learning and AI adoption increased from 77% to 96%. Large banks reported universal use of both technologies in both years.
Earlier purchases can supply context for evaluating a transaction that appears unusual in isolation. Whether that information supports approval depends on the institution’s controls and the other risk signals available.
In PYMNTS’ coverage, Nilesh Dusane, global head of institutional payments at AWS, described payment models that analyze transaction sequences. A plane ticket followed by hotel and restaurant purchases, for example, supplies context for evaluating subsequent spending.
The approach illustrates how institutions using the same technology category could reach different decisions. The information available to a model and its ability to interpret relationships among transactions can affect its assessment. The coverage describes the capability without supplying comparative fraud loss results.
Customer history also has limits. A familiar device or valid login cannot establish whether a customer is following a scammer’s instructions. 4% of fraudulent dollar value in the bank research, up from 12% in 2025. Banks must account for payments initiated by deceived customers as well as transactions started by intruders.
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