Artificial intelligence (AI) is beginning to transform the world of banking, and one of its biggest impacts may be helping people in rural and underserved areas access credit.
A recent study from the University of Missouri found that banks using AI-based tools are significantly more effective at identifying creditworthy borrowers, particularly in regions with limited financial infrastructure. In places where access to traditional banks is sparse and credit histories can be thin or nonexistent, AI is helping financial institutions make more accurate and inclusive lending decisions.
Traditionally, credit decisions have been based on a narrow set of metrics, with credit scores playing a central role. But AI systems can dig much deeper. Instead of just looking at a borrower’s credit report, these systems can evaluate patterns in income, savings behavior, rent and utility payments, and even how consistently someone pays their phone bill.
According to Brian Sathianathan, Co-Founder and CTO of Iterate.ai and an expert in AI applications, this broader analysis offers a clearer and more complete picture of someone’s financial reliability.
“AI is helping banks make more informed lending decisions by analyzing a broader range of data points beyond just credit scores. It can consider things like income patterns, spending behavior, and on-time payments for utilities or rent, which gives a more accurate and inclusive view of someone’s financial reliability. This is especially important for people who may not have access to traditional credit,” Sathianathan explains.
This approach is particularly valuable for people in rural areas who might not have credit cards or extensive borrowing histories. Many work in agriculture, trades, or seasonal jobs where income isn’t consistent, which is often penalized by traditional credit models.
Sathianathan believes that more inclusive data models can correct for these gaps and help bring more people into the financial system. When AI can recognize responsible financial habits outside of the typical credit framework, it opens doors for borrowers who have long been excluded.
The benefits of this shift aren’t limited to consumers. Financial institutions, especially community banks and credit unions, stand to gain by reducing the number of missed opportunities to lend to creditworthy individuals. When banks can better distinguish between risky and reliable borrowers, particularly in low-density areas, it helps promote local economic growth and strengthens trust in the financial system.
As AI becomes more deeply embedded in financial technology, understanding how these systems work is becoming increasingly important for more than just data scientists. It’s also essential for anyone entering the finance or banking industries. Sathianathan views this as a growing responsibility for young professionals in these fields.
“For young professionals entering tech or finance, understanding how these AI systems work, and how to apply them responsibly, is a smart move. It’s not just about technical skills, but about building tools that create more equitable outcomes,” he says.
Still, with new power comes new challenges. Financial advocates have raised concerns that if AI models are built using biased data, they could reinforce inequalities rather than reduce them. Transparency in how decisions are made, and clear explanations for loan approvals or rejections, are crucial to building trust and avoiding hidden discrimination.
Rather than blindly trusting AI, banks need to ensure the tools they use are designed with fairness in mind and regularly audited for unintended bias. That includes being clear with borrowers about the types of data being used in decision-making and giving them recourse if they believe an error was made.
The University of Missouri study shows a promising path forward: a future where credit access is based on a more holistic view of financial health, rather than just a number on a report. If implemented thoughtfully, AI could help reshape lending into a more just and accessible system, particularly for those living far from traditional financial centers.
With continued innovation and careful oversight, artificial intelligence may not only improve lending but also help redefine financial inclusion for millions of Americans.
