How AI and Real-Time Data are Reshaping Small Business Lending

Highlights: 

• AI, specifically agentic AI, is enabling lenders to accelerate credit decisioning, processing tasks like credit checks in about eight minutes instead of four to eight hours.

• Integrating alternative and real-time data, such as cash flow and supplier-vendor payments, allows AI systems to rapidly generate a more complete view of a small business's health, leading to faster, safer, and more inclusive lending decisions.

In the rapidly evolving landscape of financial services, small business lending stands at a critical juncture. The traditional methods of credit evaluation, often slow and hard to understand, are giving way to a revolution powered by Artificial Intelligence (AI) and instantaneous data access. 

AI is no longer a futuristic concept; it's a present-day reality for small businesses right now. A recent survey from Goldman Sachs showed that about 76% of small businesses already use some form of AI.¹ While initial adoption focused on optimizing back-office processes, the true game-changer is its move into front-office functions like credit decisioning. 

The introduction of agentic AI—specialized AI agents that break down complex underwriting problems into discrete, manageable tasks -- allows for both the speed of automation and the thoroughness of manual review. Organizations are rethinking how data supports AI shifting from fragmented documents to structured usable assets aka data products. Data foundation is fundamental to scalable AI solutions because if it is weak, Agentic AI won’t just make incorrect decisions, it magnifies them. AI just scales whatever data you give it - good or bad.

The impact is profound: tasks like credit checks, which once required a human to dedicate four to eight hours, are now being processed in about eight minutes. This massive reduction in turnaround time is a competitive necessity, enabling lenders to serve small businesses at the speed of their operational reality.

For lenders evaluating small businesses, especially those with little credit history or "thin files"—the right data is very important. Alternative and real-time data are essential, which includes real-time cash flow metrics, banking transactions, and invoicing patterns -- offers a dynamic snapshot of a business' health, far beyond what traditional credit scores can provide.

Supplier-vendor payments data offers invaluable insight into a business’ operational health, liquidity, and payment behaviors. By integrating these different data streams, AI systems can help rapidly generate a more complete view of a customer's total exposure across an entire bank, potentially leading to safer, faster, and more inclusive lending decisions. This capability is critical for unlocking capital for businesses that might otherwise be overlooked by systems reliant on static, historical data. The shift to cloud-based data accessibility is accelerating this transition, making real-time credit evaluation scalable and easy for lenders to use anywhere.

As AI becomes more common, we must use it carefully. Here are a few main goals to keep in mind:

• Accountability and the Human-in-the-Loop: Humans must retain the ultimate authority for authorizations and oversight, ensuring the AI acts as a sophisticated assistant, not a replacement for judgment.

• Explainable AI: Lenders must watch AI to make sure it is fair to everyone. They also need to know exactly how the AI makes its choices so they can explain it to others.

• AI-Ready Data: AI needs good information and context to work well. Data must be standardized and data security must be implemented at the time of data creation and ingestion.

• Real-Time Data Infrastructure: That provides reliable, well-governed and low-latency access to the right data at the right time of the decision.

In the future, AI models will handle most loan decisions. This shift paves the way for “credit on demand." As real-time cash-flow and alternative data become easily accessible, lenders will be able to offer money right when a small business needs it most, like when they are buying new inventory or have an opportunity to expand. 

Most credit models today aren’t limited by algorithms - they are limited by stale or fragmented data. While credit scores still matter, the new focus is on how the business is running right now. Real-time data unlocks better risk decisions, faster approvals and the ability to continuously adapt. It also makes AI actually operational, not just experimental. The lenders who use AI best will be the ones who succeed.

Looking to approve more small business applicants without increasing risk? Discover how data from the Commercial Financial Network can help.

Source:

1. Goldman Sachs, Survey: Small Businesses Embrace AI—But Need Training and Support to Fully Harness It, March 2026