How much can AI save your small business lending team?

AI continues to transform small business lending by streamlining processes, reducing errors and speeding up decision-making. Financial institutions rely on AI-driven automation to handle tasks that once took hours, allowing teams to operate more efficiently and reduce costs.

AI solutions like document automation and cash flow analysis provide measurable savings and operational efficiencies for small business lenders. Integrating AI technology in the lending process can help reduce customer acquisition costs while optimizing underwriting and accelerating decision times – all without sacrificing accuracy.

Reducing customer acquisition costs

Customer acquisition and qualification are some of the most significant expenses for lenders, especially when running credit bureau checks. However, rethinking the underwriting funnel can help reduce these up-front costs. AI-driven document automation reduces the cost and complexity of gathering and analyzing cash flow data from documents like bank statements, making it possible for lenders to consider this data before pulling credit bureau reports.

With cash flow analysis at the top of the funnel, lenders can filter out high-risk borrowers early in the process and focus on quality applications. AI-powered cash flow analysis provides a real-time view of borrower profiles, helping spot financial red flags early and ensuring only qualified applicants move forward in the lending pipeline.

This strategy reduces the need for manual document review and data entry, and minimizes wasted resources to drive down customer acquisition costs and improve the overall lending process.

Just how much can early cash flow analysis save small business lenders? In the calculator below, see how the cost of processing an application can change with a cash-flow-first approach

Fighting fraud below the surface

It’s no secret that fraud is a growing concern and risk for small business lenders. In a recent study, Lexis Nexis Risk Solutions reported that small business lending fraud has risen by nearly 14 percent in the past year, leading to losses of 6 to 10 percent in most companies.

While evolving fraud methods make it difficult to detect signs of file tampering in documents, intelligent fraud detection software like Ocrolus Detect can help lenders proactively detect fraud by uncovering hidden evidence below the surface. With a simplified Detect Authenticity Score, lenders can weigh the context of what has been tampered with and confidence in the fraud signal against their own unique risk thresholds.

Preventing fraud in lending requires a mix of technology, process and analysis to detect signals of potential fraud and investigate illegitimate documents accurately. With more efficient, effective fraud detection, lenders can optimize risk analysis processes to protect themselves against fraudulent borrowers without delaying decisions or negatively affecting their customer experience. 

Increased operational efficiency

AI optimizes lending operations by automating document processing and replacing manual, error-prone tasks with faster, more accurate workflows. With AI-driven document automation, lenders can easily scale operations with consistent speed and accuracy, preventing bottlenecks and enabling them to write more loans quickly.

Rather than spending hours reviewing financial documents line by line, AI scans large volumes of documents and extracts relevant, structured data in minutes, enabling powerful analytics to provide a complete view of a borrower’s financial standing.

These analytics inform more comprehensive risk models. By processing large data sets, AI refines risk predictions and helps underwriters make more accurate borrower assessments. This enhances decision-making, reduces losses and boosts overall productivity, positioning lenders to thrive in a competitive market.

Case study: Lendr’s success with AI

In one case, Chicago-based financial services company Lendr faced significant delays due to labor-intensive manual document processing. Underwriters spent over five hours each week manually verifying bank statements, leading to loan approval times of 30 to 45 days—quite the extended wait for a business looking for quick capital.

This bottleneck limited their ability to serve clients and grow their business efficiently. To streamline operations, Lendr partnered with Ocrolus to automate document verification. 

The results were immediate: time spent on bank statement processing dropped from hours to just 12 minutes, saving more than 70,000 hours annually and cutting costs by $560,000. Beyond cost savings, Lendr shifted resources to higher-value tasks, such as improving customer service and fine-tuning underwriting criteria.

With faster processing, Lendr increased loan volume without scaling its staff. Through AI-driven document automation, Lendr can now better serve clients, improving the overall borrower experience and boosting profitability.

AI-driven document automation and analysis are delivering substantial savings, improving efficiency, improving decision-making and reducing costs for small business lenders. As the industry evolves, adopting AI technology ensures lenders stay competitive and can help businesses access the capital they need to grow and thrive.

Book a demo today to learn how AI-powered document automation and analysis can help you save time and money in small business lending.

Key takeaways:

• With cash flow analysis early in the underwriting process, lenders can filter out high-risk borrowers sooner, reducing the need for unnecessary credit checks and lowering acquisition costs.
• Automating document processing helps lenders add efficiency to their operations and write more loans more quickly.
• With AI-driven document automation, Lendr saved over 70,000 hours annually and cut costs by $560,000, increasing loan volume and enhancing borrower satisfaction.