By W.B. King
Among the findings in Parlay Finance’s Supercharge Small Business Lending with Loan Intelligence Systems survey is that less than 50% of small businesses report that their credit needs are met—a significant issue for loans under $1 million, which represent 93% of small business requests.
“To compete in modern lending, institutions need more than a system of record – they need an intelligent way to intake, assess and guide small businesses applying for a loan,” the report noted. “A loan intelligence system (LIS) is a new technology category that transforms how lenders engage with, evaluate, and convert small business borrowers.”
Conceived to help immigrant-owned, veteran-owned, and women-owned businesses access affordable capital, the Alexandria, Va.-based Parlay Finance offers an LIS, a suite of artificial intelligence (AI)-powered applications that enables community banks and credit unions to increase small business loan volume, efficiency, and profitability.
Mike Anderson, business owner, and former SVP at US Bank and Wachovia, noted in the report that LIS is game changing. “The improved customer experience for applicants doesn’t just simplify a process that is often dreaded—it can actually create loyalty and deliver real value,” he shared.
Application Friction
Historically, community lenders have evaluated loans using commercial lending practices, which can require two to three weeks of processing time, the report stated. Conversely, online and alternative lenders turn these requests around in one to two days.
“While many banks are now attempting to modernize through technology adoption, organizational challenges persist,” the report continued. “The common dilemma of whether to align small business lending under consumer or commercial units often creates knowledge gaps, resulting in missed cross selling opportunities and underwriting inefficiencies.” Further, traditional LOS (loan origination system) platforms were designed for “static data collection rather than dynamic decision-making.”
Data from the report suggests that the biggest hurdle for small business lending occurs at the application stage, which is often rife with friction. On average, 68% of applicants abandon loan applications during the process, with SBA loans experiencing even higher drop-off rates due to their complex information requirements,” the report continued. “This creates a compounding effect throughout the lending value stream, as lenders cannot efficiently assess eligibility or make timely decisions without complete and accurate data.”
To combat these issues, many financial institutions implemented multiple LOS solutions that offered specialization, such as for commercial and industrial loans or U.S. Small Business Administration (SBA) 7(a) loans. The latter is used to purchase real estate, equipment and machinery, refinancing debt, furniture and supplies as well as working capital, among other actions. These loan mitigation attempts, however, often cause more problems.
“This siloed approach can result in qualified applicants falling through the cracks or being forced into the wrong product pipeline,” the report stated. “When applicants need to be moved between systems, this may cause more manual work for the lender and risks extending processing timelines, leading to further abandonment.”
For traditional loan origination, the report said that 80% of related costs, delays, and manual tasks occur during the first three stages of origination: intake, decisioning, and conversion. Automation alone cannot solve these challenges, as many applicants struggle with financial literacy and process familiarity. What’s needed is intelligent systems that can dynamically assess applicants and guide them to the right products based on their unique characteristics and needs.”
Optimal Product Fit
Marc Rehberger, SVP, senior managing director and head of tech enabled banking at the West Reading, Penn.-based Customers Bank noted in the report: “Community banks need to adopt new technology solutions that amplify authentic human approach. For example, an LIS gives the bank real intelligence to scale personal service while meeting modern lending demands without throwing more people at the problem.”
By using AI-powered LIS solutions, the report contends that the noted three critical organizational steps—intake, decision and conversion—can double loan volume without additional headcount. This is achieved by “validating applicant data in real-time and automatically determining optimal product fit for each small business.”
This approach benefits both borrowers and lenders—creating an efficient, transparent experience, the report stated. “For small business owners, it removes the uncertainty and friction typically associated with loan applications while providing valuable insights into their financial standing. For lenders, it enables scalable growth and deeper customer relationships while reducing operational costs.”
Youri Nelson, CTO at the Wilmington, N.C.-based Lumos Technologies, noted in the report that community financial institutions need more than traditional lending tools to compete.
“With Loan Intelligence Systems and insight-rich third-party data, lenders can streamline their operations, reduce abandonment rates, and make data-driven decisions that unlock trapped capacity and drive growth.”
As non-bank lenders expand their technological advantage, thus competing with credit unions and banks, the report noted that the time for incremental improvements has passed—the time to act is now.
“Those who move quickly will capture oversized returns in their markets, positioning themselves as leaders in the next generation of community banking,” the report continued. “The question is no longer whether to adopt an LIS, but how quickly lenders can implement this essential technology to secure their future in small business lending.”