Improving SMB access to credit, working capital

Vancouver, Canada-based JUDI.AI is a small business lending analytics platform established in 2016 to improve the loan origination process. Founders Troy Wright and Kevin Clark, banking industry veterans, wanted more small and midsize business (SMB) owners to qualify for loans, stated Stacy Gorkoff, vice president, marketing at JUDI.AI.

"The SMB lending space is hard," Gorkoff said. "Credit unions and community banks that focus on growing their communities tend to view small business borrowers as high risk for low margins." In addition, loan origination has traditionally been a costly, time-consuming process that has hindered financial institutions from scaling their commercial lending businesses.

No two businesses are the same; each has different data variables, such as operational models, firmographics, business history, seasonality, costs, margins and competition; yet some lenders treat SMB lending as a one-size-fits-all proposition, Gorkoff noted. Automating manual processes Traditionally, SMB lending has been a slow, manual process that can take up to four weeks to complete. This has made some lenders reluctant to give a $150,000 loan the same time and effort as a $1 million loan. Fortunately, Gorkoff stated, JUDI.AI has streamlined the process.

"As a data science expert in small business lending, JUDI.AI looks at lending as an analytics business that is only as good and flexible as the data and machine learning applied to it," Gorkoff said. She cited the following benefits of the company's SaaS-based platform:

• Automation: Takes the SMB loan underwriting process down from four weeks to four minutes and increases the number of loans processed by 40 percent.
• More volume, less risk: Unlocks more data sources to make models more accurate and SMB lending less risky—resulting in 30 to 50 percent less risk of default compared to loans using credit scores alone.
• Reinforced relationships: Offers the business insights and trusted advice SMBs need to grow new and existing relationships.

Fast, intuitive implementation

JUDI.AI uses adaptive machine learning to power its SMB-specific credit risk assessment model. The company's credit science is based on more than $1 billion of applications analyzed, which has helped accelerate implementation cycles and improve intuitive interfaces, Gorkoff pointed out. In addition, the platform conducts a real-time review of cash flow for every loan applicant before and after funding, she stated. Transactions such as withdrawals, transfers, recurring payments and other debt/credit payments can be reviewed month by month to help the SMB owner and financial lender keep a finger on the pulse of a business.

JUDI.AI said its proprietary transaction categorization engine can automatically construct a "synthetic" SMB income statement and review financial history faster and more frequently than an annual review. By continuously monitoring cash flow metrics, the engine identifies predictive success and predictive risk indicators, including debt service coverage ratios, negative account balance trends, operating debit trends, new line of credit payments or NSF transactions. This enables lenders to proactively offer advice and expand service offerings to help customers grow their businesses, Gorkoff noted.

Reduce risk, improve efficiency

Gorkoff further stated that automating the credit review process reduces approval times and improves the staff experience. In addition to seeing improved consumer credit scores, lenders have seen more SMB-specific data points, continuous cash flow monitoring and machine learning insights that have enabled lenders to deepen customer relationships, she added.

Gorkoff also pointed out that JUDI.AI can easily integrate with existing loan origination and core banking systems to support an omnichannel SMB lending experience across branches, phones and digital channels. Its small business lending analytics platform will seamlessly complement any loan workflow process, she added. "It is an affordable solution with proven results," Gorkoff said. "It is a fantastic addition to any digital transformation project that adds measurable value quickly—especially from the perspective of resource efficiency, business growth and customer retention."

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