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CompanyProfile

Improving SMB access

to credit, working capital

ancouver, Canada-based JUDI.AI is a small
business lending analytics platform estab-
lished in 2016 to improve the loan origination ISO/MLS contact:
V process. Founders Troy Wright and Kevin
Clark, banking industry veterans, wanted more small and Stacy Gorkoff
midsize business (SMB) owners to qualify for loans, stat-
ed Stacy Gorkoff, vice president, marketing at JUDI.AI. Vice President, Marketing
stacy.gorkoff@judi.ai
"The SMB lending space is hard," Gorkoff said. "Credit
unions and community banks that focus on growing their 604-828-5548
communities tend to view small business borrowers as
high risk for low margins." In addition, loan origination www.judi.ai
has traditionally been a costly, time-consuming process
that has hindered financial institutions from scaling their
commercial lending businesses. Gorkoff pointed out. In addition, the platform conducts
a real-time review of cash flow for every loan applicant
No two businesses are the same; each has different data before and after funding, she stated. Transactions such
variables, such as operational models, firmographics, as withdrawals, transfers, recurring payments and other
business history, seasonality, costs, margins and debt/credit payments can be reviewed month by month to
competition; yet some lenders treat SMB lending as a one- help the SMB owner and financial lender keep a finger on
size-fits-all proposition, Gorkoff noted. the pulse of a business.

Automating manual processes JUDI.AI said its proprietary transaction categorization
Traditionally, SMB lending has been a slow, manual engine can automatically construct a "synthetic" SMB
process that can take up to four weeks to complete. This income statement and review financial history faster and
has made some lenders reluctant to give a $150 loan the more frequently than an annual review. By continuously
same time and effort as a $1 million loan. Fortunately, monitoring cash flow metrics, the engine identifies
Gorkoff stated, JUDI.AI has streamlined the process. predictive success and predictive risk indicators,
including debt service coverage ratios, negative account
"As a data science expert in small business lending, JUDI. balance trends, operating debit trends, new line of credit
AI looks at lending as an analytics business that is only payments or NSF transactions. This enables lenders to
as good and flexible as the data and machine learning proactively offer advice and expand service offerings to
applied to it," Gorkoff said. She cited the following benefits help customers grow their businesses, Gorkoff noted.
of the company's SaaS-based platform: Reduce risk, improve efficiency
• Automation: Takes the SMB loan underwriting
process down from four weeks to four minutes Gorkoff further stated that automating the credit review
and increases the number of loans processed by 40 process reduces approval times and improves the staff
percent. experience. In addition to seeing improved consumer
credit scores, lenders have seen more SMB-specific data
• More volume, less risk: Unlocks more data sources points, continuous cash flow monitoring and machine
to make models more accurate and SMB lending learning insights that have enabled lenders to deepen
less risky—resulting in 30 to 50 percent less risk of customer relationships, she added.
default compared to loans using credit scores alone.
• Reinforced relationships: Offers the business Gorkoff also pointed out that JUDI.AI can easily integrate
insights and trusted advice SMBs need to grow new with existing loan origination and core banking systems
and existing relationships. to support an omnichannel SMB lending experience
across branches, phones and digital channels. Its small
Fast, intuitive implementation business lending analytics platform will seamlessly
complement any loan workflow process, she added. "It is
JUDI.AI uses adaptive machine learning to power an affordable solution with proven results," Gorkoff said.
its SMB-specific credit risk assessment model. The "It is a fantastic addition to any digital transformation
company's credit science is based on more than $1 billion project that adds measurable value quickly—especially
of applications analyzed, which has helped accelerate from the perspective of resource efficiency, business
implementation cycles and improve intuitive interfaces, growth and customer retention."

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