Changing debt's calculus with Uplinq

An ongoing catch-22 in the world of debt is that those most in need of capital—whether because their financial health has taken a hit, or because financial systems currently and historically exclude them, or a mix of both—are those least likely to receive it, and even less likely to receive capital at a fair price. This phenomenon contributes to ongoing wealth inequality, while also appearing, in large part, as a necessary evil for lending to continue to exist as a business.

To Patrick Reily, Co-Founder of Uplinq, underwriting models are an underlying and solvable factor behind the catch-22 of lending. With more holistic, dynamic, and contextual models, lenders can offer capital to more applicants while appreciating their real (i.e. for the large part reduced) risk of default, helping lenders extend loans to more people at fairer prices. 

What

Uplinq is the first global credit assessment platform for SMB lenders. In the United States, the company collects over 12.5 billion data points to evaluate SME applicants according to a more textured and dynamic set of variables than those offered through traditional underwriting processes, namely those dependent upon a credit score. Uplinq is designed to expand access to unbanked and underserved small business owners, such as those belonging to racial, ethnic, and gender minority communities.

Why

According to Reily, Uplinq helps address what the World Bank calls the “missing middle.” On one end are consumers, who have a suite of automated distribution and product options at their disposal. On the other end are corporations, which are subject to curated, bespoke sales and support services by big banks and other financial institutions.

“In between you have this no man's land, and that creates some really interesting problems,” Reily said. “Whether you’re Honda or Microsoft or Apple, all those companies have their foundation in small business, and so if you think about it, small business is really an incubator for what often ends up being some of the world's greatest and most significant companies—small business is the foundation, the bedrock for patented intellectual property development.” Offering accessible credit to small businesses can thus be a driver for both equity and innovation. 

How

Uplinq built a user interface for underwriters that connects to loan origination systems, credit bureaus, and KYC data; it also pulls in its alternative data to contextualize specific industries and geographies. It can also pull bank statements and tax documents, depending on the applicant and the permissions granted in the application process. 

Within the interface, Uplinq provides a specific probability of default, and then specifies the accuracy of the prediction according to how much of it it can explain. It contextualizes this risk according to internal compliance variables like KYC verification and external factors like whether a loan qualifies for community reinvestment. 

Uplinq sees a core of its product development advantage being how it solves for transparency and quantitative measurement. 

“Rather than giving [lenders] what I would call a nonsense number—if you think about your credit score, whether it's 660 or 820, what does that number really mean?—we actually translate those numbers into probabilities of default, so people understand the actual underlying risk,” Reily said. 

Within its UI, Uplinq also shows a Lorenz curve for its different models, comparing the proportion of loans approved within various models according to risk levels. The curves function as a quantifiable accountability measure proving that Uplinq’s proprietary models better serve underserved applicants, and can help bring the cost of capital down by mitigating risk and reducing the need for lenders to charge high interest rates. Speaking of AI-powered models, Reily said, “most people don't realize that there are very objective ways to measure how well these things work.”