DJ Didonna

Solving a $2.5 Trillion Problem: Can innovations in credit scoring give credit where it’s due?

Micro, small and medium-sized enterprises have a combined credit need of up to $2.5 trillion globally. The fact that this need persists is due to an intractable standoff between lenders desperate to capture this market, and borrowers unable to convey their creditworthiness in the antiquated ways demanded of them. But in our work in over 20 countries across 4 continents, we at the Entrepreneurial Finance Lab (EFL) have seen glimpses of innovation utilizing “non-traditional” data in these markets that signal a potential easing of the standoff.

Successful lending demands understanding, not just minimizing, borrower risk. Financial institutions across the world utilize the same requirements playbook to do so: previous borrowing history (credit bureau reports, bank statements, etc.), audited/formal financial statements, and other formal documentation. These prerequisites are scarce, if they exist at all, in emerging markets. But while the infrastructure and capabilities for sufficiently capturing these traditional requirements remain structurally impossible, mobile and Internet penetration in these markets are unlocking new repositories of data.

Decades ago in the United States, Wells Fargo pioneered a way around similar hurdles to small business lending by utilizing a business owner’s personal credit profile to determine creditworthiness. This evolution to measuring the individual in more developed markets is important, as individual characteristics are something every person has. But how does one measure the individual? Lenders are faced with two options: to manually extract personal information from potential borrowers – a labor-intensive and often inconsistent qualitative endeavor – or to employ “non-traditional” data in their due diligence. At EFL, we automate and quantify the former, while enabling and integrating the latter, but I’ll get to that in a bit.

The growth and prevalence of non-traditional data is staggering in emerging markets, and predictably, “non-traditional” lenders have led the charge in utilizing this information. From countries like Turkey, where bureau and credit scoring capabilities rival their European counterparts, to the likes of Indonesia, which is perennially perched atop rankings for social network and Internet penetration while lacking organized bureaus or even national identification systems, anywhere from 35 to 90 percent of small businesses lack standard borrowing requirements. This hasn’t stopped companies like Lenndo, Cignify, Demyst, and even OnDeck Capital in America from utilizing these data points for lending decisions, or disbursing themselves.

Non-traditional lenders are uniquely positioned to take advantage of the shift from what customers give once in their loan application, to what they are constantly providing about themselves in everyday life. Either overtly in their social profile, by their phone top-ups, or their business credit card transactions, entrepreneurs are communicating a more holistic view of themselves and the way they do business. As Alibaba showed in China and PayPal plans to demonstrate in the States, the traditional business lending cookbook isn’t the only way to lend successfully. Intuit and others with proprietary access to modern proxies for business health and ability to pay will inevitably follow.

So, given all of this information out there, how does EFL’s approach contribute? We assess a combination of skills, capabilities and personality to enable or supplement a lending decision by evaluating the individuals themselves. This is different from an individuals’ social profile, for example, because EFL’s methodology borrows from the pre-employment screening industry to cut through someone’s desired portrayal of themselves, into their true nature and capabilities. Even in an information-rich environment, knowing an applicant’s current personal characteristics can enable a lender to better predict their response and potential in the future – which may or may not look like the past. Furthermore, this makes equity-based investments in entrepreneurs more attractive for lenders; banks tend to only value returns at the rate of interest, sacrificing large upsides in favor of predictable interest income streams.

At EFL, we believe the lending and scoring landscape of the future incorporates the historical, behavioral and capability aspects of the individual in assessing creditworthiness. Each lens has its flaws (financial fraudster Bernie Madoff’s history on paper looked great), but together, these lenses provide a more holistic view of an individual’s and business’ capability. We believe the increasing availability of this “non-traditional” data, combined with lenders’ increasing willingness to deploy unorthodox methods of credit assessment, will unlock trillions of dollars for stymied individuals and enterprises across the world, helping give credit where credit is due.

DJ DiDonna is co-founder and COO of the Entrepreneurial Finance Lab (EFL).

credit scoring, lending