Using Psychometrics to Reduce Default Risk in Emerging Markets
Evaluating default risk for SME’s in emerging markets can require non-traditional methods of credit worthiness.
Evaluating default risk for SME’s in emerging markets can require non-traditional methods of credit worthiness.
by Damian Kearney, MBA ’15
In my travels to and work in emerging and frontier markets, it has been easy to see the presence and influence of Multi-National Corporations. I’ve eaten at KFC in Guatemala, filled up at a Total fueling station in Uganda, and worked for Accenture in the Philippines.
Similarly, I’ve also been exposed to a plethora of Micro-finance institutions, reaching the “bottom-billion,” low-income consumers and small business owners in locations including Sub-Saharan Africa and parts of Asia. These institutions promote financial inclusion for populations otherwise lacking access to credit and other financial products.
In emerging markets, I have seen few companies in between.
The business landscape in emerging economies is notably different than in developed economies, particular in the make-up of the competitive landscape. Small and Medium Enterprises (SMEs)—businesses which employ 50-250 employees—are missing in emerging economies. In developed countries, SMEs are the economic engine, employing the majority of the labor force, and producing roughly half of GDP. In contrast, in lower-income countries, SMEs employ only 30% of the labor force and contribute 17% of GDP[i].
Understanding the causes of the differences in these landscapes is complex, and requires a broad understanding of the business ecosystem. While high returns entice investors to emerging markets, political risk, currency risk, and capital barriers generally limit the growth potential of these markets. One area of uncertainty pertinent to SMEs in emerging markets is default risk. Credit markets in emerging economies often lack the ability to judge the creditworthiness of SMEs. While large companies have the ability to gain financing either from corporate treasuries or venture capital, and large interest rates protect creditors of micro-finance, SMEs lack access to these markets. According to Moody’s analytics, a dearth of credit scores or related metrics of credit worthiness prevent retail banks from assessing risks in emerging market companies[ii].
New companies are emerging to capitalize on that inefficiency. One such company is Entrepreneurial Finance Lab (EFL). Celebrating its 5th year, EFL uses “psychometrics” to determine creditworthiness of emerging market entrepreneurs. With the absence of credit scores, EFL uses a test administered on a tablet to gauge users’ quantitative reasoning, integrity, and other qualities determined to be markers of a person’s ability to not only build a successful business, but to repay loans borrowed.
The results have been staggering. Partnering with US credit reporting agency Equifax and a Latin American financial institution, EFL demonstrated the ability to increase lending by 140% while maintaining target default rates, or to reduce default rates by 50% while maintaining target acceptance rates[iii]. Recently, EFL broadened its product offerings, moving into consumer financing. The company partnered with a Peruvian retailer, Gropo Monge, enabling the retailer to offer an additional 35% of its customers loans for electronics and household appliances, with no increase in default[iv].
Another similar company in the space is VisualDNA, based in London. Using an interactive questionnaire, VisualDNA’s tools use individual’s response to questions to gauge creditworthiness. Where it differs from EFL is that the company relies on images, rather than words to create a psychometric profile. For example, a perspective borrower might be asked “How much do you save?” and be shown several images associated with saving (piggy banks, bank statements, empty pockets, etc.). Responses create a profile which can be used to detect character traits which indicate likelihood of default on loans.
As successful as they have been, psychometrics may only be the beginning for these companies. In a recent intjerview with EFL, product specialist David Reiff, he said while psychometrics are the company’s “bread and butter,” EFL is actively pursuing other forms of alternative data to judge creditworthiness. “Data about mobile and online usage are areas we are very interested in. We are searching for data which builds up the integrity of our products.” Admitting that these offerings are still in development, Reiff detailed how mobile or online data could gauge a person’s creditworthiness. “A person who makes longer phone calls could be an indicator of someone engaged in more business-related communications. Or a person with a broader online social network could indicate a deeper safety net.”
Companies like EFL and VisualDNA are beginning to change the way we think about traditional barrier to capital flows. Employing disruptive technology, they produce innovation, and cause us to rethink our traditional understanding of barriers to capital flows in emerging markets.
[i] “The Missing Middle,” Entrepreneurial Finance Lab Research Initiative. http://www.hks.harvard.edu/centers/cid/programs/entrepreneurial-finance-lab-research-initiative/the-missing-middle#heading_01
[ii] Moody’s Analytics Emerging Markets Service, http://www.moodysanalytics.com/Products-and-Solutions/Credit-Research-Risk-Measurement/Credit_Research/Moodys-Emerging-Markets-Service
[iii] “EFL Case Study: Using the EFL Score to Enhance Credit Bureau Data,” https://www.eflglobal.com/wp-content/uploads/2014/09/EQUIFAX-Case-Study-2014.pdf
[iv] “EFL Case Study: Enabling Access to Consumer Credit in Peru,” https://www.eflglobal.com/wp-content/uploads/2014/11/GMG-Case-Study-2014.pdf