Where are we now? 6 years after the first digital consumer credit product launched
In Part 1 of a 2 Part blog series, we highlight recent survey findings and insights on the uses and risks of digital credit for borrowers in East Africa. This post was written by Alexandra Wall, a graduate student researcher with CEGA’s Digital Credit Observatory (DCO).
When CEGA’s Digital Credit Observatory (DCO) launched in 2016, there was very little quantitative evidence on the social or economic impacts of digital credit. In the six years since the first digital consumer credit product (M-Shwari) launched in Kenya, our understanding of digital credit has been largely shaped by anecdotes and qualitative studies with small samples.
Gradually, however, more evidence is shedding light on the relationship between borrowers and the digital loans they take out. I recently spoke with Michelle Kaffenberger, a member of the DCO’s Community of Practice, to learn more about findings from two recent digital credit surveys. This post highlights these findings as well as other topics discussed during our conversation, including current trends and risks in the digital credit space.
CGAP and FSD Kenya recently undertook a major effort to understand the experience of users of digital credit by conducting two nationally representative phone surveys with over 7,000 mobile phone users in Kenya and Tanzania. The findings, summarized in this working paper by Michelle Kaffenberger and Edoardo Totolo (with Matthew Soursourian), provide key insights regarding the profiles of digital credit borrowers, the ways in which the products are used, and the risks that borrowers face in using them. These national surveys provide a step towards better understanding how digital credit products are experienced across a wide demographic of borrowers.
Key findings from the surveys include:
● 56% of borrowers in Tanzania and 47% in Kenya have repaid a digital loan late; 31% in Tanzania and 12% in Kenya have defaulted
● These late repayment and default rates are relatively consistent across gender, education, and occupation segments
● 20% of Kenyan and 9% of Tanzanian borrowers reduced food purchases to repay a loan
Findings suggest there is a segment of borrowers that may not be benefiting from — and may even be harmed by — taking out digital loan. The fact that delinquency is relatively consistent across demographic groups, including segments where you would expect variation, suggests that repayment may not be entirely based on a borrower’s ability to repay. We suspect that certain characteristics of digital loans — no face-to-face interaction with a loan officer, no peer pressure or reputation risks afforded by local lending groups, and minimal product friction — may actually lead borrowers to de-prioritize repayment over other financial obligations.
While some borrowers certainly experience hardships when repaying loans, others may benefit from the possibilities that digital credit provides. It’s important that lenders are able to distinguish between these two types of borrowers and make lending decisions accordingly, for example by using positive repayment history to provide larger loans and better loan terms to those wishing to make productive investments.
Deeper qualitative research can help uncover the nuances of repayment behavior and the role that elements of product design (timing, cost, flexibility), the nature of digital credit (automation, remoteness), and borrower characteristics (creditworthiness) play in shaping late repayment and default rates.
Financial Inclusion or Exclusion?
When the first digital credit product launched six years ago, it was viewed by many as an alternative to traditional microcredit, which was often restrictive in lending and had modest impacts on borrowers. Digital credit was seen as an opportunity to provide loans that were more affordable and accessible to an even wider consumer base. However, with digital consumer credit loans starting to bear the resemblance of payday loans (short-term and high-cost), these products are at risk of contributing to even more financial exclusion.
This raises the question of whether the digital credit products available today are actually appropriate for the most vulnerable borrowers. And what incentives do for-profit companies have for serving this segment of the population? Graham Wright from MicroSave points out that “fintechs will not be able to reach rural customers without access to 3G data services and smartphones — even if they were interested in doing so.”
A majority of digital loan products currently target urban and peri-urban consumers, compounding an increasing concern that the most financially excluded populations in rural communities will continue to have limited access to new innovative credit products. Even in a market like Kenya, which now offers digital loans from over 20 providers, the CGAP/FSD Kenya working paper notes that “digital credit remains mostly out of reach or unused by the most vulnerable groups…that are characterized by irregular cash flows.”
Nascent Digital Credit Markets
While there’s no denying that the digital credit market in East Africa — and especially in Kenya — is a unique case that has seen unprecedented take-up of mobile financial products, there may be some generalizable insights that can apply to more nascent markets. For example, although the primary drivers of digital credit have been different in East Africa (mobile money) than in East Asia (e-commerce), the relatively consistent repayment patterns seen across demographics in East Africa demonstrate that there may be something unique about “digital” that might carry over to other contexts.
In addition to behavioral insights that may be translatable to other global regions, the consumer risks and regulatory responses that have happened in Kenya and Tanzania should be closely watched by other countries where digital credit products are gaining momentum. There is a window of opportunity for regulators in more nascent digital credit markets to find answers to questions such as: Should reporting to credit reference bureaus (CRBs) be required across all lenders (regulated and non-regulated)? or Should negative listings for all loan sizes be reported to CRBs or only loan amounts above a certain threshold (e.g. $10)?
The CGAP and FSD Kenya survey findings suggest several key messages for policy makers to consider, as many new unregulated lenders “who operate beyond the purview of any regulatory authority” have entered the market since 2015. In their working paper, Kaffenberger and colleagues note that “Regulations should be extended to cover all lenders, including currently unregulated ones, so that all borrowers have the same protections.”
What’s Needed: Understanding Causal Impact
These are key questions and considerations that will need to be addressed if digital credit markets are to grow responsibly. While descriptive data collection efforts — including the national surveys conducted by CGAP and FSD Kenya — can provide valuable insights, it is difficult for such studies to establish causality and impact.
A much-anticipated, recent impact evaluation in Kenya by Tavneet Suri (DCO grantee), Billy Jack, and CEGA affiliate Prashant Bharadwaj (working paper coming soon) finds that new M-Shwari customers with low credit scores may not experience improvements in income and consumption, but are better equipped to pay for schooling and cope with emergencies as a result of having access to digital credit.
While this is one of the first studies to measure the impacts of digital loans on borrowers using a quasi-experimental design, additional experimental research studies on this topic are currently underway. CEGA’s Digital Credit Observatory (DCO) is supporting a coordinated suite of impact evaluations that can illuminate the connection between digital credit and welfare outcomes. The causal impacts of digital loans on borrowers’ well-being can inform regulatory measures that can be put in place to mitigate negative impacts.
In Part 2 of this blog, we will hear from Caribou Digital’s DFS Lab and Accion’s Smart Campaign about what investors and consumer protection organizations are doing to address risks and concerns in the digital credit marketplace.
The Digital Credit Observatory, funded by the Bill & Melinda Gates Foundation, was established by CEGA in 2016 to fund a suite of coordinated studies answering questions related to the impacts of digital credit in emerging markets and the effectiveness of related consumer protection measures.