Four differences and five similarities of digital credit markets in Kenya and Tanzania

October 18th, 2016

While both Kenya and Tanzania registered fast uptake of digital credit, a new study by FSD Kenya and CGAP with almost 8000 individuals found considerable differences as well as similarities in the adoption and use of digital credit in the two countries.

Digital credit has revolutionized access to formal credit in Kenya and Tanzania, making the region a hub for technology and banking innovations. While both countries registered fast uptake, a new study by FSD Kenya and CGAP with almost 8000 individuals found considerable differences as well as similarities in the adoption and use of digital credit in the two countries. The similarities suggest factors they may be common to digital credit as a product, while differences are largely due to different structures of the telecommunication and banking sectors and local economic contexts.

Five similarities
  1. Digital borrowers tend to be very active both in Kenya and Tanzania: Uptake of digital credit has been fast in both counties, with 35% of Kenyan and 21% of Tanzanian phone owners having accessed digital credit at least once in the last 5 years. What is even more remarkable is how active digital borrowers tend to be: 60 percent of Tanzanian borrowers had at least one digital loan outstanding at the time of the survey, as did 54 percent of Kenyan digital borrowers.

  1. In both markets, young, urban men are the most common digital borrowers: Compared to the average adult, the typical digital borrower in both markets is more likely to live in an urban area, be between 26 and 35 years old, and have completed at least secondary schooling. Education is a strong predictor of digital credit use in Kenya, with 72 percent of digital borrowers having secondary schooling or above, compared to 41 percent of all adults. In Tanzania, however, the share of digital borrowers who have completed secondary schooling (one in four) is only four percentage points above the national level.

Figure 3. Demographics of digital credit users (dark) versus all adults (light)

  1. The reasons for borrowing digital credit are similar in Kenya and Tanzania: Across Kenya and Tanzania, borrowers report two widespread use cases of digital credit: basic “day-to-day” household needs (35 percent and 37 percent, respectively) and working capital for small enterprises and self-employment (37 percent and 31 percent, respectively). When day-to-day needs and “personal household goods” (22 percent for Tanzania, and 10 percent for Kenya) are combined, these household consumption purchases are by far the most commonly reported use cases for digital credit.

  1. Late repayment of digital loans is widespread in both Kenya and Tanzania: 56 percent of digital borrowers in Tanzania and 47 percent in Kenya report having ever repaid late. Because these numbers are self-reported, the actual rates could be even higher. The similarity in late repayment rates in the two markets indicates this is a common occurrence with digital loans. Qualitative research has suggested that the privacy and lack of human touch with digital loans make their repayment a lower priority for borrowers, compared to loans from family or community members where borrowers’ local reputation is at stake.

Figure 2. Percentage of borrowers who report having repaid late or defaulted on a digital loan

  1. In both markets, digital credit reaches those who were already more financially included. In Kenya, digital borrowers are 26 percentage points more likely than the typical adult to have a bank account, while in Tanzania they are 19 percentage points more likely. Digital borrowers are also more likely to have national health insurance and to engage with other financial services, including pensions and microfinance.

Figure 3. Use of financial services among digital borrowers (dark) and all adults (light)


Four differences
  1. The digital credit market is more concentrated in Kenya than it is in Tanzania: While uptake has been fast in both counties, there are significant differences in the market structure. 82 percent of digital borrowers in Kenya have used the leading lender, M-Shwari, while only 34 percent has used the closest competitor, KCB M-Pesa (percentages add to more than 100 because some borrowers have used more than one digital lender). In Tanzania, the market is split more evenly, with 48 percent of digital borrowers having used M-Pawa, 39 percent having used Timiza, and 29 percent having used Nivushe. This is largely due to the differing market structures in the two counties: in Kenya, Safaricom has a dominant position in the telecommunications market whereas in Tanzania there is stronger competition.


  1. Kenyans are more likely to engage in multiple borrowing: Thirty-five percent of Kenyan digital borrowers have borrowed from more than one digital lender while only 15 percent of Tanzanian digital borrowers have. The high percentage in Kenya is primarily due to M-Shwari borrowers who have also borrowed from another digital lender. This indicates that digital lenders in Kenya should be aware that many of their customers already have a credit history with M-Shwari. Because M-Shwari had little competition for its first few years of operation, early M-Shwari borrowers may have been trying other offers as they became available. Further, 14 percent of digital borrowers in Kenya had multiple digital loans outstanding at the time of the survey, compared to 6 percent of digital borrowers in Tanzania.
  1. Digital credit is concentrated among entrepreneurs in Tanzania, whereas the userbase is more diversified in Kenya: In Tanzania, 50 percent of digital borrowers report self-employment as their primary income source, compared with only 14 percent of the adult population. In Kenya, those with self-employment as their primary income source are also the main users of digital credit (31 percent of digital borrowers), but the market is otherwise more spread across different types of livelihood groups. In both countries, the penetration of digital credit among those with farming, casual work, or transfers from others as their primary income source is relatively low. Uptake is particularly low for the farming and casual work segments in Tanzania, both of whom represent major livelihood groups (41 percent and 20 percent, respectively) but account for only 18 percent and 5 percent, respectively, of digital credit borrowers.

  1. In Kenya, borrowers tend to reduce usage of non-digital loans after gaining access to digital credit. In Tanzania, digital credit primarily adds to or complements the borrowers’ existing credit sources. Sixty-three percent of digital borrowers in Kenya reported reducing their use of at least one type of nondigital loan source since they began using digital credit. This suggests that many Kenyan borrowers use digital credit as a substitute for other sources. In Tanzania, only 34 percent report reducing the use of other loan sources, suggesting digital credit complements, rather than replaces, other loan sources.

These findings can be instructive for countries where digital credit is more nascent. As may be expected, early adopters are likely to be young, urban, and male. Late repayment and to a lesser extent default on digital loans is widespread. Other factors such as market concentration and the role digital credit plays in financial portfolios will depend on underlying contextual factors. Policymakers and regulators should keep watch to understand how digital credit is evolving in their own markets, and to spot potential problem areas early on.



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