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Four things to be aware of in the search for digital finance impact



In previous insight pieces on savings, credit, and, Person-to-Person (P2P) transfers, we synthesized what we learned from studies in the Digital Finance Evidence Gap Map (EGM) using a product lens. However, the product lens is just one perspective, and the digital finance impact landscape is more varied and layered than this. Here we share four factors that digital finance researchers should consider when testing the impact of a digital finance product.

Figure 1: Source of variance on impact

1. Digital finance is not one thing

Digital finance includes dozens of diverse products, and researchers need to disentangle each digital finance product from the broader category in order to deepen the digital finance community’s understanding of what changes each of these products catalyze in the lives of low-income users. When the 60 product studies within the Digital Finance Evidence Gap Map (EGM) were disaggregated, we saw vast differences among the products that have been tested to date. P2P payments and transfers account for 30% (18) of the impact studies, savings for 18% (12), and credit for 12% (7).

Figure 2: Number of digital finance products represented in the Digital Finance Evidence Gap Map

Results from studies on P2P transfers cannot contribute to our understanding of the impact of digital credit. Indeed, every product comes with its own theory of what changes as a result of interacting with it. To advance knowledge in the digital finance community, we need to identify the gaps in product impact knowledge and allocate resources to begin correcting it.

2. Product design and delivery varies

Digital finance products can be and are designed and delivered in many different ways. The difference with digital is the opportunity to enhance services, and hopefully outcomes, by integrating design and delivery elements. An analysis of the EGM confirms that product designers use a multitude of innovative digital, and non-digital, design and delivery mechanisms. The EGM shows that across the 60 products studied, 28 different design and delivery features were observed. On average there were two design and delivery mechanisms described per product in the EGM.

Figure 3: Number of design and delivery mechanisms used across 60 products in the Digital Finance Evidence Gap Map

This means we might expect different client outcomes from digital credit products with a mobile learning component versus digital credit products without. Even within the same category of digital finance products, how they are designed and delivered may differ, and these differences result in variance in user outcomes.

However, most studies are not engineered to show whether the driver of change was (1) the way they recruited clients, (2) the training content, (3) the price of the SMS, or (4) some combination of these elements. These design and delivery choices typically become a single data point in a study so that we learn about the sum of the whole, rather than the sum of the parts. This is fine for deployments but a challenge for meta-analysis and impact assessment unless these variations and distinctions are made explicit.

3. Markets vary

A product owner could test a similar product in two different countries and find that client outcomes diverge. Regulation, infrastructure, capital, and, of course, the client’s ability and need to engage with the product vary across markets. The EGM represents 24 countries, but Kenya accounts for over a quarter of these impact studies (27%) and East Africa as a whole for over half (52%).

Figure 4: Number of countries represented in the Digital Finance Evidence Gap Map

Unsurprisingly, Kenya, the site of much innovation in digital finance, is the most studied country. But we must acknowledge that we simply know less about other regions and countries and that much of our learning comes from a particular region. So, before we transfer learnings from Kenya or Tanzania to other contexts, we must carefully consider the various social, economic, and cultural differences involved.

4. Clients vary

We could also test the same product in the same country with different client segments and find different results. One question to ask is, with which population segments are we testing various digital finance products? From a review of the 60 products in the EGM, the user sample has been concentrated on a mix of urban and rural clients (30%; 18), followed by exclusively rural clients (22%; 13). Fewer studies, 12% (7), have focused on smallholder farmers and, 8% (5), on women.

Figure 5: Number of client categories tested

With whom we choose to test our products matters. Just as a specific market focus can limit our generalizability so can the client sample. This is not necessarily a bad thing: in the context of digital finance, a number of outcomes are unlikely to be experienced equally by all clients. Often, some people benefit more, others less. But we only know when we test for it. See FiDA’s Snapshot on How do advances in digital finance interact with dynamics of exclusion? for more details. A quarter of the studies in the EGM looked for, and highlighted, differential effects on some level within a market based on gender, location, income, or education as described below.

Cases in which the marginalized benefit more from a digital finance product

  1. In a study of M-Pesa in Kenya, results showed that M-Pesa users did not resort to reducing consumption as a coping mechanism when they faced a negative economic shock. Further, the effects were shown to be more evident for the bottom three quintiles of income distribution than for the top.
  2. A study on mobile money in Burkina Faso found that individuals living in rural areas were three times more likely to save with mobile money than those in urban areas. Additionally, women were six times more likely to save with mobile money than men, and less educated individuals were four times more likely to save with mobile money than higher educated individuals.
  3. A Kenyan panel study on M-Pesa reported that mobile money access reduced both extreme and general poverty and that the effects were more pronounced in women—women being affected more than twice as much as the average.
  4. A study in Tanzania examined the impact of P2P transfers in the event of a [weather related] shock. They found that the benefits of other people using mobile money in the community come largely from rural areas where, with 1/3 of the village using mobile money, household benefit by a 10% increase in consumption. In urban areas this effect is only 3% and not significant.

Cases in which the marginalized may benefit less from a digital finance product

There are also cases in which the benefits of digital finance accrue to high status, high skill individuals, rather than to marginalized populations.

  1. CGAP partnered with the Busara Center for Behavioral Economics and Jumo KopaCash—a mobile money marketplace that offers digital credit—to measure client responses to various repayment reminders. The messages’ results varied by demographic with positive effects on repayment for male borrowers and negative effects for female borrowers.
  2. In a panel survey looking at the savings behaviors of M-Pesa users and non-users in Kenya, 65% of M-Pesa users reported having some savings, compared to 31% of non-users. The results showed that those most likely to have savings are male, live in rural areas, and have higher levels of education and income. In terms of the value of savings, those who registered with M-Pesa save 12% more than those not registered. Furthermore, the survey showed that those who are male, urban, and have higher levels of education and income tend to have more savings.
  3. A study on the effects of ATM cards on bank account use in Kenya found that while ATM cards increased account use among male-owned and joint accounts, a negative impact was found on female-owned accounts.The hypothesis was that household pressures to share savings drove women to stop using their accounts when an ATM card reduced the costs of accessing their money.
  4. Testing the effects of a roving Point of Service (PoS) on savings account use in Malawi, researchers observed differential levels of impacts based on wealth levels. For households at the top of the wealth distribution, an increase in savings services was associated with less reliance on distressed asset depletion to cope with economic shocks. However, the effect was the opposite for those at the bottom of the wealth distribution.

These observations offer the digital finance community a refined understanding of impact by determining the conditions under which impact is present, or stronger or weaker. They also underscore the need to examine how a digital finance product interacts with and affects various excluded groups.

The takeaways

  • Digital credit, particularly insurance products, are under-evaluated for client impact. While a growing community of practitioners are working to address gaps in credit knowledge (for example the Digital Credit Observatory, CGAP, FSD Africa), this is not yet the case for insurance. Digital insurance, a nascent product, has primarily, and understandably focused on business model testing. However, as a starting point, qualitative work should begin examining the insurance impact theory.
  • Much research has looked at what does and does not work in terms of product configurations and campaigns, but few impact studies are engineered to pinpoint whether the recruitment strategy, pricing, messaging, or something else that contributed to a given change.While thousands of choices go into product design and delivery, they typically become a single data point. Without understanding this nuance, it is difficult to discern exactly what we are learning.
  • The learning on digital finance impact is concentrated in East Africa. While this knowledge may be transferable, there is a notable absence of studies that focus on West Africa and Southern Africa.
  • Digital finance studies that have examined impact on more excluded groups show that impact is not homogenous. While a few studies specifically define a group of people, we lack research that disaggregates client segments. Acquiring this knowledge would advance our learning on product design and user needs.

Although these nuances may seem obvious to some and overwhelming for others, it is important to recall that while the impact landscape is complex, the studies themselves do not have to be. There is more than one way to gather impact insights, and if the digital finance community is going to be inclusive, we must ensure that we are expanding the conversation on impact to include, in an appropriate way, voices and signals beyond those that can be gathered by experimental methods (See FiDA’s Approaches to determining the impact of digital finance programs for more details).

To continue building the evidence base, the broader community needs to be more involved in contributing insights so that we can have active conversations about impact. Every study that targets a gap— in a product, a market, a design and delivery mechanism, or a client segment—brings the digital finance community closer to understanding the various impacts of different digital finance products and services. Developing an evidence base is like building a puzzle, no individual piece can reveal the picture, but, bit by bit, the picture will emerge as new pieces are added.


FiDA is publishing a series on insights derived from an analysis of the latest Digital Finance Evidence Gap Map (EGM) update. This is the fifth blog.

Previous blogs:

The studies in the EGM represent our best knowledge of digital finance impact insights. New studies are ever emerging and thus the EGM will continue to evolve. If you have questions about the EGM, are interested in discussing research priorities, or know of relevant digital finance impact studies that meet the inclusion criteria, please contact ideas@financedigitalafrica.org.

Fiction or future for platformization? The implications we explored with banks, fintechs, and MNOs



Participants at our event exploring different platformization scenarios.

Platforms are a hot topic and for good reason. The digital “platformization” of markets is one of the defining forces of change in the shift to digital economies. Facebook and Google have leveraged network effects in social media and search to grow massive multi-sided markets in attention and advertising. Innovators such as Upwork, Uber and Kuhustle are revolutionizing the world of work. Amazon, Alibaba and Jumia are fundamentally changing how merchants sell to customers. These platforms are not only transforming online experiences but have real-world implications for users and the markets in which they work.

Platformization presents both new possibilities and new challenges for financial and economic inclusion in Africa and we had a chance to talk about this in new ways with a mix of dynamic startups and larger institutions active in the space. In early October, we organized an event alongside the IFC conference held in Dar es Salaam, Tanzania, where we invited leading representatives from MNOs, fintechs, and banks to explore the business strategy and financial inclusion implications of platformization. While some platforms bask in user bases in the millions and billions, astronomical transaction velocity, and stickiness so effective that people have to consciously tear themselves away from the screen, most African financial service providers struggle with low customer uptake, thin usage, and a dearth of digital data.

There is no doubt, then, that certain platforms can dramatically change the landscape for traditional financial institutions, presenting new opportunities for collaboration and competition. Likewise, some platforms will also likely need to make a shift towards thinking more about financial inclusion, because of their pivotal role in the digital economies of the global south and because their success relies on the ability of users to seamlessly transact.

In truth, platforms and financial services providers in this digital community probably need each other and this became a theme of discussion among participants at our event. Representatives from JumiaPay, JD Finance, Mastercard Foundation, Uber, and the World Bank, among others, participated and helped shape the group’s understanding of platformization. The event was interactive at its core – an important element to stimulate the kinds of discussion needed to more wholly understand the opportunities and challenges platformization presents.

One lens, six scenarios, and endless implications

We first introduced the FiDA Partnership Lens for Platformization – a framework to move forward through the sometimes confusing landscape of platformization.

Jonathan Donner introducing the FiDA Partnership Lens for Platformization.

We then introduced the participants to six fictional scenarios that they, in groups, would have to navigate – wearing the hat of MNO, bank, or fintech. These scenarios – while fictional – we think are possible.

The fictional scenarios we dropped these MNOs, fintechs, and banks into were these:

1. Facebook’s WhatsApp launches Whatsapp zero-fee payments and transfers in sub-Saharan Africa, enabling customers to link bank accounts and mobile wallets to the service. Whatsapp begin to recruit merchants who will offer payments through a QR code system.

2. Indonesia’s motorcycle delivery service Go-Jek enters Kenya offering a wide range of services from transportation and courier services, to mobile payments and food delivery.

3. Walmart takes Flipkart (the Indian e-commerce platform in which it owns a 77% share) to Africa.  In a bid to ensure prices remain competitive, it introduces low-price private label products which put pricing pressure on small merchant businesses.

4. Three local labour platforms – similar to Dumaworks, Taskit, Kuhustle and Lynk – consolidate to overcome fragmentation in the labour market. The new, consolidated platform, called WorkWork, begins to develop other product offerings to enhance revenues, by partnering with several banks and fintechs.

5. WeChat pens a deal with OEM, Transsion (manufacturer of Itel, Tecno, and Infinix), enabling WeChat and WeChat Pay to be enabled on any Android device in five influential African countries.

6. Regulation requires online platforms and marketplaces to obtain banking licenses, or partner with banks / insurance providers, etc. in their quest to enter the lending, insurance and wealth management space. Jack Ma, co-founder and executive chairman of Alibaba Group visits Kenya, Nigeria and Rwanda in search of potential partnerships.

Each scenario above had a series of events that played out as participants thoughtfully moved through business strategy during the first session, and how they moved through financial inclusion implications in the second session, guided by a facilitator. These events impacted the way each representative responded to the others in the group and brought a level of real-worldness to the scenarios which was appreciated by participants.

As Peter Zetterli from CGAP put it:

“To have conversations that were quite concrete in nature – talking about specific scenarios was useful in teasing out some concrete questions and answers from what could otherwise be a fairly abstract and hypothetical conversation.”

One conclusion that came out of these conversations, noted by Sid Garg, founder of fintech startup Teller, was the realization that while platforms present an opportunity, it doesn’t mean that players can ignore local market context.

“The opportunity that platforms present – especially for small players – allow something like Teller, or another small startup, to scale really quickly but one of the things I noticed at the event was that you have to adapt to the regional and cultural characteristics of each market. You can’t just trust that a platform will give you the access and skill you need – you still need to do a lot of work to adapt your products.”

For many, this event highlighted that platformization is already underway with WeChat and WhatsApp, and could see these scenarios play out in the next six months. The prospect of WhatsApp turning on payments in several countries in Africa, or even all of them, isn’t far fetched and could have great impact on the business models of incumbents in the space, therefore potentially impacting financial inclusion. How companies adapt their strategies to platformization will likely be key to their ability to thrive in the shift to a digital economy.

“Before, as a platform founder, I felt my job was done when I connected both sides of the marketplace but I do feel strongly now that there’s a value you can add on both sides of the marketplace by adding financial services.”

Sam Gichuru, founder of Kuhustle

Over the next few months FiDA Partnership will conduct research to critically assess platforms’ prospects for delivering financial services and furthering the economic activity of underserved individuals, small businesses, and developing economies. We will explore how platformization is affecting partnerships with bearing for financial inclusion and impacting the livelihoods of micro and small enterprises.

We have shared our analytical framework and have started the conversation considering these themes with key players in the spirit of collaborative exploration. We’re thankful to those who participated in our event last month, and we thank you for being a part of this discussion as we move forward. Stay tuned to our blog for further updates on our platform research and please reach out with any comments or questions. This is a conversation that should involve all of us, and we look forward to hearing your input.

Digital payments and transfers—the P2P impact story



There were 690 million registered mobile money accounts as of December 2017. The digitization of a pre-existing behavior—sending and receiving money—is clearly valued in many markets. The digital finance community now has more than 10 years of person to person (P2P) experience on which to reflect: What have we learned about the impact of P2P on clients?

The insights so far

P2P studies account for 30% (18) of all digital finance products and eight countries in the EGM. The majority of studies focus on Kenya specifically and East Africa in general. Most studies examine P2P use generally rather than focusing on a specific P2P service. The mobile money channel is used in 100% of the products tested.

Figure 1: P2P products and countries examined

These 18 studies comprise 57 outcome tests. The diagram below shows the outcomes tested and the number of studies that had a positive, negative, or null effect. Of the 18 products examined, 66.7% (12) reported exclusively positive results, 0% reported exclusively negative results, 5.6% (1) reported exclusively null results while 27.8% (5) reported mixed results.

Among the headline insights:

  • P2P has provided more privacy and thus control over financial resources, especially for female users.
  • Overall, P2P digital transfers are more affordable than previous transfer methods. However, users with low digital literacy and numeracy may not benefit from all cost savings because of fraud or errors.
  • Numerous studies have highlighted positive outcomes in sharing risk through remittances. However, two studies forefronted concerns for those who are sending money.

Figure 2: P2P impact pathway

Spotlight on selected digital P2P studies

We highlight a selection of insights gathered from an analysis of the P2P studies within the EGM and invite digital payment and transfer practitioners, researchers, donors, and policymakers to interact with the EGM to derive insights that match their needs and questions.

Privacy and control

  • Three Kenyan studies from 2008, 2009, and 2014 foregrounded how storing value in an eWallet has provided female clients with privacy and control over their finances. Women valued the decreased risk of their money being used by their husbands. Privacy was important in controlling how, on what, and when the money is spent. Women also appreciated having personal accounts without limiting account opening requirements, travel to banks, or the need to obtain permission from spouses.

Saving time and money

  • Digital payments theoretically reduce the cost of financial services whether through smaller fees, reductions in the cost of travel, opportunity costs of travel, or time savings. Supporting this theory, a 2008 study on M-Pesa found that users reported paying less for transfers compared with sending money on a bus or through the post office. They also reported sending more remittances due to the lower cost. However, a 2014 study found that digital transfers can sometimes cost more due to fraud, agent liquidity, and errors in sending to the wrong number.

Resilience and risk sharing

A popular hypothesis is that digital P2P presents a quick and convenient channel to receive money and thus share risk in times of economic stress. The majority of studies that tested this hypothesis found positive effects through a variety of mechanisms.

  • Straightforward access to cash: Studies on M-Pesa from 2008, 2009, and 2012 showed that M-Pesa enhanced reciprocity and sharing during times of need, particularly for payments related to education, health, and funerals. Additionally, a 2008-2010 panel study on M-Pesa found that users were 11% more likely to receive remittances when faced with a shock and observed a 9.6% difference between users and non-users in education spending.
  • Consumption and spending: In the first analysis of a 2008-2010 Kenyan panel study on M-Pesa, researchersfound that M-Pesa users increase their consumption expenditures by 11.8% during a financial shock, whereas non-users reduce theirs by 3%. In a second analysis of the data, researchers found that while non M-Pesa users saw on average a 7-10% drop in consumption during a financial shock, users did not experience a drop in consumption. In Uganda,  a 2009-2012 panel study found a 13% increase in household per capita consumption following the adoption of mobile money services.
  • Household shocks versus community shocks: A study using data from 2010-2013 in Tanzania examined the effects of mobile money when an aggregate shock—like a drought—occurs. In the absence of an aggregate shock, 36% of a village using mobile money results in a 4% to 10% higher rate of consumption per capita, indicating that mobile money users share remittances with the village. However, when an aggregate shock occurs, non-users experience a drop in consumption while households using mobile money do not. Thus, mobile money users are choosing not to share remittances when an aggregate shock occurs.

Beyond resilience, welfare and income

Researchers looked at P2P’s effects on welfare and income using a range of analytical approaches and looking at diverse client segments—many studies are 10 years old. Several studies optimized for the fact that mobile money services were widespread in the markets examined—and so could not be randomized or withheld—and used panel designs. These insights, while informative and foundational, should be read with care, as many speak to association rather than causation and do not isolate the mechanism of change.

  • Physical security: A 2009 study on the community effects of M-Pesa, found that men especially identified physical security as an important outcome.
  • Asset investment: A 2010 study on various P2P services in Kenyafound that users invest $42 more per year in agricultural inputs than non-users. Similarly, a 2009-2010 Kenyan panel study with farmers found that mobile money users were associated with higher spending on agricultural inputs. Looking at other business investments, two Kenyan studies from 2009 and 2013 provide insights into how M-Pesa aids business expansion through direct investment but also through increased money circulation and lower vendor transaction costs in obtaining stock.
  • Income changes: Many income insights from P2P services come from the agricultural sector.A 2009-2010 Kenyan study on banana farmers, found that on average mobile money users earn $745 more per year than non-users. Similarly, a 2010 Kenyan study of farming households noted that mobile money users earned $224 more in farming activities per year than non-users. In Uganda a 2012-2015 study of coffee farmers found that mobile money use was associated with a 31% higher farm income.
  • Food security: A 2009 study on community level effects of M-Pesa revealed positive insights on improved food security. The mechanisms cited include improved access to agricultural inputs and thus greater agricultural productivity. Increased money circulation was also related to improved food security. Additionally, a 2008-2010 panel study in Kenya observed a 9.1% difference in food expenditure among users and non-users of P2P.

The first examination of both sides of the ‘P’

In 2018, a study that matched senders of remittances with receivers of remittances was published. To this point, the examination of effects of P2P transfers was based on the receiver’s experience, despite concerns about the welfare of the sender raised 10 years ago by a qualitative research study . In Dhaka, one team followed urban migrants and their extended families in Rangpur. The intervention involved training a randomly assigned group of migrants and their matched household on bKash.The 45 minute (and $12) intervention led to both an increase in accounts and active use. Numerous additional outcomes were examined:

  • Rural households and migrants save more: Rural households were 43.7 percentage points more likely to save, and they saved 125% more than households in the control group. Migrants in the treatment group are 18 percentage points more likely to save and save 38.4% more than the control group by storing value in their bKash accounts, as seen in their month-end bKash balances.
  • Migrants send more during shocks: Migrants in the treatment group whose rural households are hit by negative shocks send between 197% and 520% more remittances using bKash than migrants in the control group.
  • But send less if they are hit with a negative health shock: When the paired migrant is hit by a negative health condition, the consumption of rural households in the treatment group is, overall, not statistically different from consumption in the control group.
  • Education outcomes improve, but not through remittances: Children in the treatment group spent 0.25 hours more studying per week compared to the control group. Additionally, estimates for school attendance, enrollment, and performance are positive. However, parents are not using bKash remittances for education. Rather, the increase suggests that children may be swapping hours spent on household business activities with study. Another possible channel could be through the treatment impacts on health.
  • Health outcomes improve: Households in the treatment group had 0.12 fewer members who were sick compared to the control group. The average medical expenses across all household members also decreased.
  • Negative health impacts on migrants: Migrants in the treatment group had more difficulties with work and emotional problems. Overall the treatment decreased the health index of migrant households. This may be from the pressure to remit money back home.
  • Change in economic status:Estimates shows that treated migrants were 10.8 percentage points less likely to live below the poverty line.

The takeaways

Relative to digital savings and credit, P2P is the most fully formed, evidenced based pathway to client impact.The insights are numerous and often consolidating, permitting more confident conversations on the impact of P2P.

  • P2P users, particularly women, value the ease of storing value and making and receiving transactions in privacy, allowing for more control over how their money is used.
  • P2P transfers are touted as cost saving versus traditional methods of money transfers. Indeed this appears to be the case at face value, although those with limited digital literacy and/or numeracy may have different experiences due to fraud or genuine mistakes.
  • Numerous tests have highlighted how users share risk and smooth consumption through quick access to remittances. More recent studies have followed the money flow from sender to receiver and back again, to confirm previous tests. However, money comes from somewhere and there are concerns regarding the pressure on those sending.

But gaps remain. The clearest gap is in the markets tested. Studies have focused on East Africa where P2P services are widespread, but we cannot assume the same effects in all markets. Additionally, many of the studies that have looked at changes in welfare and income have not cleanly linked the change to P2P, i.e., whether the use of P2P catalyzed the change or the first P2P users were more likely to already be sophisticated business owners investing in assets that boost their income. As many of the first studies on the longer-term effects of P2P were panel designs, it is difficult to isolate the change mechanism. While these designs have developed a narrative around the long-term effects of P2P, only recently have studies begun to isolate the P2P mechanism and reveal insightful discoveries.

FiDA is publishing a series on insights derived from an analysis of the latest digital finance Evidence Gap Map (EGM) update. This is the fourth blog.

Previous blogs:

The studies in the EGM, represent our best knowledge of digital finance impact insights. New studies are ever emerging and thus the EGM will continue to evolve. If you have questions on the EGM, are interested in discussing research priorities, or know of relevant digital finance impact studies that meet the inclusion criteria, please contact ideas@financedigitalafrica.org.

Digital Credit—What do we know about the impact on clients?



This post has been co-authored by Niamh Barry from the FiDA Partnership, and Natasha Beale, Carson Christiano, and Alexandra Wall from the Digital Credit Observatory (DCO) at the Center for Effective Global Action (CEGA).

Credit is a powerful tool in providing liquidity: credit can smooth consumption during financial shocks, provide capital to grow businesses, ensure children’s educations, and ultimately enable people to live happier, healthier, and more prosperous lives.

Traditionally, credit providers require agent and client interaction, risk assessment uses previous financial history, loans are disbursed into a bank account, and payments are made through a bank branch. This excludes those without bank accounts, documented financial histories, or access to a branch. Since digital credit is instant, automated and remote, it could potentially overcome these barriers. Digital credit products can assess credit worthiness remotely and automatically using alternative data sources such as call records, mobile money use, and even geospatial and psychometric data, and then lend money directly to consumers’ mobile phones. Currently, the digital credit market landscape is “dominated by short-term, high interest loans made directly to consumers,” often through telco-bank partnerships.

Five years after its launch, 21.1 million Kenyans have accessed credit through Safaricom’s digital lending product M-Shwari. In addition to the telco-bank model, more and more companies are emerging to meet the growing demand for digital credit including numerous fintech companies that provide intermediary digital credit scoring services or directly originate loans to customers through app-based lending using alternative data. However, high interest rates and the volume of clients blacklisted by credit bureaus— often for late repayments or defaults on loans less than USD $2.00 —are cause for concern. Researchers and practitioners must carefully consider both the causes and effects of over-indebtedness.

What are the insights so far?

The EGM, is not confined to products that are digitised ‘end to end’, but also include credit products that have digitized some aspects of their design or delivery. Within the EGM there are just seven studies that have tested the effect of digitally enabled credit products in five countries. These studies are not yet representative of the diversity of all the digital credit products available so it is not possible to make definitive statements on the ‘impact’ of digital credit. The studies involve different markets, client groups, and design and delivery mechanisms. The table below illustrates the diversity of the digital credit products examined.

Table 1: Design and delivery of credit products

These studies include 21 tested outcomes, with ‘healthy borrowing’ being the primary outcome of focus, and just two studies providing insights on the longer-term effects. The diagram below shows the outcomes tested and the number of studies that had a positive, negative, or null effect; 57% of the credit products tested showed only positive results and 43% showed mixed results. The diversity of results is indicative of the early stage of testing and learning. As more products are tested and we continue to synthesize the evidence—with the support of investors, donors, practitioners, and researchers— clearer patterns may emerge.

Figure 1: Digital credit impact pathway

Spotlight on selected digital credit studies

We highlight just a selection of insights from an analysis of the studies within the EGM and invite digital credit practitioners, researchers, donors, and policymakers to interact with the EGM to derive insights related to their own questions.

Integrating behavioral science into repayment reminders

  • CGAP partnered with Busara Center for Behavioral Economics and Jumo KopaCash—a mobile money marketplace that offers digitally delivered credit—to measure client responses to various repayment reminders. Clients were given interest-free loans via mobile money and asked to repay them after a week in order to access a larger future amount. They found that clients who received evening reminders were 8% more likely to repay their loans than those who received morning reminders. They also tested reminders that varied how they communicated the benefits of repayment. Messages either emphasized ability to access higher future loan amounts or the long-term benefits of repayment. The messages’ results varied by demographic, such as positive effects on repayment across the board for male borrowers and negative impact on repayment across the board for female borrowers.
  • Also with support from CGAP and the Busara Center, Pesa Zetu— a peer-to-peer digital lendertested the impact on repayment of content variations. One test varied the messages received by borrowers to see if different framings could improve borrowers’ on-time payments by creating a sense of social obligation to the lenders. 81% of borrowers who received reminders that included the name or number of lenders who contributed funds, were more likely to repay their loans on the day the reminder was sent, compared to only 27% in the control group.

Up front information disclosure

  • The CGAP, Busara, and Jumo KopaCash experiment also tested information disclosure in a lab setting. Participants played a game in which they earned real money by completing various tasks on a computer. To buy into the game, they had to borrow money that they would pay back with what they earned from completing the tasks. Each loan outlined the different costs and repayment periods. They found that separating out the various associated costs with a loan helped reduce default rates from 29.1% to 20%. The experiment also sought to make the terms and conditions (T&Cs) more accessible by moving them up in the product menu: T&C views rose from 9.5% to 23.8% and those who viewed the content had a 7% lower delinquency rate.

Embedding interactive learning

  • In another CGAP supported experiment, M-Pawa—an interest-bearing mobile money savings account that provides micro loans conditional on savings performance—partnered with Arifu, a mobile learning service, to improve savings and borrowing behaviors among smallholder farmers. Using two-way SMS on financial literacy content, researchers observed that after the interaction, Arifu users take larger loans (1,017 TZH/$0.44), repay sooner (by 5.46 days), and have larger first payments (1,730 TZH/$0.76 more) compared to their behavior before interacting with Arifu.

Limiting credit to certain products

  • With the support of the IDB Group, Empresa de Servicios Públicos de Medellın (EPM)—a large retail store—created and tested the ‘Social Financing Program’ in Colombia. The program provided credit to allow EPM customers to buy various home and personal goods in establishments affiliated with the program. By using its own data to evaluate credit applications, EPM required less information than traditional banks. The initiative aimed to serve low-income borrowers with less access to formal finance by enabling them to build a credit history and buy goods. They found no effect on uptake of other financial tools (such as savings accounts and formal credit). However, the results show that the credit card was associated with an increase in the number of household goods owned, such as floors, kitchens, and bathrooms. The intervention showed mixed and limited results on self-reported well-being outcomes.

The value of being in an ecosystem with more than one financial tool

  • In partnership with Safaricom, researchers piloted the use of a mobile banking account (MBA) and a locked savings account (LSA) to encourage parents to save for their children’s transition to secondary school. Use of the MBA increased the likelihood of credit access within the platform. Parents in both treatment groups were between 3% and 5% more likely to draw on an MBA loan than the control group. The treatment estimates also suggest that between 12% and 18% of users who opened an account as a result of the program took advantage of the credit option.

Detailed insights on digital borrowers in Kenya and Tanzania*

CGAP and FSD Kenya recently conducted two large-scale, nationally representative phone surveys of mobile phone owners in Kenya and Tanzania. The survey findings are numerous and a few are highlighted here.

  • The primary users of digital credit products are predominantly young, urban self- or wage-employed men.
  • Most borrowers use the loans to meet business and day-to-day needs. Loans are rarely used for medical needs or emergencies.
  • Digital borrowers use more financial services than the average Kenyan or Tanzanian adult.
  • About half of borrowers report having repaid a digital loan late, and a significant proportion report having defaulted.
  • Digital credit is only one loan source among many. 33% of digital borrowers in Kenya and 25% in Tanzania were juggling loans from two or more sources (digital and nondigital) at the time of the survey.
  • More than a quarter of borrowers in Tanzania and nearly a fifth in Kenya, reported experiencing poor transparency of fees or terms.

It evident that better transparency and consumer protection requirements are needed and regulators, donors, and investors alike will need to play a role in ensuring the digital credit market grows responsibly.

The takeaways

The evidence on the client impact of digital credit is limited, particularly for longer-term welfare outcomes. But insights, particularly for promoting ‘healthy borrowing,’ are surfacing:

  • The framing and timing of SMS reminders can improve repayment rates and protect borrowers. But the differential effects observed between men and women suggest that further testing is needed.
  • Making T&Cs more salient, accessible, and thus viewed and understood by borrowers may lead to better borrowing behavior and repayments.
  • Using interactive learning content on financial literacy has shown promising results for repayment behavior.
  • Being in an existing financial ecosystem may improve use of other financial services, such as using savings to access loans.

Beyond borrowing behavior, we know very little. In 2016, the Center for Effective Global Action (CEGA) at the University of California, Berkeley launched the Digital Credit Observatory (DCO), funded by the Bill & Melinda Gates Foundation, to call attention to open research questions around digital credit. The DCO noted in 2016that, to their knowledge, “not a single quantitative impact evaluation has rigorously measured the social and economic impacts of digital credit.” This is in contrast to the 90 (quantitative) studies included in a more recent meta-analysis of traditional microcredit. Only very recently has a FSD Kenya supported study provides insights on the longer term effects of a Kenyan digital credit product.

In order to advance the discourse on digital credit, the DCO manages a set of coordinated studies answering key questions related to the impacts of digital credit in emerging markets, as well as the effectiveness of promising approaches to maximizing benefits and minimizing risks to low-income consumers. The research portfolio also considers the heterogeneity of effects of products and their design and delivery on different client segments. Such insights from the DCO are possible due to engaged donors, practitioners and researchers. The digital credit community must continue to look for opportunities to gather impact insights so we keep learning how to best move forward in the journey toward meaningful financial inclusion.


*While this study was concluded after the literature review period ended and thus will be included in the next iteration, the findings provide the most current and detailed nationally representative evidence available on digital credit and related consumer issues for users in East Africa.

FiDA is publishing a series on insights derived from an analysis of the latest Digital Finance Evidence Gap Map (EGM) update. This is the third blog, others will include impact insights on payments and transfers, the design and delivery of various products, and where (people and location) we have been looking for impacts. Previous posts:

The studies in the EGM, represent our best knowledge of digital finance impact insights. New studies are ever emerging and thus the EGM will continue to evolve. If you have questions on the EGM, are interested in discussing research priorities, or know of relevant digital finance impact studies that meet the inclusion criteria, please contact ideas@financedigitalafrica.org.

Digital savings—what do we know about the impact on clients?



FiDA is publishing a mini series on various insights derived from an analysis of the latest Evidence Gap Map (EGM) update. This is the second blog, others will include impact insights on digital credit and payments and transfers, the design and delivery of various products, and where (people and location) we have been looking for impacts. 

Previous blog: Launching the Digital Finance Evidence Gap Map 2.0

Saving is a sound financial practice, particularly for people with lower or fluctuating incomes. Savings help people cope with a poor harvest or a sick family member. Sufficient savings can secure the continuation of children’s educations or allow for the expansion or diversification of a business. Those who save may be rewarded with interest or, as they build a financial footprint, access to credit which—when invested in businesses or income-generating assets, can increase earnings.

As simple as it is in theory, many struggle to save effectively. There are several challenges to overcome such as limited discretionary income, fee sensitivity, access to and availability of appropriate savings products, and savings habit formation.

While numerous studies report the impact of various analog approaches to improving savings behavior and the longer-term results of savings, we focus on if and how ‘digital’ has improved savings behavior among low-income populations.

What are the insights so far?

The EGM includes just 12 studies that evaluated the effect of digital savings products (in 9 countries). It is early in terms of the quantity of insights. Accordingly, we should be cautious about drawing conclusions or rendering a verdict. With the exception of the Tanzanian studies on M-Pawa, these 12 studies involved different markets, client groups and design and delivery mechanisms. The table below illustrates the diversity of the digital savings products that were examined.

Table 1: Design and delivery of savings products

These 12 studies, entail 41 outcomes tests. The diagram below, shows the outcomes tested, and the number of studies that had a positive, negative, or null effect. Positive, negative, and null effects have been observed on client outcomes both across the studies and within a single study. This is indicative of the early stage of testing and learning on digital savings. Over time—with the support of investors, donors, practitioners, and researchers—more products will be developed and tested. As we continue to synthesize the evidence, clearer patterns may emerge and eventually allow us to uncover best practices.

Figure 1: Digital saving impact pathway

Spotlight on selected savings studies

We highlight a selection of insights from our analysis of the studies within the EGM and invite digital savings practitioners, researchers, donors, and policymakers to interact with the EGM to derive insights that match their needs and questions.

Interactive learning and nudges

  • In a CGAP supported experiment, M-Pawa—an interest-bearing mobile money savings account that also provides micro loans conditional on savings performance—partnered with Arifu, a mobile learning platform, to improve savings and borrowing behaviors among smallholder farmers. Using two-way SMS on financial literacy content, the intervention observed that if a customer ever interacted with Arifu, they had a larger number of transactions compared to non-Arifu customers (0.64 more). Additionally, interaction with Arifu’s content led customers to have larger running balances (4,447 TZS/$1.94 more).
  • The Technoserve Women in Business program also partnered with Arifu and M-Pawa to trial two interventions meant to improve business outcomes for female micro entrepreneurs. The M-Pawa intervention provided an M-Pawa training session and allowed clients to set savings goals and receive weekly savings reminders through Arifu. The business intervention included the M-Pawa training session in addition to business skills training. The results showed that women in the M-Pawa group saved three times more than women in the control group, while those in the M-Pawa plus business training group saved almost five times more. The intervention increased the probability of receiving a loan by 14 percent. Regarding business outcomes, the study found that the intervention did not have an impact on business survival. There was, however, evidence that the intervention led to business expansion when combined with business training. Here, women were 4.6 percent more likely to operate a secondary business and generate a small increase (4,000TZS/$1.74) in monthly profits.
  • Bancolombia tested two-way SMS, in partnership with Juntos Finanzasto improve savings balances among their clients. Three months after the introduction of two-way SMS, active new accounts increased by 32.5% and average account balances increased by 50%.

Bringing digital to the door

  • Sri Lanka’s National Savings Bank piloted weekly, door-to-door savings deposit collection services to a randomly selected sample of individuals in rural areas using a wireless point of service (POS) terminal. The weekly visits generated an increase in the frequency of transactions, which quadrupled from a control average of .5 transactions per month to an average of more than  2 per month, and overall savings increased by 15% per month.
  • Opportunity International Bank of Malawi deployed roving agents equipped with a mobile ATM to provide savings services to rural areas. It was expected that access to formal savings services would help households cope with adverse shocks by reducing their use of sub-optimal coping behaviors such as depleting assets. However, the results indicated that having an active savings account did not result in a reduction of sub-optimal coping behaviors. However, the study did find differential levels of impacts based on wealth. For wealthier households, an increase in savings was associated with less reliance on asset depletion. But, the effect was the opposite for less wealthy households.

Variation in types of savings account:default, commitment, and locked

  • In partnership with Safaricom, researchers piloted the use of a mobile banking account (MBA) and a locked savings account (LSA), to encourage parents to save for the transition to secondary school. Balances on the LSAs earn a bonus of 1% additional interest, which is forfeited if funds are withdrawn early. The two savings interventions were promoted to parents, in addition to a control, at the school level. Estimates suggest that being induced to open an MBA increased bank account savings by between 1,000 and 1,500 KES ($10-$15), and being induced to open an LSA increased them by about 500 KES ($5). Parents in both treatment groups were between 3% and 5% more likely to access an MBA loan. Further, use of the MBAs and LSAs was shown to boost school enrollment regardless of the analysis used; opening a bank account was associated with a 27% to 40% boost in school enrollment.
  • In Afghanistan, assigning a default contribution was found to increase employees’ savings contributions. The study found that employees who were assigned a default contribution rate of five percent were 40% more likely to contribute to the account six months later compared to individuals who were assigned a contribution rate of zero. However, while default contribution was found to increase employees’ savings contributions, no effect was noted on a well-being index which included measures such as nights without food, life satisfaction, and physical health.
  • In Mozambique, researchers partnered with mKesh to optimize the mobile money channel as a commitment savings device for smallholder farmers. The savings treatment was based on the offer of a bonus of 20% interest for the average mKesh balance held by an individual before planting season.This bonus was paid in fertilizer. The treatment group also received training on mKesh and fertilizer use as well as a mobile phone. In the first year, the farmers’ average daily savings in mKesh increased by 38% to 44%. Looking at agricultural inputs, statistically significant effects were noted for fertilizer use and owning irrigation pumps.

Overlaying digital elements on a traditional banking service

  • The Family Bank of Kenya tested the effects of ATM cards to boost transactions. ATM cards would reduce the over-the-counter withdrawal fee by 50% and allow for out of hours withdrawals. The ATM cards led to a 68% increase in transactions over two and a half  years and increased the value of deposits and withdrawals. However, while the ATM cards had positive effects on joint accounts and accounts owned by men, it decreased the use of female owned accounts. Researchers hypothesize that women were less incentivized to save when their partner could access their account via their ATM card.

The full 360—changing an analog savings service to a digital savings service

  • A bank in the Philippines piloted a mobile banking system for savings and credit. Previously, members deposited through regular village meetings with bank agents and withdrew at bank offices in town centers. When mobile banking was introduced, members individually made repayments, deposits, and withdrawals through corner stores for a fee. The introduction of mobile banking resulted in a 20% decrease in the average daily balance and a 25% decrease in the likelihood of weekly deposits. This was more pronounced for members who had previously lived close to the bank or village meeting point. A follow-up survey suggested that the decline in savings was driven by the weakened peer effect provided by group banking and increased fee sensitivity. Despite the negative effects, mobile banking did increase the convenience of transactions. Estimates suggest a 30% reduction in the amount of time taken for deposits and 70% for withdrawals.

The takeaways

While we are far from a conclusion, digital savings practitioners, donors, and investors should note the following insights as they further develop and test savings products:

  • Two-way SMS and mobile learning platforms have been shown to enable better savings behaviors
  • Coupling the introduction of savings products with client training—either through digital platforms or traditional modes—appears to bolster clients’ ability to optimise the use of savings in the longer term.The effects of simply providing the savings products on longer term outcomes, is less certain.
  • Incorporating digital elements into existing traditional financial services such as ATM cards or roving agents with POS technology has been shown to improve access to savings products and savings behavior.
  • A total change from an analog service to a digital service needs to consider the positives of the analog service (such as agent interface and peer effects) and carefully design for the transition.
  • Default contributions, locked savings accounts, and commitment savings accounts were all found to improve the savings behavior of clients, and when client training was provided, longer-term effects on welfare were observed.
  • Product design needs to carefully consider the potential differential effects on, for example, women and men, higher and lower incomes, rural and urban, etc. There are cases where some groups benefit more than others.

Researchers, and those who fund research, have a crucial role to play in partnering with digital savings practitioners, articulating robust theories of change for a product, and testing those theories. There are clear gaps in outcomes, products, markets, and, particularly, the client segments tested.

The insights gathered thus far are encouraging and, as a community, we should continue to look for opportunities to gather evidence on the effects of digital savings products.

The studies in the EGM, represent our best knowledge of digital finance impact insights. New studies are ever emerging and thus the EGM will continue to evolve. If you have questions on the EGM, are interested in discussing research priorities, or know of relevant Digital Finance impact studies that meet the inclusion criteria, please contact ideas@financedigitalafrica.org.

Can your personality get you a credit score?



Imagine you have just completed a job and are owed money. Your client offers you a delayed payment option where instead of receiving $14,000 today, you will receive $20,000 in six months. Which option do you take?

This is one among many behavioral and personality questions that a psychometric credit assessment asks potential borrowers. By asking questions that measure an applicant’s attitude, integrity, and performance, a psychometric credit assessment can generate a credit score. And, because everyone has a unique personality and characteristics, this type of assessment provides an alternative for thin-file loan applicants (i.e., zero or low credit history) seeking to obtain loans.

Beginning in 2006, innovative firms like Lenddo and Entrepreneurial Finance Lab (EFL) — later the merged company LenddoEFL — were among the first to pioneer psychometric assessments for lending in emerging markets. In early 2018, FiDA spoke with LenddoEFL to better understand their journey in developing psychometric assessments, and, in parallel, learn more about the experience of Juhudi Kilimo (JKL), a Kenyan microfinance institution, in employing the assessment. FiDA’s case study, “Delving into human consciousness: using psychometric assessments in financial services,” offers relevant experiences using psychometric assessments to financial service providers (FSPs) interested in leveraging non-traditional, alternative data to develop credit scores.

The opportunities and challenges of psychometric assessments

We were told EFL could accurately measure character so it was a test, and if it worked then we could start placing more emphasis on people’s character versus collateral.

JKL

JKL wanted to decrease their turnaround time to make credit decisions, and improve their acceptance rate. In 2016, supported by a Mastercard Foundation (MCF) grant, they turned to LenddoEFL and piloted their credit-score model, to explore an objective way of measuring a loan applicant’s character. As a result of the pilot, JKL improved their acceptance rate by 5% and increased the maximum loan amount available from 67% of collateral to 100% of collateral for high-scoring individuals. Moreover, new ‘high-scoring’ clients received, on average, $40 more (the average loan size is $300) than before the LenddoEFL model was implemented and were also offered access to clean energy loans.

However, JKL had to make the following structural, operational, and technical changes over the course of seven months before implementing this technology:

  • Obtain senior management buy-in
  • Recruit staff
  • Revise loan policy
  • Build infrastructure
  • Train test administrators and loan officers
  • Sensitize loan applicants to the technology

Much as JKL had to transform some components of their operations to implement LenddoEFL’s credit score, EFL (pre-merger), went through their own journey to develop the credit-score tool, outlined in detail in the case study. For example, LenddoEFL learned that developing a psychometric assessment tool requires iterations of data-driven models, customizing the test for the target audience, and complementing the model with multiple data sources.

Profitability requires scale and FSPs should have a clear use case for the technology

A key lesson that LenddoEFL learned is that reaching profitability requires scale. For the moment, LenddoEFL charges clients an integration fee, a one time scorecard fee (i.e., building a customized model for the client), and a price per score with a minimum number of scores purchased per month. The price per score decreases as volume increases and thereafter they charge a recurring fee that begins after the scorecard is built. The FiDA case study outlines the fixed and variable costs that FSPs and/or FinTechs should consider in building their own psychometric assessments; for instance, up to three teams to (a) model the test, (b) deliver the test, and c) integrate the test into the core banking system.

Both JKL and LenddoEFL have learned that FSPs must be very clear on what problem psychometric credit scoring could potentially solve. JKL notes that FSPs should, ideally, first assess their in-house credit appraisal system to understand (1) how effective current tools are in assessing an individual’s creditworthiness and (2) identify any gaps that psychometric assessments could fill.

Lastly, JKL encourages FSPs to conduct a cost-benefit analysis because a return on investment depends on the volume reached/scale of the program. Likewise, LenddoEFL recommends that FSPs plan to lend to at least 10,000 loan applicants a year in order to maximize the value of their tool.

FiDA is confident that the journeys presented in this case study provide a critical perspective on both the challenges and benefits of psychometric assessments in financial services.

Launching the Digital Finance Evidence Gap Map 2.0



FiDA launched the first Digital Finance Evidence Gap Map (EGM) in November 2017 with 40 studies, covering 41 different products. A year on, the EGM includes 55 studies, covering 60 products. Each year reveals more insights on the impact of various digital finance products.

Figure 1: FiDA Digital Finance Evidence Gap Map, studies per year

In the coming weeks, FiDA is publishing a Digital Finance Evidence mini series on various insights derived from an analysis of the latest EGM update. These will include impact insights on digital savings, credit, and payments and transfers products; how various products have been designed and delivered; and where (people and location) we have been looking for impact.

Bringing impact insights together

In 2017, The FiDA Partnership embarked on a journey to answer the question: ‘What is the impact of digital finance on low-income clients?’

The complexity of this question was clear. Digital finance is not ‘one thing’, it is dozens of products, designed and delivered in various ways, to various client segments, in various markets. A single study cannot answer this question. Yet, as we aggregate the various impact insights by product and place them in dialogue with each other we are coming closer to the answer.

FiDA’s contribution to the impact conversation: the EGM

To encourage a continuous dialogue on impact, FiDA developed the EGM. After defining our methodology, we screened, coded, and folded digital finance impact insights into the EGM. At its simplest level, the EGM charts  the landscape of impact evidence—be it positive, negative, or null—for a set of digital finance products, plotted against a set of client outcomes. However its interactive design and filters enable users to scan for evidence for questions as specific as ‘Does X product, designed with Y features, delivered in Z ways, to clients in A market lead to B outcomes?’ Thus, if you wanted to search for evidence on a digital credit product using two-way SMS in Ghana, you can—provided such a product has been developed and tested and the resulting insights published.

Using the EGM

We envision several ways in which various types of users might use and benefit from the EGM:

Digital finance product and service developers and practitioners

  • Search for evidence of what has been shown to have client level impact, to inform current and future digital finance products.
  • Derive insights on which design and delivery mechanisms have (or have not) improved the adoption of a given digital finance product.
  • Use evidence to advocate and fundraise for new approaches in areas where there is little evidence(and thus help fill an evidence gap) or to scale existing products.
  • As the EGM folds in more studies over time, it may reach a level of evidence saturation that will allow practitioners to develop guidelines for practice in areas where there is substantial evidence of what works.

Digital finance investors

  • Help make evidence-based, strategic investments in areas where there is ample, high-confidence evidence of what works, what is unknown, and what is untested.

Donors

  • Identify and support the development of a body of practice in infrequently explored areas by funding programs and or research, where there is little evidence on a product, a population segment or a market.

Digital finance researchers

  • Conduct an evidence synthesis on a digital finance product, a client segment, or a market.
  • Review gaps in evidence on various products, populations, or markets and make investments to advance the impact conversation.

What is in the latest version of the EGM?

In the updated EGM there are 55 studies that test 60 digital finance products and interventions from 24 Countries. There are 14 digital finance products and 28 design and delivery mechanisms with various counts of evidence. Study design includes RCTs (23%), panels (18%) cross sections (18%), provider data (10%), A/B tests (8%) and mixed methods (8%). Here, we share some high level findings, which we will investigate further in the forthcoming series.

Geography: While 24 countries are represented in the EGM, Kenya alone accounts for over a quarter of the studies (27%), the East Africa region accounting for over half (52%) of the impact literature.

Figure 2: Number of countries represented in the Digital Finance Evidence Gap Map

Digital finance products: Across the 55 studies, 60 digital finance products were evaluated. Digital payments and transfers account for 52% (n=31) of the impact literature. When general mobile money studies (i.e., studies that did not specify the mobile money product used) are included in this category, this increased to 65% (n=39) of studies.

Figure 3: Number of digital finance products tested

Client outcomes: Across the 55 studies, there are 188 ‘tests’ linked to the 10 client outcomes. The tests are more concentrated at immediate outcomes (adoption: 13% and savings behavior: 16%) and longer term outcomes (resilience: 15%, welfare:16%, and income investing/asset building:11%). The outcomes vary at a product level analysis.

Figure 4: Number of tests per client outcome

Positive leaning results but mixed at a product level examination. While the number of studies currently available is small, considering the growth and diversity of digital finance products, we observe positive, negative, and null effects across the various digital finance products on various client outcomes. 65% of the reported tests were positive, 9% were negative, and 26% were null. However, when we review product level effects in the coming series, we will see that this proportion is varied. For example, when we look at credit products, 57% of the tests are positive, 19% negative and 24% null.

It is important to state that this does not mean digital finance products ‘work’ 65% of the time or digital credit ‘works’ 57% of the time. We are looking at 60 different products where, in aggregate, 188 tests on various outcomes were examined. On average, a single study did three outcome tests (ranged from 1 to 13). Across the 60 products examined, 55% (33) reported exclusively positive results, 0% reported exclusively negative results, 7%(4) reported exclusively null results, while 38% (23) reported a mix of positive, negative, and null results. Just one study reported only negative or null findings. So in 38% of products, some outcomes improve, some are unchanged, and a few regress.

We are at the beginning of our journey toward understanding the impact of various digital finance products. Researchers are, and should be, casting their nets wide—testing a broad range of outcomes—to interrogate various theories around the impact of various products. If a product tested two outcomes and found no effects, it does not mean that the product does not move the dial at all, but rather that what it may move the dial on was not examined. Choosing what to test is important.We refine these choices through continued testing and learning.

Figure 5: Proportion of tests by results per client outcome

We have much to learn as a community; but the digital finance EGM  collates our learnings so that we can better approach an answer to the impact question. As more products are tested, and the findings published, we can form impact pathways for each type of digital finance product and provide the community with a tool to delve into  the design and delivery mechanism, the market, and the social conditions in which the digital finance product was (or was not) successful in catalyzing change.

The studies in the EGM, represent our best knowledge of digital finance impact insights. New studies are ever emerging and thus the EGM will continue to evolve. If you have questions on the EGM, are interested in discussing research priorities, or know of relevant Digital Finance impact studies that meet the inclusion criteria, please contact ideas@financedigitalafrica.org.

AI and Big Data have transformed digital finance in China. Can they do the same in sub-Saharan Africa?



This blog has been co-authored by David del Ser, Practice Director at Bankable Frontier Associates and David Edelstein, Senior Director at FiDA Partnership

The recent FiDA Partnership trip to China was eye-opening in many ways: ranging from the speed of adoption of digital financial tools to the sophisticated ways in which financial services are built around nuanced client behavior to the rapid growth of online to offline linkages.  We heard a lot about “A, B, C and D”: the use of Artificial Intelligence (AI), Blockchain, Cloud Computing and Big Data to transform how financial services are developed and delivered.  

We were particularly impressed with advanced applications of AI and Big Data and the critical “behind the scenes” roles they play.  In this blog we highlight some illustrative examples from China, identify how these approaches can be applied to the African context and suggest some practical approaches to begin to harness the potential.

AI and Big Data Enable Practical Innovation in China

Accelerated Customer Acquisition and Support

The use of AI and Big Data is pervasive in the development and delivery of financial services in China. For example, Yirendai, the largest P2P lending platform in China and a rapidly growing investment platform, relies on AI to help customers evaluate risk and recommend loans.  Their automated bot, Yiri, which provides investment advice and education, has led to an increase of 50% in assets under management and is slated to be the primary entry point to all of Yirendai’s services.

Our group visit Yirendi’s Office in Beijing

Breakthroughs in Core Banking Software

In another example, WeBank, partly owned by Tencent, has built an advanced back-end platform relying heavily on AI and Big Data to support a range of accounts and transactions.  The service, which they white label and license to financial institutions, costs ~$1/customer/year at scale, nearly fifteen times less than a traditional banking platform. WeBank has achieved this impressively low cost through heavy use of chatbots (which handle 96% of transactions) and reliance on AI for preventative maintenance and to achieve other back-end saving.  AI is also used to assess microloans, drawing on tens of thousands of data points using both financial information and WeChat’s social data to assess creditworthiness. With this sophisticated technology in the back-end, one-third of people who draw upon WeBank credit have no previous credit history — and the non-performing loan rate is below 0.7%.

Reductions in Credit Risk and Costs

And Alipay, owned by Alibaba, relies heavily on big data, AI and biometrics to assess credit risk and reduce fraud.  Able to reduce the fraud rate to 0.001% (as compared to 0.2% for PayPal) and relying on large economies of scale, Alibaba has driven down transaction costs to well below 1% (compared to 3% to 4% at PayPal) and close to zero for P2P transactions.  They also proactively “white list” users based on a large number of factors.

These stories of low-cost scale provide a glimpse of how leading companies in China have embraced AI and Big Data to extend the reach of financial services.  Indeed, many consider themselves technology companies first, which happen to provide financial services, and have adopted the TechFin moniker.

Opportunities to extend approaches from China to sub-Saharan Africa

While China does benefit from a somewhat unique enabling environment, there are a number of ways in which companies in sub-Saharan Africa could benefit from strategies employed in the digital finance revolution in China.  

Some of the “lowest hanging fruit” involves extending knowledge gained and approaches taken using AI to the African context.  Talent to effectively use AI techniques has been a barrier in the past — but through a combination of using newly-available advanced tools (e.g., WeBank example), a growing talent base in Africa and the ability to rely on talent from outside the region, these concerns can be ameliorated.  

AI tools typically require large amounts of aggregated data.  Mobile network operators (MNOs), and to a lesser extent financial institutions and PayGo Solar players, possess or are amassing such data.  Through strategic partnerships and adoption of existing tools these companies could be doing more with the information they have, for instance predicting payment behavior to reduce churn.  For now (due to regulatory concerns around sharing/selling data), the use of AI and Big Data may be limited to optimization within companies, but in the future data sharing across companies may be able to provide a more detailed and nuanced understanding of clients.  African companies can learn from the value of big datasets and creative partnerships (to build big and diverse datasets) which we observed in China. While leveraging big data in Africa is still in its early days, the opportunity should be taken seriously.

The opportunities on the “back end” are more immediate than those on the “front end”.  This begins with the low penetration of smartphones (relative to China) and on-going reliance on USSD.  While China made a rapid leap from feature phones to using smartphones to read QR codes and conduct financial transactions, in sub-Saharan Africa the path has involved mobile money and slower adoption of smartphones.  The leap in China has enabled sophisticated use of AI on the front end — such as biometrics for KYC and facial recognition based on selfies — which will only be possible in Africa with big advances in smartphone usage.

The “silver lining” of the African path may be the extensive CICO agent networks — which generate a large amount of data.  While lacking e-commerce and smartphone data, the AI journey in Africa can draw upon the data held by MNOs, financial institutions and PayGo providers, and benefit from the growth of smartphones.  Indeed, we are already seeing companies like Pezesha, Tala and Branch capturing their own data from their apps.

What can be done today — and over time

So what can be done now?  We will close with a few pragmatic recommendations of actions that can be taken by companies in sub-Saharan Africa to benefit from advances in AI and Big Data seen in China.

We were struck by the degree of collaboration between companies in China.  This ranged from sharing data to using advanced tools to better understand and serve clients (see recent blog on this collaboration).  Neobanks in Africa should consider using advanced tools from WeBank and other providers (from China and elsewhere).  To the extent allowed by regulators, MNOs, Financial Institutions and PayGo providers should share data to develop richer consumer profiles.

Companies should consider “non-traditional” types of data — both information that may be lost today (in China factors such as how hard a user pushes on the screen and the angle the phone is held are captured and considered) and “non-traditional” sources of data (companies tapping into alternate sources of data exist in Africa — but much more could be done).  When brought together these often yield unexpected insights about consumer behavior. Knowledge of local context combined with thoughtful, applied use of data holds a lot of potential.

As smartphone penetration expands consider creative approaches to tap into the multiple data streams.  Companies today are just skimming the surface of what can be done.

Over the longer term the home-grown talent base must be strengthened.  Institutions such as Ashesi University in Ghana, the African Leadership Academy in South Africa and the Mastercard Foundations Scholars Program are pioneers — and others can and should learn from them.  

Can China’s Ethos of Collaboration Work for Africa?



This blog was authored by Annabel Schiff – Senior Manager, Partners at the FiDA Partnership – with input from Lesley Denyes – Program Manager and Digital Finance Specialist at IFC

In China, collaborative relationships have played an important role in driving financial innovation and inclusion in the country. In Part 1 of this blog series we discussed the Chinese ethos of building the digital finance space together, based on insights from our recent FiDA Partnership fintech study tour to China. In this blog, I touch on the existing partnership landscape in Africa, as well as some of challenges in recreating China’s collaborative atmosphere.

The Partnership Landscape

Partnerships and contractual relationships between banks and non-banks

Partnerships are happening in Africa. In fact, they are critical to the success of digital finance either to fulfil regulatory requirements, as a means to provide mutually beneficial and essential channels (e.g. funding, distribution, communication), or as an avenue to grow both service offerings and customers.

MNOs partnering with banks to offer more sophisticated products

MNO-led bank partnerships – such as Safaricom and CBA’s M-Shwari product – enable mobile money providers to offer products beyond payments and in turn enable banks to reach a wider audience. These types of partnerships, however, also face challenges. A good example is the unsuccessful partnership between Equity Bank and Safaricom through which the M-Kesho product was launched. Both partners struggled to define a mutually beneficial partnership, in part due to them perceiving each other as competitors rather than partners.  

Banks partnering with MNOs to reach new customers and grow their business

We also see banks and MNO’s cooperating when a bank wishes to develop their own digital finance brand in order to grow their customer base. They therefore partner with an MNO to leverage its infrastructure for the delivery of digital finance. For example, in 2015 Equity Bank in Kenya signed a contractual agreement with Airtel to leverage its access channels to deliver their Equitel service.

Equity Group CEO James Mwangi with former Airtel Africa CEO Christian de Faria (photo credit: www.kachwanya.com)

Partnering for regulatory compliance

Partnerships between banks and MNOs also take place for regulatory reasons. In bank-led markets, such as Pakistan, Bangladesh and to an extent Uganda, non-banks are required to either buy a bank, or partner with one, in order to be issued an e-money licence. While the majority of bank-led services are found in Asia, Uganda also regulates that non-banks must partner with a licensed financial institution to offer digital financial services. In Uganda, these banks tend to sit in the background while the MNOs design, brand, market and distribute the services.

Partnerships to enable wallet-to-wallet interoperability

Wallet-to-wallet interoperability between MNOs is one of the most notable examples of industry cooperation in Africa. In fact, countries such as Tanzania, Rwanda and Kenya that have introduced interoperability at the wallet level are ahead of China where wallets still do not interoperate. In Tanzania providers have noted how interoperability has impacted the quality of services, focusing them on driving “value into the system, rather than growing our own, segregated network”. Despite the potential commercial and financial inclusion benefits of interoperability, expansion has been slow. Even in mature mobile money markets such as Kenya, interoperability has only just been established, and the jury is still out regarding the success of the interoperability pilot.

It is important to note that interoperability enabling transfers between mobile money accounts and bank accounts, is more common and better established. In their 2017 State of the Industry report, GSMA noted that bank-to-mobile interoperability has contributed to a notable rise in funds entering and leaving the mobile money ecosystem in digital form.

Cooperating with the fintech players

Traditional mobile money providers, such as banks and MNOs, are also cooperating with fintechs, who tend to be smaller, more agile, technology-focused organisations. The ecosystem manager at Barclays’ Rise innovation hub in Cape Town highlighted that the reality for fintechs is like the African proverb: If you want to go fast, go on your own. If you want to go far, go together. For small fintechs, partnerships are key to helping them not only access funding, but also reach new customers, overcome regulatory constraints, train data to develop new and better models, and access necessary technology to delivery their services. For banks, the pressure to innovate has led many to invest in and collaborate with fintech start-ups. For example, in 2015 Barclays opened a product lab in Kenya and Standard Bank launched incubator programs in Johannesburg and Cape Town.

Challenges with Building this Collaborative Environment

Heavy OPEX investment can breed competition rather than collaboration

In China the government has invested heavily in driving financial inclusion by mandating state-owned banks to roll-out cheap bank accounts, resulting in 80% of adults having a bank account in China. High bank penetration means that rather than relying on a cash-in, cash-out (CICO) network, customers seamlessly load funds into their digital wallets through linkages to their bank accounts. While customers can cash out at some retail locations, there are no agent networks.  

In contrast in Africa, owing to low bank account penetration, financial inclusion is increasingly driven by mobile money. While digital finance has helped accelerate financial inclusion, most African digital finance providers have had to invest heavily in building out their own CICO agent network. Agent network management is the most costly element of a digital finance business; costing between 40–80% of revenue. Such significant investment not only excludes smaller players, but also reduces incentives for larger players to open up and enable other providers to ride on their distribution channels, hence the slow uptake of wallet interoperability. While some African markets have set regulations against exclusive agents, in most markets mobile money is yet to be interoperable at the agent level. For those who have invested heavily in agent networks, they have also likely invested in building up a brand reputation and trust among their customers. The legacy of heavy investment can breed an ethos of competition rather than collaboration.

M-PESA agent in Nairobi, Kenya

Alternative lenders struggle to partner for loanable funds owing to lack of scale

FIBR’s research in Ghana and Tanzania showed that, unlike China, regulation prohibits non-financial institutions to lend. Beyond regulatory restrictions, funding obstacles exist due to early stage risk. Much of this is related to a lack of scale, data, and thus weak algorithms to develop credit-score models.

In contrast China comes with scale. The online population size is 730 million, twice the size of America. African countries, even Nigeria, are small in comparison. With scale comes data, which not only enables providers to trial products more effectively, but also allows them to more efficiently test algorithms. This is why technology companies in China are able to negotiate low cost loanable funds from banks by proving their credit score model (see the JD Finance example in Part 1 of this blog). In Africa, digital finance players and even large banks are still refining their models and algorithms. Weak, unrefined algorithms have resulted in banks tending to finance on-lenders at a high price due to the risks involved, or fail to provide any funding at all.

Partnerships to help expand data sets have been slow

It is not only scale that helps Chinese fintech players garner huge swaths of customer data, but also their product offerings. In China, merchant payments led the digital uptake, driven by technology companies who layered payments on top of existing use cases, such as Tencent with their social network and entertainment offerings, and Ant Financial with e-commerce.  As mentioned in Part 1 of this blog, payments permitted players to gather valuable data on customers which, along with their existing customer insights, enabled them to develop more sophisticated financial services.

In contrast peer-to-peer payments first drove adoption in Africa. Merchant payments have struggled to take hold, except in Kenya where Lipa Na M-Pesa has gained some traction, and South Africa where bank cards and POS terminals are widespread. The lack of merchant payments means less engagement with customers, and therefore less data. Without the prevalence of merchant payments, there is the question of what data could be used to develop new financial services products, particularly data-driven digital credit products for which there is latent demand. A recent IFC market survey asked “What product will lead DFS adoption in the near future?”: 30% of respondents said credit and 25% said merchant payments, beating out P2P at 23%.  While digital finance players are exploring partnerships with non-financial institutions to help fill these data gaps, the uptake of big data and analytics in the region has been slow.

Conclusion

In the end, partnerships are good for customers.  They create options, promote competition and inspire innovation. The Chinese digital finance journey illustrates the value of collaboration, for both providers and customers. Most African countries present a very different commercial landscape with significant barriers to a similarly collaborative environment. However, as traditional bank and MNO revenue streams come under increasing pressure, we will likely see a shift towards business models with a higher reliance on collaboration. Looking to the Chinese experience may present some valuable lessons when the time is right.

How to study MSMEs in the digital era



In the coming months the FiDA team will be conducting new research at the intersection of two broad themes: financial inclusion in the platform era and enterprises and financial inclusion.

Apart from agriculture, Micro, Small, and Medium Enterprises (MSMEs), are the greatest source of employment in many countries in sub-Saharan Africa. They have have long been a focus of interest to the development community, but as digitization transforms the nature of work—from gig economies to international supply chains—the links between MSMEs and ICTs are increasingly important. We’ll be exploring how, in particular, the spread of ‘platforms’ (Google, Facebook, Alibaba, etc.) creates new models for (and avenues to) financial inclusion.

As we get underway, we’d like to share the results of an exercise we conducted to help focus our research. Granted, it’s basically a 2×2, and as consultants we know these are common, but in this case we think it’s durable and useful to share.

The first dimension in our table is the size of the firms in question. In our discussions, we found that the definition of MSME was quite broad; accordingly, we distinguish ‘Micro’ from ‘Small and Medium.’ However, there is no hard and fast rule for drawing this line. Some countries define microenterprises as firms with <10 employees, others draw the line at <5 employees. For sub-Saharan Africa, where firm sizes tend to be smaller (and the majority of firms are sole proprietorships) we think the <5 delineation makes more sense.

  • Firms with fewer than five employees—both sole proprietorships and microenterprises, are the most numerous type of enterprises. Many are informal, and most struggle to grow. Microfinance rose as a community of practice specifically to address the needs of these tiny businesses, and the literature on them, their use of ICTs, and their challenges is now quite robust
  • By contrast, Small and Medium Enterprises(SMEs) are usually formal, registered, and paying taxes. These firms also face challenges vis-a-vis financial services, but they are not so much challenges of access as they are of suitability or affordability—loan terms might be too short, bank fees too high, etc.

The second dimension refers to the nature of the enterprise as it relates to the digital economy. As Duncombe and Heeks have explained, there’s a key distinction between small firms that benefit from ICTs and small firms that produce ICTs. We see a durable conceptual split between ‘the broader economy,’ which is benefiting from and being transformed by digitization, and the subset of firms with ‘digital DNA’, which are making the products, delivering the services, and writing the code that underpins that digitization.

A related but distinct category of firms are the platforms themselves—the handful of multinational superplatforms as well as a larger set of local and regional electronic marketplaces—that are transforming sectors of the economy in real time. This is what we mean by ‘the platform era’: platform logic has become central to the ways in which digitization and the internet are changing economies, and this platformization is a major theme for our work in the year ahead. Our typology is more clear if we place platforms in a different section of our framework.

The result is a 2×2 with a modified adjunct for the platforms themselves. As you can see, the research topics than emerge are distinct enough to clarify the most relevant research questions:

  • Box 1 involves the largest number of firms in any economy. Here we are dealing with the struggle of the everyday, how firms  from small restaurants and fix-it shops to retail establishments might utilize national and global platforms in new ways. Research here would (and will!) explore how the traditional clients of microfinance institutions are adapting to the platform era. It could focus on the ways in which social media and the personal Internet is being appropriated to fit the needs of the smallest firms, even when the lines between entrepreneur and enterprise are blurred.
  • Box 2 is quite different in that platforms may be providing new opportunities for small-scale economic organizations with ‘digital DNA’ to offer products and services in entirely new ways. The best, and perhaps most controversial, example of this might be gig work whereby individual proprietors or small firms utilize the infrastructures of labor platforms to earn livings in the cloud, mediated completely by the platform.
  • Box 3 involves a country’s established, formal SME class. How do these firms adapt to the platform era? There are a host of innovations, from inventory and product management to advertising and financing, that can be offered at lower cost and higher value to these firms thanks to digitization. How, specifically, are the platforms involved with these new offerings?
  • Box 4 involves digital startups; the stuff of businesses coming out of accelerator programs and preparing to take off. Many are businesses that write the software or design the new hardware that is customizing the global Internet and other digital technologies for African markets. There’s a great deal of enthusiasm around these businesses, but the research that one would do to understand a digital startup differs from the research  one would do to understand the motorcycle repair shop just down the street. Both are enterprises, but they occupy very different places structurally, both in terms of their local economies and their international visibility.
  • Box 5 is our floating adjunct to the 2×2, our acknowledgment that the platforms themselves deserve and require significant scrutiny. From Jumia to Sendy to WhatsApp for business, the terrain of platform-related digital services is shifting and expanding. Yet there is  little work that specifically engages with the interface between platforms and all four of these MSME segments, particularly with respect to financial inclusion outcomes. Recent findings from FIBR, an R&D project of BFA in partnership with Mastercard Foundation, are beginning to fill this void, looking first at how Tanzanian merchants are moving online.

Our next research project, kicking off in late 2018 in Kenya, will explore the connections between “box 1” microenterprises and the “box 5” platforms that serve them.  

All in all, there’s a lot of work to be done. The point of this post is to sensitize readers to the importance of a bit of specificity regarding terms so that a generalized enthusiasm for platforms and/or MSMEs does not get in the way of refined research questions that can uncover new insights. We look forward to sharing updates about the research as it nears completion.