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Is digital finance changing the lives of the “excluded” for the better?



Snapshot 4: “How do advances in digital finance interact with dynamics of exclusion?” addresses one of the key questions of FiDA’s Learning Themes. The FiDA Partnership synthesizes the digital finance community’s knowledge of these Learning Themes as “Snapshots” that cover topics at the client, institution, ecosystem, and impact levels to present “current insights” about the topic in question, highlight “what (the digital finance community) can do,” and call attention to “implications” for future research and investment.

Grace is 55 years old; she has a primary school education and a small business selling produce in her village. Her husband owns a mobile phone, but she does not. Benson is 30 years old; he has a secondary school education, and works in the city as a taxi driver. He owns a mobile phone. Grace and Benson learn  about a digital credit product that provides small loans through a mobile phone.

Do you think Grace and Benson will have the same experience accessing and using digital credit?

Why we wrote this Snapshot

When digital financial services are designed for broad populations, it’s easy to assume that different demographics within a population will use them in the same way and experience the same impacts. Yet, factors such as age, literacy, gender, geography, and language shape the nature of the adoption, use, and impact of digital finance. That is,  a digital credit product’s effect on an outcome like “growth of business” may be greater or less depending on the client’s age or education. A recent analysis by CGAP and FinMark Trust highlighted the distinct variables that can compound exclusion from financial services.

Snapshot 4, “How do advances in digital finance interact with dynamics of exclusion?” discusses persistent issues surrounding exclusion and how digital finance research measures exclusion. We offer these  observations to sensitize researchers and practitioners to the importance of these dynamics and encourage exploration of how distinct variables of exclusion determine how marginalized groups experience outcomes.

Don't assume effects are universal

The prevailing narrative around the impact of technologies on a given population is a variant of the idea that a rising tide lifts all boats. Yet, research rarely presents dis-aggregated insights. Instead, studies report the average effect which suggests that every individual in the study experienced the reported effects equally. A review of digital finance impact studies from FiDA’s Evidence Gap Map found that 78% of studies did not report even a  basic variable: gender dis-aggregated data. While, studies with just women result in useful insights, if we do not look at the way digital finance is used by women in comparison to men, it is impossible to argue that a digital finance product or service has been more or less helpful to those women than it would have been to other segments of the population.

Sometimes the marginalized benefit more

When the design of a digital financial service syncs with the needs of an excluded group, the benefits of using it accrue disproportionately to them. Snapshot 4 highlights digital finance studies that present instances in which being female, less educated, lower income, or from rural areas was associated with greater effects than being male, more educated, or from urban areas. For example, an impact study in Burkina Faso highlighted that while mobile money made no difference in the savings behavior of relatively advantaged groups (urban, male, and highly educated), it increased the probability of saving for disadvantaged groups (rural, female, and less educated).

Sometimes the marginalized benefit less

Unfortunately, there are many cases in which the benefits of a technology accrue mostly to high status, high skill individuals, rather than to the marginalized populations we often wish to serve. Snapshot 4 highlights a study that found, for higher income households, that an increase in savings services was associated with less reliance on asset depletion to cope with economic shocks. However, an opposite effect was observed for those with lower incomes.

These observations can provide the digital finance community with a more refined understanding of impact by determining the conditions under which impact applies or is stronger or weaker. They also underscore the need to examine how a digital finance product may interact with and affect various excluded groups.

Build and evaluate strong theories of change

What to do when faced with these dynamics of exclusion? We foreground that the first step is to develop theories of change that allow for impacts to accrue differently to different user groups. This is fundamental to understanding the potential impact heterogeneity and, ergo, to designing impact research. A heightened awareness of these challenges will help practitioners plan appropriate digital finance services that their underserved clients will want , and be able, to use regularly. 

Read Snapshot 4 for more details on our findings, implications, and a list of the top-10 reads in the space.

The state of the Mobile Money industry in 2017



This guest blog was written by Francesco Pasti, Senior Manager of Mobile Money Services at GSMA.

Numerous new trends emerged in mobile money throughout 2017 – from the accelerated growth of bank-to-mobile interoperability, to the emergence of South Asia as the fastest growing region, and a raft of innovations designed to reach the most underserved. The mobile money industry is now processing a billion dollars a day and generating direct revenues of over $2.4 billion. With 690 million registered accounts worldwide, mobile money has evolved into the leading payment platform for the digital economy in many emerging markets. The 2017 State of the Industry report on Mobile Money from the GSMA sheds light on several factors underpinning the success of a growing number of mobile money providers: a sustained focus on activity rates, the digitisation of platforms and measures to reduce the net cost of the agent network. On each of these fronts, the trends in 2017 were positive.

A growing number of mobile money services are achieving activity rates of over 50 per cent

While average industry activity rates grew modestly to 36 per cent in December 2017, a closer look reveals significant variation among providers. Our analysis shows that these providers all have a strong distribution network, enjoy enabling regulation, and rely more on an account-based business model.

More funds are entering and leaving the mobile money ecosystem in digital form

Use cases such as bulk disbursements, bill payments and bank-to-mobile transactions have been the main drivers of this trend. As mobile money becomes more digital, it is connecting the wider economy and, in turn, becoming more profitable for providers and more useful to consumers.

Many successful providers are decreasing the net cost of the agent network

Agents remain a crucial and distinguishing asset of mobile money providers. In recent years, we have seen growth in the number of active agents and average values processed by agents. At the same time, the inflow of digital funds is reducing provider costs, by alleviating the need for subsidised cash-in agent commissions.

Amidst a changing landscape that sees the spread of smartphone and fintech companies and an increased digitisation of new sectors of the economy, mobile money providers serving as a payment platform for a broad range of entities appear to be best placed to thrive.

The persistence and scale of the cash economy in emerging markets means that complex distribution networks remain crucial for digital services to interface with physical lives. By leveraging these enduring assets and finding new ways to connect scale with innovation, mobile money providers can serve as a gateway to the widening array of digital services in emerging markets.

Policy objectives will play an increasingly important role, as the scope of mobile money regulation broadens. While the pace of core regulatory reform is slowing, this masks two important emerging trends: the extension of new areas of regulation to mobile money and the rapid spread of financial inclusion policies. As regulators confront questions around data protection, regulatory sandboxes, and more, the policy end game of greater inclusion must remain at the fore.

Read the full report for the detailed analysis of these levers to growth and sustainability, and for spotlights on success stories and examples of innovation from mobile money providers around the world.

What makes a successful commercial partnership?



Snapshot 10: “What makes a successful commercial partnership?” addresses one of the key questions of FiDA’s Learning Theme 10. Each Learning Theme addresses a range of topics within the digital finance space. The FiDA Partnership synthesizes the digital finance community’s knowledge of these learning themes as “Snapshots” that cover topics at the client, institution, ecosystem, and impact levels to present “what we (in the digital finance community) know” about the topic in question, highlight “notable new learning,” and call attention to “implications” for future research and investment.

In 2016, Paypal, a US based online payments system, partnered with two of the largest global credit card networks, Mastercard and Visa, and concurrently invested in a FinTech platform, Acorn. In doing so, Paypal became a bridge between traditional financial institutions and emerging FinTechs. Collaboration may extend the value of Paypal’s services to more people, expedite innovation, and future-proof Paypal in this era of rapid mobile-based innovation and the rise of large internet players.

On the other side of the Atlantic, digital finance players appear to have an increasing appetite for collaboration. For example, Safaricom’s M-Pesa, the Kenyan mobile money giant, and the Commercial Bank of Africa (CBA) in Kenya, partnered to deliver the savings and microloan product M-Shwari. Leveraging Safaricom’s dominant position in the marketplace allowed the product to successfully scale: as of 2016, M-Shwari accounted for approximately 15% of CBA's total revenue. The partnership has succeeded because each partner has a clear understanding of their respective roles and how the product benefits the interests of each. CBA, a corporate bank that targets higher net worth individuals, benefits from the large pool of savings without diving into the operational challenges. Further, CBA does not necessarily want to brand within M-Shwari’s target market, and thus only Safaricom brands the product. In turn, Safaricom benefits from the banking infrastructure of CBA without which it would not be able to provide loan services.

These and other examples suggest that there is a business case for dominant players in financial services markets to collaborate at the ecosystem level. However, a number of factors determine whether a digital finance provider will collaborate in a financial services market as Snapshot 10, “What makes a successful commercial partnership?” explores in detail.

What influences players to collaborate? 

In essence, power dynamics in a financial services market influence how digital finance players engage with each other. Market conditions, such as a fiercely competitive market or a quasi monopoly environment, determine players’ actions. In some markets it may be neither necessary nor fruitful for players to collaborate. Providers who have highly dominant positions—such as b-Kash in Bangladesh which accounted for about half of the market presence in digital finance in 2016—may be reluctant to share scale advantage with smaller competitors. They may prefer instead to forego the advantages of interoperability — which provides interconnection, payments aggregation, and infrastructure sharing — to lock in their market position.

However, in fragmented markets where competition is greater,  digital finance providers stand to benefit from working together to pool their customers into one interoperable network in order to enable interconnection and payments aggregation. For instance, mobile money providers in Cote D’Ivoire collaborated to provide a universal and accessible digital school registration and fees payment solution along with a streamlined user experience. The program worked because its services were attractive to each of the stakeholders: the MNOs benefited from increased revenue flows and the government benefited from the cost savings and reduction in lost payments.

Moreover, the increasing success of mobile insurance services and the tangible benefit it brings to all stakeholders justifies collaboration between specialist providers and digital finance providers. In 2014, 64% of mobile insurance services were launched by MNOs in partnership with specialist solution providers. An MNO might use such a partnership strategically by offering the insurance product under its own brand. Or, in a purely transactional  partnership, the MNO might only provide the platform. For new launches in 2015, 57% of services collected premiums through airtime deduction;the remaining 43% relied on mobile money as the primary payment option.

New players will bring new business models

Digital finance providers are looking to the future. The imminent threat of large internet players is driving partnerships between new types of players in the digital finance space, such as that of  M-Kopa, a pay as you go solar energy provider, and Safaricom. These types of collaboration can facilitate cross-network mobile payments which encourage a larger population to use digital financial services, and, in turn, help digital finance achieve its social and commercial potential. Snapshot 10 discusses the necessary ingredients of a successful partnership: such as  a long-term vision of the partnership and each partner working from the position of their strengths and competitive advantages. Successful partnerships have demonstrated — such as in the case of the Kenyan savings and loan product, M-Shwari — that they have the potential to reach a large number of unbanked but mobile enabled customers and thus extend financial inclusion.

Read Snapshot 10 to learn more about what it takes to successfully collaborate, the new types of partnerships that are evolving, and the top 10 must reads in this space this year.

Can big data shape financial services in East Africa?



Every minute of every day millions of users in Africa create digital data. This new data is creating opportunities for alternative “big data” to catalyze an expansion of financial services to low-income and hard to reach populations. FiDA’s Snapshot 9, “Best Practices in Big Data Analytics” and FiDA’s Focus Note, “Can Big Data Shape Financial Services in East Africa? discuss the potential of big data analytics in financial services in greater detail.

Snapshot 9 focuses on the opportunities created by big data  — such as the number of lending and insurance products that have launched across sub-Saharan Africa. Indeed, mobile credit services are leveraging usage and behavior data to determine which customers can be granted small amounts of credit (cash or airtime) over their mobile phones. However, the extent to which companies are using mobile operator data and other big datasets is not well known. The return on investment in big data analytics is another unknown quantity still. What types of data, particularly what types of big data, are being used? Are the benefits tangible — how do the results from big data compare to those of traditional underwriting methods? What costs and risks exist? Is a market for data developing?

The FiDA Partnership’s Focus Note, “Can Big Data Shape Financial Services in East Africa? sets out to answer some of these broader questions. The Focus Note shows how 30 leading organizations — including Kenyan and Tanzanian banks, microfinance institutions, mobile network operators, and FinTech organizations — think about big data and analytics and how they use (and how they don’t use) big data.

FiDA’s  research found that players do not exchange and profit from big data directly. Rather companies have focused on developing relationships on a case-by-case basis to provide analytics of traditional or big datasets. This has led to a slow (but steady) uptake of big data and analytics and, as a result, a more measured expansion of services leveraging alternative methods. According to the interviewed organizations, four factors constrain rapid growth in this sector:

  1. Lenders have a limited use case for third-party data. Traditional underwriting practices still dominate credit decisions and repayment data and are seen as the most accurate predictor of risk. Big data is mainly used to determine a client’s ability to pay, typically with reference to low-denomination, short-term loans.

    Increasingly, lenders are exploring the use of big data to assess willingness to pay, however, there are limitations, including the ability to validate quality and authenticity. Marketwide data is typically neither structured nor detailed enough to be used in a meaningful way. However, one type of marketwide data — satellite data — is proving useful for several FinTechs.
  2. Organizations are pursuing partnership models in lieu of transactional relationships. For a variety of reasons, including compliance with laws and regulations, preserving customers’ trust, and maintaining an early competitive advantage, organizations are treading cautiously with customer data. As a result, relationships between players working in this field resemble partnership structures rather than transactional marketplaces. While the financial services ecosystem is evolving slowly in East Africa, the strategy behind partnerships allows players to explore what is possible with data and analytics on a case by case basis. Moreover, this partnership trend is likely to continue because MNOs need to rapidly build an ecosystem around digital wallets and establish partnerships with banks and FinTech players that can deliver a wider variety of digital financial services. In turn this ecosystem will generate more data that will enable the creation of better targeted products.
  3. Most of the organizations interviewed are still testing, refining, and experimenting with which datasets are most predictive as well as validating their analytical models. This has  led some FinTech organizations — such as Apollo Agriculture, FarmDrive, and Tala — to become customer facing, at least temporarily. By working directly with customers these FinTechs are able to capture data with which  to train and prove the predictive power of their models. The implication of this is that they have to fund the loans from their own balance sheets; as a result, the amount of capital available for lending limits the volume of data they can collect. Further, even in situations in which customer data has been shared, data analytics organizations have learned that integrating with a provider’s system  requires tremendous time and effort and hampers the ability of FinTechs to scale. Banks and MFIs need to improve readiness as much as FinTechs need more runway to improve models and offerings.
  4. Most banks and FinTechs believe a business case that is strategy- and leadership-led is essential to the uptake of big data and analytics. To expand financial services to low-income or hard to reach customers, banks need to be part of the solution. However, for this to happen, banks will need to shift their perspectives on the breadth of the customers they would like to reach.

The absence of a marketplace — and the pivoting of pioneers who initially paved the way to develop the market — could indicate that it’s too early for big data plays. More likely, however, it demonstrates that a market will never emerge in the same way that it has in the United States. Progress will come gradually, and partnerships among mobile network operators, banks, and FinTechs will be crucial to success. Organizations will need to weigh the value of being a pioneer against the current market challenges outlined above.

As a complement to  the Focus Note, FiDA has developed Profiles of Digital Finance Organizations Leveraging Data and Analytics—brief profiles of how the organizations that participated in the research are using data. The profiles categorize data sources (big data as well as traditional) across four functional categories:

  • Individuals’ financial services use or history.
  • Individuals’ digital interactions using a device.
  • Other individual data, such as psychometric survey responses.
  • Marketwide data, such as crop prices or satellite imagery.

We hope that readers will benefit from the candid details shared by the participants in this study, without whom these findings and knowledge outputs would be impossible.

Synthesizing impact evidence for digital finance—our methodology



The Digital Finance Evidence Gap Map (EGM) Methodology Paper is a companion to the interactive EGM. The EGM summarises the evidence of the effects of digital finance products on various clients, their households, and their communities.

Systematic reviews can take several forms. However the use of logical and transparent methods to identify and assess studies is a universal feature. Through the rigorous review of literature focused on aggregating evidence on the impact question, these reviews become a one stop shop for digital finance researchers, practitioner, and enthusiasts.

Before delving into the impact evidence outlined inn the EGM, keen readers may want to take a closer look at the methodology we used to review and select digital finance impact studies.

The EGM Methodology paper will walk through the development of our inclusion criteria and coding framework. While we highlight the importance of experimental research, we also emphasize the value that mixed methodologies can bring to a sector in which evidence is sparse.

If you have any thoughts or feedback on the methodology, please email ideas@financedigitalafrica.org

Untangling the impact evidence for digital finance products



The Partnership for Finance in a Digital Africa (FiDA) are thrilled to introduce the Digital Finance Evidence Gap Map (EGM)  and the Digital Finance EGM Analysis: Paving the Impact Pathway report, which we believe fill a critical gap in knowledge about the impact of digital financial products on resource-constrained clients.

Why we developed these resources

The digital finance community relies heavily on the impact evidence of traditional financial services and products, and indeed many studies have explored the effect of traditional finance products on clients. From these studies, the digital finance community understand that the benefits depend on the product, its design, the delivery channel, and the demographics of those using it. Despite this growing evidence base, less systematic attention has been paid to how the digitization of these products may vary or enhance the impact. FiDA’s impact mapping exercise scanned and assessed the state of knowledge of digital finance products beyond those accessible through analog channels.

An interactive Evidence Gap Map

FiDA’s Evidence Gap Map (EGM), summaries the impact evidence of diverse digital finance products on several client outcomes.  Its purpose is to present what products were studied, how they were designed and delivered, and the positive, negative or null evidence uncovered. Some takeaways from the EGM:

  • While 21 countries are represented in the EGM, sub-Saharan Africa dominates the literature with 65% of the studies. Within sub-Saharan Africa, Kenya accounts for 35% of the impact research.
  • Payments and transfer products are the most studied digital finance category, accounting for 54% of impact research. There are just seven studies on savings and one each on credit and insurance.
  • 26% of client outcomes tested focused on the adoption of a digital finance product. This was followed by effects on savings (15%) and income (13%). However, digital credit, savings, and insurance products have significant evidence gaps on outcomes beyond product adoption.
  • Overall, 78%  of the outcomes have come in as positive, 10% as negative, and 12% had no effect.

A deeper look into the impact research

While the EGM is an excellent step toward mapping the evidence landscape, gap maps alone can not determine the circumstances under which a product was, or was not successful. Therefore, to accompany the release of the first digital finance EGM, we undertook an in-depth review of the impact evidence for each digital finance product. FiDA’s report, “Digital Finance EGM Analysis: Paving the Impact Pathway” presents a synthesis of the findings from the impact studies in the EGM. Under each product, there is an outline of relevant impact studies, an analysis and summary of evidence by client outcomes. Below are a few examples of the numerous insights from the EGM analysis report:

Payments and transfers

  • Research supports that digital payments and transfers can improve investment in assets, welfare and income gains through fewer leakages, direct income, or informal loans remitted.
  • Business to person (B2P) and donor to person (D2P) digital transfers may be cost-effective but there is narrow evidence to suggest broader uptake beyond the receipt of salary or cash transfers.
  • There is limited evidence that digital payments and transfers improve savings behaviors.
  • In markets where digital payments and transfers are new concepts or uptake is low, client training and handholding may improve uptake.

Savings

  • Two-way SMS has the potential to improve savings behavior.
  • Digital savings products designed with minimal frills have resulted in successful adoption.
  • Integrating digital savings products with existing services has positive adoption effects.

Credit

  • A digital credit product which used a mobile money channel for loan repayments, used local peer educators to "handhold" new female customers. This resulted in a higher uptake of the mobile channel.

Insurance

  • A provider demonstrated the benefits of a freemium model and low fee add-ons by offering clients the option to double their free insurance coverage by paying a low fee monthly fee deducted from their mobile money account. This  convinced previously uninsured clients to opt in.

Mobile banking

  • Improving female adoption of mobile banking could be achieved through female targeted training.
  • Gamification could lead to an increase in mobile banking transactions.
  • As many financial services for low-income and rural populations are delivered in a group setting, digitization may disrupt the existing social architecture, leaving its overall effect uncertain.

This level of analysis, highlighted in the EGM analysis report, will enable the digital finance community to be strategic in our approach to product design and for commissioning and conducting needed research.

If something in the digital finance EGM has piqued your interest and you wish to learn more about the context of the tested products, the distinguishing features of product design and delivery channels, the quantified and/or qualified findings of the products per outcome and what the implications of the findings are, then Digital Finance EGM Analysis: Paving the Impact Pathway is the report to read.

Exploring the use of digital financial services in daily life



Snapshot 3: “How do clients use digital finance in daily life and daily practice?” is one of 16 learning themes designed to address a range of topics within the digital finance space. The FiDA Partnership synthesizes and disseminates the digital finance community’s knowledge of each of these learning themes as “Snapshots” that cover topics at the client, institution, ecosystem, and impact levels. The Snapshots give a current view of “What We (in the digital finance community) Know” about the topic in question, highlight “Notable New Learning” and call attention to “Implications” for future research and investment.

When it comes to the adoption of digital finance, the data says it all. In 2017, there were 690 million registered mobile money accounts globally, and  sub-Saharan Africa accounted for almost half of these registered mobile money accounts (GSMA). While access challenges persist, the industry is doing better and better at getting digital financial services into the hands of low-income, underserved individuals.

However, researchers know less about what individuals do with digital financial services once they have adopted them. The available data indicates that the most popular services are  remote payment and transfer services, which are  typically used on a monthly basis. This  data unfortunately reveals little about exactly why clients use (or don’t use) specific digital finance products. This knowledge gap impedes the digital finance community’s ability to drive “effective use” of these services and ultimately  hampers  meaningful financial inclusion. As discussed in FiDA’s Learning Advances in Digital Finance 2017, Meaningful financial inclusion is not achieved simply through 'access to' or 'the ability to use' these services. It is achieved through the effective use of these services.

Key findings

To drive “effective use,” the digital finance community needs to understand not only the breadth and frequency of use, but also, and perhaps more importantly, the rituals of digital finance use and the motivations to use (or not use) a given digital financial service. For example, why did one provider see customers cashing-in at one location and cashing-out at another location 8 km away the next day? Why do customers save through bundled digital savings and credit services? Are they saving towards a fixed goal, or are they just trying to increase their potential loan size limits?  Unpacking the nuances of use brings to light deeper insights around how the digital finance community can better drive regular, effective use of the digital financial services on offer.

Snapshot 3 reviews current research on the breadth of use, frequency of use, and rituals of use. As noted above, breadth of use is generally limited to a few payment and transfer services and frequency of use tends to be monthly rather than daily. To date there is limited research around the rituals of digital finance use. Delving into rituals of use suggests that individuals repurpose digital financial services to fulfill their own needs, that clients use  single products to fulfill a variety of needs, and that users sometimes adapt digital financial services for unproductive, ineffective, and risky purposes.

While this Snapshot only  introduces the rituals of digital finance use, we hope that it will motivate and guide deeper research.   Access and adoption, while a crucial step towards financial inclusion, is only the first  of many. Arguably, ensuring that the services on offer are used, and used effectively, is a bigger challenge still.

Read Snapshot 3 for more details on the key findings and a list of the top-10 reads in the space this year.

Does digital finance really address low-income customers’ needs?



Last month, we made our first foray into sharing, collaborating and cross promoting with the wider ecosystem as Next Billion published a piece we wrote on on whether digital finance is really addressing the needs of low-income customers.

The numbers don’t lie: Digital finance has gained remarkable traction globally, with over 170 million active mobile money accounts in more than 90 countries. And this has translated to noticeable changes on the ground. Strolling through the markets of Kenya or Pakistan, one often hears “M-Pesa me,” or “Easypaisa kara lo! (Send me Easypaisa),” illustrating the success of digitizing person-to-person (P2P) money transfer services. Yet over the past 10 years, the digital finance community has endeavored unsuccessfully to design products, beyond money transfer and payments, that are relevant to the needs of low-income customers. As a result, usage is still infrequent.

The blog post, draws on our recent review of research in the space, and highlights some of the successes and struggles in digital commercial offerings over the past decade. We discuss how the advent of data, generated through mobile phones, is steadily helping providers build products around their customers’ behaviors, exemplified by Pay As You Go (PAYG) energy providers in East Africa. These tailored, niche products have the potential to reduce the gap between adoption and usage of digital finance products and thus meet the financial needs of low-income customers.

We are excited about the future of digital finance. We invite you to join the conversation, and to read the full article here.

The incessant struggle: incentivizing customers to keep value digital



Snapshot 6: “How can users begin to keep value digital, longer?” is one of 16 learning themes designed to address a range of topics within the digital finance space. The FiDA Partnership synthesizes and disseminates the digital finance community’s knowledge of each of these learning themes as “Snapshots” that cover topics at the client, institution, ecosystem, and impact levels. The Snapshots give a current view of “What We (in the digital finance community) Know” about the topic in question, highlight “Notable New Learning” and call attention to “Implications” for future research and investment.

A recent catastrophic mudslide in Sierra Leone highlighted the potentially life changing role that saving or storing money digitally can have on the lives of underserved individuals. The landslide in Freetown on August 14, 2017, impacted a population of nearly 92,000. A small survey found that only 7% of affected individuals had formal savings; the rest saved at home under their mattresses, in cupboards, and behind books. As a result, those without formal savings  lost everything in the disaster.

Incentivizing low-income individuals to store or save money digitally is an important and enduring challenge. Beyond the benefits of catastrophe-proof savings, the financial inclusion benefits are far reaching — from enabling individuals to better manage their resources and smooth financial shocks, to unlocking merchant payments and putting people in a position in which they can pay for daily expenses electronically.

And yet, more than a decade since the launch of the first digital finance service, the majority of accounts are empty or hold relatively small balances and dedicated digital saving accounts are still secondary products in terms of popularity. Snapshot 6 explores in depth the ongoing struggle to keep value digital, as well as what incentives may help drive improved digital savings and storing behavior.

Key findings

Both digital finance customers and providers face a number of challenges  in keeping value in the digital ecosystem. These range from providers encouraging (or requiring) clients to cash-out their money immediately to demonstrate their need for a social payout, to the lack of interconnected digital financial services and use cases driving the need for physical cash on a daily basis. Trust and information gaps, psychological barriers to saving, and ill-designed savings services are also potential barriers to saving.

In terms of incentivizing money to be kept digital, providers can introduce automatic contributions to savings products that mimic the “friction and flow” of many informal financial management strategies. Read Snapshot 6 to better understand why clients aren’t saving and storing digitally at the rates the digital finance community had hoped,learn more about what the digital finance community can do to improve digital finance behavior in this area, and to find the top 10 reads on this topic, this year.

Is big data a big deal?



Snapshot 9: “Best Practices in Big Data Analytics” is one of 16 learning themes designed to address a range of topics within the digital finance space. The FiDA Partnership synthesizes, and disseminates the digital finance community’s knowledge of each of these learning themes as “Snapshots” that cover client, institution, ecosystem, and impact level topics. The Snapshots give a current view of “What We (in the digital finance community) Know” about the topic in question, highlight “Notable New Learning” and call attention to “Implications” for future research and investment.

Big data is a big buzzword in the digital finance community. In Snapshot 9, the FiDA Partnership explores this buzz and the potential of big data analytics in digital finance. The research indicates that as more people weave digital technology into their lives, digital finance providers can use the data generated from these digital interactions (i.e., big data) to create tailored products that better address customers’ financial needs and draw in new customers previously excluded from formal financial services.

Key findings

The key to success in providing digital financial services is granular level data on customers that explain their needs. Big data has the potential to provide this granularity. According to the IFC Handbook on Data Analytics and Digital Financial Services, big data generally has five characteristics — veracity, velocity, volume, variety, and complexity. In the world’s six biggest emerging economies — China, Brazil, India, Mexico, Indonesia, and Turkey — big data has “the potential to help between 325 million and 580 million people gain access to formal credit for the first time.”

Although big data has gained traction in developed economies, research suggests that digital finance providers in low-income countries lag behind their counterparts in systematically collecting and analyzing customer data. In fact, the GSMA’s “State of the Industry 2015” report found that just a little over one-third (39%) of mobile money providers tracked the gender of customers and only 40% of mobile money providers knew the urban/rural split of their user base. Even these simple metrics can provide valuable insights for providers that want to increase their user base or encourage active use among existing customers.

Indeed, Accion Global Advisory Solutions’ interviews with industry experts and practitioners found that large datasets may not be a first-order concern for many financial service providers working with low-income populations. Rather, many organizations’ most immediate challenge is learning how to leverage small data. Moreover, big data is only meaningful if it is mined and analyzed to produce deep insights about customers. This is not a trivial task. Typically, digital finance providers lack the expertise and capacity to fully leverage the potential of big data. And it is likely a bigger task still to convince senior management that using big data analytics to generate a nuanced understanding of low-income customers can have significant bottom line benefits. Snapshot 9 outlines the steps s digital finance providers can take and the resources they need to cultivate in order to embark on their data journey.

More recently, the FiDA Partnership conducted interviews with thirty Kenyan and Tanzanian organizations — including mobile network operators (MNOs), FinTechs, microfinance institutions, and banks — and found that big data analytics has not taken off in sub-Saharan Africa. This is unsurprising given the challenges organizations face. Similarly, we found that these providers do not exchange and profit from big data directly, rather they have focused on developing relationships on a case-by-case basis to provide analytics of traditional or big datasets. FiDA’s upcoming Focus Note on this research, “Big Data and Analytics: Is East Africa There Yet?,” will discuss the four factors that the organizations interviewed believe are constraining the rapid growth of big data analytics in sub-Saharan Africa.

Nevertheless, there are companies in sub-Saharan Africa that are leveraging big data analytics to offer sophisticated products to their clients, such as by analyzing mobile phone usage and behavior data to grant small amounts of credit to customers via a mobile wallet or airtime account. M-Shwari, a combined savings and loan product, was one of the first to experiment with this model in 2013. More recently in December 2017, M-Shwari announced that they will segment customers who repay their loans on time and have positive savings behavior. M-Shwari will offer loans at cheaper rates to “good” customers and offer a rebate fee for customers who repay on time. They also plan to explore whether these offers encourage people to “behave” better in terms of their repayments and whether new customers will be inclined to use the service. Moreover, big data analytics is now being employed in sectors adjacent to financial inclusion such as M-Kopa, a pay-as-you-go (PAYG) solar energy provider. M-Kopa uses data to design and tailor their services from developing a price point to, more recently, extending a credit product to their customers.

While the big data and analytics space is still new and evolving, Snapshot 9 provides initial guidance to digital finance providers that are thinking about utilizing big data analytics and considering how best to navigate this path. Read Snapshot 9 to learn about the internal capacity and skills needed to pursue big data, see examples from organizations that have integrated big data analytics with their product development, and to find the top-10 reads in this space.