Digital banking: a game changer in microcredit services?
A case study of M-Shwari and Nubank’s digital loan services in Kenya and Brazil
Introduction
When it launched its digital personal loan service in 2019, Nubank was once again largely praised by its Brazilian customers and by the Fintech enthusiasts worldwide. The only 8-year-old and yet largest Fintech company in Latin America has repeatedly launched innovant services such as a fee-free international credit card, a reward system to convert the money spent into points and then into discounts, or an extremely well-designed user interface for their mobile application. In less than a decade, Nubank convinced more than 30 million Brazilians (14% of the total population) with their combination of state-of-the-art, polished services and competitively cheap fares. Its new micro-lending service is yet another instance of Nubank’s successful innovations. Indeed, it offers loans with cheap interest rates that customers can take out directly on their mobile phone, without any human interaction.
If that service is new in Brazil, it has been used for nearly a decade in Kenya, often considered as the pioneer country for digital loan services. In 2007, the Vodafone Group and Safaricom, two telecommunication companies, partnered to launch the mobile phone-based money transfer service M-Pesa, and in 2012 they developed a digital micro-credit service named M-Shwari in collaboration with the Commercial Bank of Africa (CBA), a private bank. M-Pesa’s digital loan service can rightly be considered as a revolution. Indeed, the company opened access to financial services, and in this case to credits, to millions of citizens barred from doing so through the conventional banks.
Financial inclusion can be defined as the “access to a full suite of financial services, provided with quality, for everyone who can use financial services, thereby leading to an increase financial capability” (UN DESA, 2021). Such financial services include access to a bank account, to insurance products, or to a credit. The United Nations Department of Economic and Social Affairs notes:
“2.5 billion — more than half of the world’s working adults- are excluded from financial services. This is most acute among low-income populations in emerging and developing economies, where approximately 80% of poor people are excluded. Access to financial and social assets is a key contributing factor to help youth make their own economic decisions and escape poverty. Providing young people with financial services — whether a safe place to save or an appropriately structured loan for investment in an enterprise or education can promote entrepreneurship and asset building, and emphasize sustainable livelihoods. The financial component is especially effective for youth when complemented with training in entrepreneurship and financial literacy, and mentorship opportunities” (UN DESA, 2021).
As expressed by the UN, loans can represent an important tool of financial inclusion, contributing to empower people economically, help them escape poverty and allow them to invest in their future. There is also evidence that financial inclusion creates in its turn “more stable financial systems and economies, mobilizing domestic resources through national savings and helping to boost government revenue” (UNCDF, 2021). Banking services are thus essential elements for resilient and strong economies.
Digital lending, which is discussed in this report, is a new feature that makes loans easier to access for millions of people. If this boom in financial inclusion arguably contributed to individual empowerment and overall economic growth in Kenya and Brazil, it also brought in new threats and challenges, as discussed in this report. For the sake of brevity, we focus here on two precise digital micro-credit services. The broader discussions on micro-credits and on digital finance services are only mentioned when relevant to the topic. Besides, there exists different forms of loans, such as peer-to-peer lending, different companies developing similar services and many other interesting cases in other countries that could have been studied. This report focuses on bank to customer lending through M-Pesa and Nubank’s digital services in Kenya and Brazil as they are major examples in this domain, in two countries with quite different characteristics, which allows an interesting comparative analysis.
This report thus aims to analyze how the digital micro-credit services developed by Safaricom and the CBA in Kenya and Nubank in Brazil are revolutionizing the financial inclusion in these countries while raising new challenges that remain to be addressed. The first part aims to explain what is digital lending and discuss its impact on the financial industry. The second part dives into two case studies in order to draw comparisons on the implementation and effects of those services in Kenya and Brazil. Finally, the third part analyzes how those new services are actually addressing some of the recurrent issues of microcredit services, while also generating new ones.
I. A review of digital lending
A. Definitions
Digital financial services, or DFS, are “financial services which rely on digital technologies for their delivery and use by consumers” (Pazarbasioglu, 2020, 1). In a Coursera video, Prof. Jonas Hedman (2017) gives a good overview of the history of DFS. The digitalization of finance has been ongoing since the 1960s with the financial sector getting equipped in computers and starting offering digital bank accounts. Then in the 1970s came the automated teller machines or ATMs linked to those accounts that allowed people to withdraw, deposit or transfer money directly through a digital interface and without human interaction. This decade also saw the beginning of electronic trading. The next milestone in digital finance was the creation of the SWIFT network that established standards for global transactions. With the rise of the internet in the 1990s emerged internet banking that includes access to one’s bank account from their computer as well as online payments on websites. The most recent evolution of digital finance is mobile payments. Led initially by mobile operators, what started as the possibility to download ringtones by SMS has recently been invested by the Fintechs to offer a wide variety of services.
Mobile banking really emerged at the turn of the millennium with SMS banking and the mobile web services. With the development of smartphones in the years 2010s, mobile banking applications were developed (CFI, 2021). With their user-oriented clean interface, they offer more and more possibilities in terms of services that were previously reserved to physical banks or computer banking, and attract more and more users around the world, with Sub-Saharan Africa currently leading the way. A 2017 World Bank report on financial inclusion and the Fintech revolution noted:
“The power of financial technology to expand access to and use of accounts is demonstrated most persuasively in Sub-Saharan Africa, where 21 percent of adults now have a mobile money account — nearly twice the share in 2014 and easily the highest of any region in the world” (Demirgüç-Kunt et al, 2017, v).
Mobile banking is thus not merely a new technology for traders or for the economically developed countries. It also has an impact on financial inclusion in the least developed countries.
Digital lending can be defined as “the process of offering loans that are applied for, disbursed, and managed through digital channels, in which lenders use digitized data to inform credit decisions and build intelligent customer engagement” (Stewart et al, 2018, 9). It is not per say a mobile banking service as it can sometimes be performed on computers or other digital channels, but it is de facto usually manageable through mobile applications and often provided by mobile network operators (MNOs) partnering with financial service providers (FSPs).
Chen and Mazer (2016) “differentiate digital credit from conventional loans by identifying three key characteristics: digital credit is instant, automated, and remote.” Those three factors are crucial to understand the advantages of digital lending, which are the rapidity of the service, the relatively cheap fees and the facilitated access thanks to digitalization.
B. How does digital lending work?
The Kenyan MNO Safaricom has been offering loans for nearly ten years in the digital banking platform M-Pesa. On its website, it gives a brief explanation on how to get a loan:
“How does it work?
Access the M-PESA menu.
Select Loans and Savings.
Select M-Shwari.
Select Loan.
Request Loan.
Enter amount.
Enter your M-PESA PIN
Loan amount will be sent to your M-PESA Account. The loan amount to be paid will be in inclusive of the facility fee.”
On the user side, borrowing money via the M-Pesa application is thus fairly easy and does not require any additional document upload to explain the purpose of the loan or to prove the capacity to repay it. The loan amount has to be between KSh100 and KSh50.000 (roughly 1€ to 400€) and the interest rate is 7.5% (Konvigilante, 2021).
The Brazilian digital bank Nubank launched in 2019 its “empréstimo pessoal” (personal loan) service. However, it is not yet open to all its customers. For those who can access it, the process on Nubank’s application is quite similar to the one on M-Pesa. Clients can run a simulation by indicating the reason why they want to borrow money, the value they want to request, the number of installments, and the date to begin paying back and can then proceed in asking for the loan upon seeing the result of the simulation. They are then shown the very short terms of the contract (4 paragraphs) and after scrolling down on it they can request the loan (Nubank, 2021). The credit amount starts from 30 reais (4.50€) and the maximum depends on the banking history of each customer, so does the interest rate that ranges from 2.1 to 5% (Coimbra, 2019). Such a rate is quite low compared to the ones of conventional banks.
If the process to contract a loan is similar, the repayment method varies greatly between the two services. M-Shwari loans are relatively little loans that can be repaid in one time. Customers have 30 days after borrowing the money to pay it back, or they are charged another 7.5% interest fee. They can choose to repay the loan exactly 30 days after, or anytime beforehand, and can then borrow money again (Konvigilante, 2021). Nubank’s microloans are usually bigger and meant to be paid through instalments over up to 2 years. Besides, the borrower can start repaying for the loan three months after it contracted it. Unlike M-Shwari’s customers, Nubank’s ones are automatically withdrawn every month the installment amount, unless they do not have enough money in their account, in which case they are charged an additional fee. To prevent that, Nubank informs the clients prior to the repayment day via notifications on their mobile (Nubank, 2021).
Both companies thus use the carrot and the stick to ensure their customers pay back their loans, offering them the access to a new credit and reminding them to repay on time, while also threatening them with extra fees in case they fail to do so. The repayment mechanism, voluntary for M-Shwari, automatic for Nubank, is however a major difference as it induces a different engagement between the customer and the bank.
C. The impact of digital lending
Digital credit first appeared in Kenya in November 2012. It was created “through a partnership between Commercial Bank of Africa (CBA) and Safaricom” who jointly launched M-Shwari, a service providing access to digital loans on the M-Pesa platform of mobile banking (Kaffenberger et al, 2018, 5). Nowadays, digital lending is available in most countries in the world and the market value of such financial service is increasing exponentially.
Analysts agree nowadays to call digital lending a revolution that “will have a permanent impact on the financial industry” (Ibid, 5). The alternative finance industry from which digital lending is part of has grown by 264% in just a year between 2014 and 2015 (Ibid, 6). Besides its growing economic value, digital lending represents an important tool for social inclusion. Indeed, it opens an access to capital to a population usually excluded from conventional loans. Stewart et al (2018, 15) note :
“Digital lending can be a powerful force for financial inclusion. Innovations in digital lending are enabling financial service providers (FSPs) to offer better products to more underserved clients in faster, more cost-efficient, and engaging ways. Governments are increasingly incentivizing the growth of digital lending models as a way to promote greater financial inclusion and extend high-quality financial services to underserved communities and businesses.”
The researchers from Accion, an international nonprofit organization focused on microfinance and fintech impact investing, have an overall very positive vision of the impact of digital lending. However, the novelty of the service does not allow enough distance to fully assess the benefits and issues that it induces. The next section develops two case studies whose comparison sheds some light on the differences between those digital lending services in Kenya and Brazil.
II. Comparative case studies of the deployment of digital lending services in Kenya and Brazil
A. Financial inclusion in Kenya and Brazil
Kenya and Brazil hardly share commonalities socio-economically. Brazil’s population is 4 times the one of Kenya (211 million against 53), its fairly high HDI of 0.765 puts it at the top of developing countries, while Kenya ranks rather in the middle with a HDI of 0.601. Its GNI is three times the one of Kenya and it is considered as an emerging economy along with the other BRICS while Kenya is sometimes called a frontier market, in-between emerging markets and least-developed ones. One can thus say that apart from being two developing countries, Brazil and Kenya are at different stages of economic development. Geographically, Brazil is 15 times bigger than Kenya, on a different continent and facing a different ocean.
Details of Brazil and Kenya’s HDI in 2020 (UNDP, 2021).
Interestingly enough, there are more people with a bank account in Kenya than in Brazil, as the table below illustrates (World Bank, 2021). Moreover, the rate of respondents reporting having an account doubled in Kenya in only 6 years, while it increased by 25% in Brazil throughout the same period.
Percentage of respondents with an account in Brazil and Kenya (World Bank, 2021).
Besides, the rate of people borrowing money in Kenya is superior to Brazil’s by 24.4 points, although it is in sharp decline in Kenya while it remains stable in Brazil. Those two indicators suggest that financial inclusion might be stronger in Kenya than Brazil, despite the former being a less economically developed country than the latter. This statement would require a qualitative analysis of the quality of this access that is beyond the scope of this study. It is certain however that M-Pesa has played an essential role for financial inclusion in Kenya, as explained in the next part.
Percentage of respondents who have borrowed money in the past year in Kenya and Brazil (World Bank, 2021).
B. A review of Safaricom and Nubank’s digital banking services
Safaricom is a mobile network operator formed in 1997 and partially managed by the British multinational telecommunication company Vodafone since 2000. In 2007, it launched M-PESA, a mobile phone-based money transfer service. In its forteen years of service, M-Pesa has revolutionized the banking industry in Kenya by offering convenient, secure and low-priced banking services via a mobile application. M-Pesa was initially funded by public funds from the United Kingdom in an effort to encourage private sector innovations to improve financial inclusion in developing countries. Since its start, M-Pesa is thus a product of international development, which explains the pro-poor approach of the service.
In 2012, Safaricom partnered with the Commercial Bank of Africa to offer supplementary banking products targeted to poor people. The UNCDF (2021) notes:
“A long-term impact study on a mobile money service in Kenya, M-PESA, found mobile money has lifted as many as 194,000 households — 2% of the Kenyan population — out of poverty, and has been effective in improving the economic lives of poor women and of members of female-headed households.”
Safaricom is thus a major actor of financial inclusion in Kenya. Thanks to M-PESA, “76.7% of the population are within 5km of a financial access touch point and there are 161.9 financial access touch points per 100,000 Kenyans compared to 63.1 for Uganda, 48.9 for Tanzania and 11.4 for Nigeria” (Ndung’u, 2018, 39). Among the 52 million Kenyans, there are about 21 million (40% of the total population) subscribers to M-PESA services in 2017 (Donkin, 2017).
M-Pesa and Nubank’s logos
The company Nubank in Brazil rose in 8 years to become the largest fintech company in Latin America. Fábio Sirota and Gustavo Fratini (2019, 48) attribute Nubank’s success to two factors : “traditional banking concept disruption and user-friendly approach.” Recent sources estimate that 34 million Brazilians (16% of the total population) had an ‘NuConta’ bank account in early 2021, a number that tripled since the beginning of the COVID-19 pandemic at the end of 2019. The fact it can be all managed online, the free subscription and a strong mouth-to-mouth dynamic has boosted the company’s popularity in the past year. Nubank is targeting a young audience: 70% of their customers are aged below 36 (Nubank, 2021 (2), its average customer being urban students or young workers, earning 1 to 3 minimum wages, motivated by the cheap rates and convenience of the bank (Souto Soares, 2018). It has established itself as the bank for the millenials and its entrance in the Brazilian banking market fueled a new competition with conventional banks like Banco do Brasil, Itau and Santander, pushing them to fasten their digitalization in order to keep their clients and attract new ones (Sirota & Fratini, 2019, 52). Unlike M-Pesa, Nubank’s funding and investors are mostly American venture capital firms and investment banks such as Sequoia Capital and Goldman Sachs. The company might contribute to financial inclusion in Brazil, but it has not presented it as a major goal nor launched services targeting this particular customer base.
Safaricom and Nubank are thus quite different in their approach on financial inclusion through mobile banking. While Safaricom has been targeting people excluded from the banking institutions, Nubank has rather been competing with conventional banks to offer services that would attract the youth. Yet, both companies launched similar banking services using innovation, technologies and well-thought user experience (UX) design. As a result, they both lead the mobile banking markets in Kenya and Brazil, respectively. At last, they are also both the pioneers in their country for digital lending services.
C. M-Shwari customer’s profile: who takes a digital loan and why?
No studies have been done regarding the customer’s profile of Nubank’s loan service since it was created only in 2019 and is still not available to all customers. One can note however that the objectives list from which to choose when contracting the loan are: “household bills, reform or repair, investment in my business, travel, debt, medical bills, education, shopping and other”. While there is no information regarding which objective is the most selected or effectively pursued by the borrowers, this list gives an idea about what the loans were thought for.
Digital loans in Kenya are more documented. Researchers from the Kenyan Bank Association (KBA) have indeed conducted an in-depth research on the users of M-Shwari, Safaricom’s digital lending service available on the M-Pesa platform since 2007.
The study found that the average customer tends to be a male (55% of the digital borrowers while they represent 49% of the adult population), living in an urban area (55% of the digital borrowers while they represent 36% of the adult population) and aged between 26 and 35 (41% of the digital borrowers while they represent 28% of the adult population). But the most striking figure is the level of education. Indeed, 72% of digital borrowers report having completed at least secondary schooling while this represents merely 41% of the adult population of Kenya (Wamalwa et al, 2019, 24). This number means adversely that the 59% of the Kenyans who have not completed secondary education only account for 28% of the M-Shwari users. As basic education completion and wealth are proven to be correlated, one can infer that most Kenyans from the lower social classes (with the lower incomes) do not use M-Shwari loans. This figure calls into question the objective of Safaricom and the CBA to use M-Shwari to get people out of the poverty trap.
The graph below, produced by the KBA, exposes the main reasons reported by the customers for taking a digital credit and is disaggregated by gender.
Reasons for Taking Digital Credit by Gender (%) (Wamalwa et al, 2019, 12).
In Kenya, the main reasons for taking a digital loan are thus business, then day-to-day needs (especially for men) and education (especially for women). The gender divide on digital loan is further analysed (Ibid, 22), with results showing that men tended to contract more digital loans while women turned more often to conventional ones. The average customer of M-Shwari is thus a young urban male adult with a high school degree.
The non-profit, UK-funded and Nairobi-based company FSD (Financial Sector Deepening) Kenya (2016, 4) notes:
“The poverty profile of users of M-Shwari appears to be following a similar trajectory to that of M-Pesa: early adopters are significantly more likely to be urban, above the poverty line and already banked. According to one key informant “M-Shwari is not exclusive of the poor. Rather, it has been taken up more quickly by the less poor”. In 2013, only 19% of M-Shwari users were below the national poverty line; this had increased to 30% by the end of 2014. It can be expected that the proportion of poorer users will grow over time, as usage amongst higher income groups approaches saturation.”
FSD Kenya’s analysis highlights that M-Shwari was first appropriated by customers who already had a bank account, lived in cities and line above the poverty line before attracting poorer people in a second stage. The original customers’ profile is reminiscent of Nubank’s target audience. Further deployment of the latter’s services will show if this pattern of digital lending service two-stage adoption will repeat in Brazil as it did in Kenya. If that is the case, Nubank could become a major actor of financial inclusion. However, the CBA and Safaricom seem more engaged than Nubank in understanding pro-poor clients, designing products that fit their particular needs and giving them access to a bank account and loans.
Despite the similarity of the two mobile applications, Nubank and Safaricom’s digital lending services are quite different. Implemented in countries with distinct socio-economic characteristics, the objectives and targeted customers of the two companies are contrasting. On one side, Safaricom indeed takes on a pro-poor approach, offering nano-loans that are to be repaid in a month. Nonetheless, an analysis of M-Shwari’s customer base has demonstrated that it has been used first and is also being used by the urban non-poor youth. Nubank rather presents itself as a competitor to traditional brazilian banks and offers digital micro-loans targeting Brazil’s urban youth. Digital loans thus seem to appeal to the same audience, before being possibly adopted by the poorest. If studies shows that in Kenya this pro-poor approach with digital lending has contributed in reducing financial exclusion and improving overall economic development, this new service also brings up old and new issues which are raised in the following section.
III. A critical analysis of digital lending
A. The double-edged sword of broadening access to credit
In their report titled “Digital Credit, Financial Literacy and Household Indebtedness”, the Kenya Bankers Association (Wamalwa et al, 2019, 2–3) note the demonstrated positive impact of digital lending:
“The use of digital channels to provide loans has reduced transaction and information costs associated with lending, thereby driving demand and expanding the supply of credit. Financial institutions can leverage this technology to more efficiently screen for default risks, and households can more easily and affordably borrow (Gross & Souleles, 2001; Narajabad, 2012; Livshits, Sanchez, 2012). Access to digital credit, enables households and firms to invest in human and physical capital and shift to higher-skilled, high earning occupations (See, for example, Galor and Zeira, 1993; Banerjee and Newman, 1993; Lloyd-Ellis and Bernhardt, 2000, Jack and Sur, 2014). This not only increases income and wealth at the household and national levels but also reduce [sic] wealth inequality.”
Digital lending is making loans available quicker, at cheaper rates and in safer manners than conventional ones. In that sense, it is very competitive compared to other forms of loans and effectively opens the service to poorer customers otherwise excluded. However, this service is not exempt from drawbacks, the most pressing issue being overindebtedness that can be defined as “a household’s persistent and ongoing difficulties meeting financial commitments” (European Commission, 2008). Just after mentioning some of the positive impact cited above, the searchers from the KBA (Wamalwa et al, 2019, 4) then report on the negative impact of digital microcredits:
“The results also show that using digital credit reduces income and increases the probability of selling household assets to repay a loan. Digital credit users are more likely to have more loans than conventional credit users. Therefore, using digital credit reduces household income as it does not bridge the financing gap to enable households to undertake investments that generate sufficient income to repay household debt. This exacerbates household indebtedness and reduces welfare as a result of selling household assets to repay the loan and a reduction in income.”
There is no unique narrative that can be drawn on digital microcredits’ efficiency to take people out of the poverty trap. Depending on the interest rate and maturity of the loan, on the sanctions in case of late repayment, on financial education and measurements of repayment capacity of the borrower and many other factors that include hazardous events, microloans can either contribute to increase “income and wealth at the household and national levels” or to exacerbate “household indebtedness and reduc[e] welfare”.
While each of these factors need close examination, let us focus on this report in one in particular: repayment (in)ability. In Kenya and even more in Tanzania, late repayments and payment defaults are very frequent, especially among the poorer share of the population. For example, a third of Tanzanian digital borrowers have defaulted and more than half have repaid a loan late (Pazarbasioglu et al, 2020, 27). Digital lenders tend to conduct limited or no evaluation on capacity to repay and have limited understanding of their customers, which allows them to distribute loans instantly, but also increases the risks (Stewart, 2018, 16). They give loans based on the customers’ willingness to pay back, rather than their ability to do so.
Such a trend was heavily accentuated with the COVID-19 pandemic. In Kenya, M-Shwari loans doubled with the pandemic, but Kenyans like most peoples around the world have been forced to stay at home and many of them found themselves unable to repay their loans to the CBA and other private banks (Michaelson, 2020). Lacking the ability to work and public financial relief may have pushed millions of Kenyans to turn to digital loans and to contract several ones, leading dangerously towards overindebtedness. Many of those borrowers end up barred from accessing digital services, thus further excluded financially.
B. Information in the digital age
Just as with financial inclusion, the access to information through digital platforms is a disputed topic. Nubank is popular in Brazil for aiming at educating its customers on financial management and for offering them tools to effectively keep track of their spendings and earnings. The conclusion of a 2018 evaluation of Nubank’s contribution to the financial education of its customers also shows positive results, stating that Nubank’s mobile application effectively contributes to the development of habits that help people take informed decisions and better manage their personal finance (De Oliveira Vasconcelos, 2018, 24).
While the customer’s satisfaction rates are quite high in Brazil, in Kenya and Tanzania issues of communication with the digital banks have been raised. According to a survey, about 10% of M-Pesa customers have needed to contact customer care but could not figure out how. More than half of digital borrowers who called customer care in Tanzania report calling for a question or a complaint about the fee or interest rate, about an unexpected change or about their information. Those figures drop to 15% in Kenya where M-Shwari has been implemented a decade earlier, thus suggesting that the issue may partly come from the newness of the service (Kaffenberger et al, 2018, 25–26). As mentioned above, rates of defaulted or late payments are also higher in Tanzania, suggesting that there might be a causational relation between poor access to customer care and repayment issues.
A study in South Africa showed that information asymmetries between borrowers and lenders can induce default payments (Ibid, 16). While offering clean interfaces with simple contracts to their customers, digital lending platforms cannot replace the contact face-to-face with a banker, with the possibility to ask questions and explain in depth the terms of the loan being contracted. Its accessibility may also make personal digital microcredit preferable to other means of informal microfinance such as peer-to-peer lending with relatives or communitarian tontines that strengthen social bonds besides the short-term money input they offer (Guérin, 2015, 145). Kaffenberger et al (2018, 19) note that “[q]ualitative research has suggested that the privacy and lack of human touch with digital loans makes their repayment a lower priority for borrowers, compared to loans from family of community members where borrowers’ local reputations are at stake (Mustafa 2017b)”. Issues of information asymmetries and privacy are thus two challenges that digital banks must address in order to ensure loan repayment.
Besides, the information collected by the digital lenders on the borrowers also raises new issues. There have been cases of defaulters whose names were posted on the lenders website or directly on their social media walls in order to shame them and pressure them into repaying their loans (Stewart, 2018, 16). One can see here a direct continuity with the “economy of shame” as called by Lamia Karim that consists in microfinance NGOs mobilizing local norms of honor to exert some control over the borrowers (Guérin, 2015, 198). Moreover, these cases of digital public shaming might just be the tip of the iceberg in terms of controversial information sharing. With raising concerns of the GAFAM and other tech companies’ use of their customers’ information on one side and of the risks related to cyber-security such as hacking on the other side, digital information owned by banks might be used in many ways at the expense of the borrower.
While some digital lenders contribute to financial transparency and education, in many cases the digitalization of microcredit is accentuating issues such as unawareness of loan conditions, difficulties to discuss with customer care, repayment default or misuse of client information. Each of these issues need to be addressed by the banks but also by the governments and international organizations in order to regulate the market and prevent the rise of predatory financing.
C. The digital divide, a continuity in inequality
One last topic for this critical overview of digital lending is the question of inequality. As previously mentioned, M-Shwari, and M-Pesa services in general, have helped many Kenyans to step out of poverty and to reduce wealth inequality. Bringing in a different perspective on financial inclusion, socio-economist Isabelle Guérin (2015, 31, translation mine) deconstructs the “myth of empowerment through the market”. She argues that microfinance offers technical economic solutions where the issues are (also) calling for broader social, cultural and political institutional policies. More, according to her, microfinance often worsens inequalities between people, including between men and women by further indebting them (Ibid, 217).
The issues raised by Guérin about microfinance seem to have permeated in the digital lending industry. Indeed, studies mentioned in the previous sections have shown that digital loans were not mostly used by poor people, that the latter were sometimes over-indebted because of this new service, or even barred from accessing those services in case of default repayment. 2.7 million people in Kenya have been blacklisted for payment default, sometimes for loans of less than US$2. Defaulters must then pay fines to recover access to financial services (Stewart, 2018, 16). Moreover, World Bank researchers note that “[u]nequal access to infrastructure and technology increases the digital divide. Examples include lack of access to basic telecommunication and financial infrastructures, as well ass [sic] affordable mobile devices and data-plans. Women and the poor are often disproportionately disadvantaged” (Pazarbasioglu et al, 2020, 8). In addition to issues of impoverishment and inequality enhancement, the digital divide thus also further exclude fringes of the population.
Lastly, Bateman et al (2019, 11) adopt a radical perspective on the role of fin-tech companies in perpetuating socio-economic inequalities:
“But the core problem as it stands — as illustrated in Kenya and other places around the world — is that the bulk of this value does not go to the poor. Rather, fin-tech is very clearly designed to hoover up value and deposit it into the hands of a narrow global digital-financial elite that are the main forces behind the fin-tech revolution. Of course, this enormous wealth could be redirected towards Kenya’s poor population and reinvested locally, for example through communityowned financial institutions and financial cooperatives, but there would appear to be little time, sympathy, or political support for building such pro-poor institutions when so much wealth can be appropriated by so few so quickly in another way.”
The researchers cynically turn the problem around in their argumentation, accusing the elite from the global fin-tech industry to be the ones benefiting from the system. They denounce the lack of wealth redistribution from those rich companies to the local population. If their argument was to be further studied and adopted by civil society and political actors, then redistribution schemes could be implemented. Similarly to extractive actors, fin-tech companies could expand their corporate social responsibility in order to fund local communities’ development, so to compensate for the inequalities they generate conducting digital lending businesses in developing countries.
Conclusion
This report has presented digital lending as a major innovation of the financial industry. It started in East Africa in the early 2010s and spread around the world since, particularly in developing countries. Digital microcredits are typically contracted via mobile phones through a simple procedure and available almost instantly. They consist of small sums with varied interest rates that are meant to be repaid within 1 to 24 months. Financial service providers (FSP) motivations can be analyzed as dual. First, there is the developmentalist motive to consolidate a country’s economic development thanks to better financial inclusion rates and a pro-poor empowerment approach. This ideal is central in microfinance since it was developed by Nobel Peace Prize winner Muhammad Yunus, the “banker to the poor”. The second motive is more purely capitalistic and concerns the expansion of the banking industry by utilizing state-of-the art technologies to reach new and old customers alike. Mobile banking and lending services have been adopted by many non-poor customers and are on a sharp increase because of the mobility restrictions imposed by the COVID-19 pandemic.
Those two motivations shone through the comparative analysis of the Kenyan mobile lending service M-Shwari developed by Safaricom and the CBA and of the Brazilian digital bank Nubank’s personal loan service. While Safaricom and the CBA show their determination to improve financial inclusion and receive funds from the British development agencies for doing so, de facto their average customer tends to be educated, urban citizens who probably have access to conventional banks. Adversely, Nubank clearly competes with conventional banks for customers, but their take on financial education and the accessibility of their services might also have an impact on financial inclusion in Brazil. The forms of the loans are quite different between the two, with very small sums in Kenya that the borrower can decide when to repay within a month, while it implies bigger amounts in Brazil to be repaid through automatic installments.
In Kenya, M-Shwari, and more generally the mobile banking service platform M-Pesa, are generally praised for their impact on poverty alleviation of their customers, including women. There is not enough evidence to draw the same conclusions with Nubank’s service, launched only 2 years ago. Nonetheless, researchers and analysts working for NGOs, the Work Bank or in academia are also raising their concerns about the issues generated by digital lending. They raise issues of digital microcredits inducing further indebtedness, notably for under evaluating the customer’s incapacity to repay and for communication issues before and after the loan contraction that induce information asymmetry. They also raise concerns concerning the use and security of the data collected, and concerning the inequality induced by the digitalization of the service, with the people lacking access to mobile technologies largely excluded from the service. Finally, some ponder who is the most benefiting from digital microfinance, between the poor allegedly taken out of the poverty trap and in the financial market, and global fin-tech companies earning much from this new service.
To conclude this report, a few recommendations, mostly inspired by Accion’s report (Stewart, 2018, 42), could be formulated in order to suggest some actions for the digital lending industry and for governments and international organizations to improve the practices and regulations of the sector:
- Offering a “cooling off period” for customers to reconsider whether to keep their loan or not;
- Review fine and overall sanction schemes to prevent the financial exclusion of defaulters;
- Improve evaluation algorithms in order to prevent over-indebtedness. Also review possible biases based on gender, age, handicap and other forms of discrimination;
- Present clear terms and prices and strengthen customer care to prevent information asymmetries between lenders and borrowers;
- Apply reasonable pricing and implement pricing regulations to avoid predatory financing;
- Seek consent and remain transparent on consumer’s data usage, and implement policies on financial data protection;
- Use the digital platform to educate on and offer tools of financial management.
For researchers finally, most remains to be studied regarding the effect of digital lending on poverty and inequality reduction. The speed and scope of digital microfinance development indeed calls for academic scrutiny.
Annex
Trends in Latin America and Africa regarding digital banking services (Stewart et al, 2018, 40).
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I wrote this article for a class on microcredit at the University Paris 1 Panthéon-Sorbonne.
