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A Central Banker Talks Money

“Now we have digital money,” economist Dr. Andrew Mullei, former governor of the Central Bank of Kenya, explained. “This money can be seen. With this technology you can see the fund and how it is developing. You can log on to the computer to see who has contributed.” Dr. Mullei went on to contrast digital money with earlier forms. “Previously we had cash money, which came to us from British colonialism. Cash money can be hidden in the pocket. You do not see it. You do not know where it is. This hidden money brought corruption.” Ironically, the money of colonial modernity had not brought Africans a more rational society, but instead had made possible mistrust, secrecy, and the pursuit of personal gain.

An economist by training, Dr. Mullei had spent a career reimagining money. As Central Bank Governor, he had set up Kenya’s first interbank real-time gross settlement (RTGS) system in 2005, which ushered in the subsequent digital payments revolution.¹ He was well known for his tough stance on corruption and for going after banks involved in money laundering. At the time of our July 2016 interview he was in his seventies, semiretired and advising his son, who was CEO of a crowdfunding software platform, one of many new technology companies in Nairobi’s emerging start-up scene. I had been hired as a consultant to help the company, named M-Changa (kuchanga means “to collect” in Swahili), to design a product as a financial tool for low-income people. Through mobile phones, they could use the M-Changa platform to conduct family and community fund-raisers, a long-standing local practice.

“In the traditional African setting, for example in my [WaKamba] community, our money was goats. You might give one to your nephew . . . you could take a stroll to your brother-in-law’s compound and just pass by and see how the goat is doing. Is my brother-in-law taking good care of [the goat]? Has it reproduced?” Back in the day, Dr. Mullei explained, one of a man’s duties was to maintain ties with his sister and her children after her marriage into her husband’s lineage. A brother-in-law, an uncle, was a bridge across a social divide. Gifts to his nephew allowed a man to demonstrate generosity and continued involvement in his sister’s welfare, and also to assess whether her husband was taking good care of the family. The goat was a gesture of trust, notwithstanding the different patrilines involved.

Dr. Mullei’s story compared three kinds of money. The original money, the goat of his WaKamba community, was circulated through public gift giving. Later during colonialism, cash money replaced the goat. Colonial currency was a source of deceit and corruption because it could be individuated and hidden in pockets or bank accounts. Dr. Mullei explained that now, new forms of digital money could return Africans to their roots in shared money with value that, like the goat, can be seen. “And now with computers we have digital money . . . everyone in the fund can see the fund on their computer. You can trace the performance of each member of the kitty. How is each person contributing? How is the fund performing?” In digital money, Dr. Mullei sees a return to the original sociality of African money, a public and shared currency where visible contributions produce a group fund.

Digital payment technology is rapidly changing the use of money across the globe.² Although mobile payments have been slow to take off in the United States and many other countries, they are rapidly displacing cash in settings as diverse as China, Kenya, and Sweden. The Global South has been a leader in money innovation. Some readers may think of Venmo or PayPal. Actually, M-Pesa achieved popularity several years before Venmo. It does not require a smartphone, bank account, credit card, or Internet connection, but works through a network of human agents where users can cash in and out. In 2007, Kenya became the first country to use the mobile phones as a payment channel on a broad scale when the mobile phone company Safaricom launched the M-Pesa money transfer service to paying customers. Kenyans use M-Pesa to send money to friends and relatives via text messaging and to store money on a phone-based mobile wallet. Marketed as a remittance service for urban migrants under the slogan “Send Money Home,” the M-Pesa mobile money transfer service soon became part of daily life.

For Dr. Mullei, most important properties of money either make money hidden or make money visible. Many others in banking and finance are similarly inspired to consider how money’s material form changes its work in society. Scholars, investors, and everyday money users are following suit. For them, Kenya offers a window into the future of money as reimagined by new communicative and digital technologies. As a laboratory of design and policy innovations, this country is producing new experiments in digital money and digital financial services (DFS), including banking, credit, insurance, crowdfunding, fundraising, peer-to-peer lending, sports betting, e-commerce, government payments to and from citizens, treasury bonds, and paying for utility services such as electricity, water, and solar power. Kenya is a laboratory of innovation³ and one of the few market success stories for mobile money. It is a site for reimagining money within an emerging consumer financial system and based on a mobile payment channel. Over the past ten years these innovations have produced a new commercial space for digital entrepreneurial innovation called the Silicon Savanna.⁴

Swept up by all this innovation, the field of development is getting involved, and embracing the promise of digital finance to reduce poverty—notwithstanding the finance and microfinance crises of the last decade.⁷ As a World Bank economist wrote, “To eradicate poverty, achieve gender equality, provide quality education, or meet any of the United Nation[s’] Sustainable Development Goals (SDGs), we must begin by creating a financially inclusive world.”⁸ Socially minded investors in the West are supporting products for the developing world like digital credit via mobile phone.⁹ Studies purporting to provide evidence that mobile money reduces poverty are widely touted.

On the one hand, claims of financial inclusion and poverty reduction are supported by household economic studies showing that remittances help poor households maintain consumption levels in the face of sudden emergency events—shoring up their resilience—and invest more in farming needs.¹⁰ A widely cited study¹¹ claimed that access to mobile money agents lifted 194,000 households out of poverty and enabled them to drop farming for other income activities like small businesses (why farming is undesirable is unclear). The numbers make an appealing headline. However, the study does not explain why these households held more money. The study measured only proximity to a mobile money agent. The authors suggest an array of possible causes for the households’ increased receipts, such as more wage work or income, money transfers, value storage, use of digital microloans, change in occupation or investment, shifts away from farming, or internal migration—not all of which imply less poverty in either the short term or the long term. Like many studies, this one does not provide enough context, and does not explain the change.

On the other hand, other work is questioning any direct relationship between digital finance and desirable outcomes like poverty reduction and financial inclusion. Although digital payments are proliferating globally, they are not leading to use of formal banking; an analysis of survey data in six countries found that the financial inclusion effort had stalled—accounts often lie empty.¹² Another review found that financial interventions have small and variable effects on income, assets, and health.¹³ Beyond the hype, many are asking deeper questions about digital money as they weigh what is at stake for the poor. The enthusiasm is waning as problems with new money technologies mount and providers fail to glean profit.¹⁴ People in rural areas struggle with poor mobile networks, understanding how to use technology, and the high costs of phones and services.¹⁵ Taxes are allowing governments to extract more value from users. Hacking, fraud, and customer data surveillance and breaches have taken people’s money. Widespread use of digital small loans is miring poor people in debt.¹⁶ All of these problems raise the prospect that new monies will leave the poor, illiterate, digitally invisible, or disabled excluded or even harmed, while fintech innovations, ranging from cryptocurrency investment funds to mobile banking, to low-cost consumer credit, to e-commerce, to data-based products and marketing become the domain of wealthy investors, and consumers and companies. In fact, financial experts and everyday people all over the world have misgivings about a new cashless future and its potential to create barriers, exploit or steal data and personal information, and obscure forms of extraction.¹⁷

Is money on a phone bringing banking inclusion, and is this inclusion a benefit? Is digital finance reducing poverty or is it creating new divides? With billions of dollars of investment at stake, these questions need answers. A lot of reports are being written and a lot of data are being generated by academics and industry researchers to measure impact. Trawling through the abundant studies fails to yield a clear evaluation of how digital finance affects poverty, if at all. There is no consistent story on whether these innovations actually work and, when they do, why.

Finally, researchers in financial inclusion by and large do not think very much about money and its varying ends and uses. They often take for granted its function as economic agency, asking few of the broader questions that Dr. Mullei pointed me toward. Mobile phone money is often viewed as a delivery mechanism to a last-mile customer, and not as an agent of change in itself.

What is missing is context, observation, and a user perspective. This book tries to correct the balance. Instead of testing hypotheses and measuring detail, I have used a more inductive approach that asks what money is, what it does, and what it means, and that tries to get at local understandings of wealth, relationships, and well-being.¹⁸ My goal has been to focus on context and on people’s intentions with money. I describe unique people and their different degrees of access, their strategies and goals, and the outcomes they achieve. Through these ethnographic studies, I will show that mobile money has created new divides and barriers that are social and technological. Furthermore, having access to digital finance does not benefit people in the straightforward ways that one might expect. In some cases, people are even being harmed, economically and socially, by these technologies.

The findings in this book are based on fieldwork conducted from 2009 to 2018 in Western Kenya, including the towns and hamlets of Kimilili, Bungoma, and Naitiri, and in Nairobi, Kenya. This research has been funded by the Fulbright Senior Scholar Program of the U.S. Department of State, which sponsored me as a lecturer at Egerton University from 2009 to 2010. In 2012, 2014–2015, and 2016–2017, this research was funded by three grants from the Institute for Money, Technology, and Financial Inclusion (IMTFI) at the University of California, Irvine. Also in 2016 and 2017, I served as a consultant to Changa Labs, where I worked with the crowdfunding platform M-Changa, the human-centered design firm ThinkPlace, and the behavioral economics consultancy Busara Center for Behavioral Economics. Above all, I rely on my understandings based on “deep hanging out” during several decades as an anthropologist working in Kenya and as an in-law to a Western Kenya family (I apologize for abusing the privilege).¹⁹

The research involved multiple methods, including semi-structured interviews, unstructured interviews, social network analysis, coproduced drawings, questionnaires, focus groups, human-centered design, and analysis of customer data from the M-Changa company. In 2009 I began interviews with Egerton University students and staff members. Work for IMTFI in Kimilili was a team effort of myself and Gabriel Kunyu, Harpieth Chaggar, Nanjulula Musombi, and Alex Wanyama. We began with 47 intercept interviews in Kimilili town about the use of M-Pesa. Using a snowball method, we then broadened and deepened the engagement with the community, conducting semi-structured interviews with 35 women around Kitale town about land access, marriage, and M-Pesa. Twenty-two women answered questionnaires about M-Pesa usage in savings groups. We also began the social networks study of family remittances, which in 2012, 2013, and 2014 collected information from more than 200 people about money transfer in order to draw 12 sociograms depicting money transfer networks of up to 70 people. In 2014 we conducted a study of coming-of-age rituals with multiple visits to 46 families in the Bungoma and Kimilili region. In 2016, we conducted a study of women’s use of digital financial tools including digital microcredit, where we worked with eight women who provided diary information to us and participated in semi-structured and unstructured interviews. Also in 2016 and 2017, we involved 61 people—31 in Nairobi and 30 in Bungoma, Kitale, and Kimilili—in semi-structured interviews on their use of digital financial tools.

Viviana Zelizer posits a quite different view in The Social Meaning of Money. In practice, we create different kinds of money all the time, using words like “gift,” “allowance,” “inheritance,” “dividend,” “fun money,” and so on. We direct different streams of money toward sustaining and symbolizing distinct relationships.²⁰ An example comes from Zelizer’s study of middle-class American women at the turn of the century, who lobbied for more status in their marriages and more control over their husbands’ wages by insisting on an “allowance,” which implies an entitlement, rather than merely a “gift,” which implies dependence.²¹ These marked forms of money or, more broadly, “media of exchange,” draw the boundaries of relationships, and the power asymmetry or moral obligation they may imply.²² Zelizer’s theory of the social meaning of money does not deny money accounting but gives money decisions context and takes into account intention, relationships, emotions, and meaning—dimensions which are often undertheorized in economics.²³

In Dr. Mullei’s story, for example, an uncle’s gift of a goat maintains a relationship with his married sister. He can look after her interests across the social divide that separates in-laws. Historically, anthropologists working in East Africa noted the importance of these animal gifts such as bridewealth, which sealed the deal at public events like weddings and funerals and served as a history of social alliances. Over time, such economic transfers build up a web of relationships.²⁴ As participants in these economic networks, people seek to accumulate ties, influence and mobilize people, and lay claim to their affection, support, resources, labor, or loyalty: wealth-in-people. These networks and communities offer inclusion to people with diverse embodied skills and knowledge; giving them both belonging “to” and belonging “in.”²⁵ Wealth-in-people explains the popularity of digital money and how it is used in an array of practices to build relationships that channel material value. These relationships are more than just social capital; I avoid that concept because wealth-in-people is equally about both economic value and social value, and about collective and individual value, and also because the kind of value people are seeking is not just capital. Throughout this book I will unfold the idea that the use of digital money is aimed at accessing, building, distributing, accumulating, preserving, and protecting wealth-in-people.

Innovators and investors are captivated by the promise of leapfrogging African money and shunting Africa ahead of the West. But the leapfrogging development narrative, as I discuss in Chapter 3, reinforces an evolutionary view, leading to an assumption that innovation in Africa is somehow surprising. Important players in the innovation story are African entrepreneurs, a local wealth-in-people. The technological path here is deviating sharply from that followed by the digital money of other regions, particularly because of the continued importance of agent networks—charting a unique future for African moneys.

For Kenyans, M-Pesa is their own money, not an imposition from the West. They lay claim to their own invention through enthusiastic storytelling, adding symbolic value to their invention and rejecting the leapfrogging trope. Their narratives, recounted in Chapter 4, emphasize local creativity and cultural wealth, pointing to informal inventions with airtime, Kenya’s innovation hubs and entrepreneurial spaces, and the regulatory experts at Kenya’s Central Bank as important examples of Global South innovation. Unfortunately, the attention paid to the M-Pesa miracle has been far greater than that given to the subsequent failures of digital finance. These failures include digital inequality and digital divides; the rise of indebtedness to digital microloans; and questionable uses of consumer data. Furthermore, e-money deployments across Africa have become ensnared in political conflicts over excessive taxation and fees and political patronage, and in Kenya M-Pesa provider Safaricom was the target of a consumer boycott over charges of election rigging. These dramas are challenging the value of cultural wealth. Instead, an increasingly urgent distributive politics besets digital money—who owns, regulates, and profits from the value channel?

In Chapter 5, I describe the practices and ideas of the wealth-in-people theory of value that underlies the use of digital money. What kinds of money and value have been long-standing in this area, and what strategies of wealth-in-people? How have new kinds of money been incorporated into the web of wealth-in-people? I use anthropological theory and a coming-of-age ritual as it played out in Western Kenya in 2014 and 2016 to answer these questions.

Using digital money transfer, new collectives and groups of wealth-in-people are forming. In Chapter 6, I use maps of money transfer pathways to reveal the interconnections of money transfer and show how they are embedded in social network positions and roles. Money-sending networks in families reveal important social norms around generosity and obligation relating to age, generation, and gender. I also ask my informants to draw their networks. I call their drawings “network self-portraiture.” Their drawings represent different kinds of money or media through visual metaphors. Drawings of hearts, buses, and boats describe the moral and symbolic qualities of money. Self-portrait drawings can reveal the process behind social networks—the relational work²⁶ around money exchange. The money networks are an important means of distribution in family groups and friendship groups.

In Chapter 7, I use ethnographic information to explain how people form digital money networks. Landlessness, unemployment, inequality, and the increasing importance of cash money weigh heavily on the families I describe. Fathers fundraise for life-cycle rituals, bridewealth, and other ritual gifts with brothers, sons, and male age mates who support one another in building and bequeathing durable assets. Women use their central positions in networks of siblings, mothers, and mothers’ families to help fund schooling, medical care, and everyday needs. These networks are ways of generating, circulating, distributing, and accumulating wealth-in-people: they are ways of surviving, ways of belonging, and ways of getting ahead.

As wealth-in-people circulates, people experience far more requests for money than their resources can support. They frequently work to lessen the social pressure to support others and withdraw from their networks. By disconnecting from technology, they deflect responsibility to address needs in their networks, instead adopting a liminal position of strategic ignorance.²⁷ These disconnections, described in Chapter 8, are not an assertion of self-interest, as might be assumed. I see these strategies of non-use as a way to protect wealth-in-people when powerful social norms that value helping, caring, and generosity collide with the scarcity of money.²⁸ Changeable strategies reveal the fragility of wealth-in-people, the dilemmas of responsibility, and distributive politics of informal financial practices. In this chapter I draw attention to practices of deliberate self-exclusion from financial networks.

Digital microcredit—small loans offered over the mobile phone—have been a focus of African fintech. Numerous industry-side reports justify these loans as empowering women to support their enterprises. In Chapter 9, I use a network perspective to show how these digital debts become a part of women’s social and financial relationships. Women attend to weighty social obligations as they struggle to build businesses using microloans as capital. The stigma of private digital debt presents risks to their reputations. Furthermore, I show how one research participant juggles loans across her social networks, and how the hidden labor of cash-in/cash-out agents assists users in accessing and paying for loan services.

Nairobi’s Silicon Savanna is an emerging fintech hub and entrepreneurial space seeking to scale innovative finance for the bottom of the pyramid. Here, a crowdfunding platform called M-Changa enables people to raise money online from across their family and friend networks. The M-Changa case study in Chapter 10 explores how wealth-in-people can be reimagined as a solution for poverty. I describe how our design team used human-centered design and behavioral economics (BE) interventions aimed at scaling the company. The lessons learned from this project throw into relief the obstacles facing Kenya’s fintech scene: digital divides and inequalities of technology access, social inequalities, and deliberate self-exclusion: strategic ignorance. In Chapter 11, I summarize some design principles based on my findings.

Evaluating the impact of digital money depends on knowing what users actually do with it. This study follows money flowing through the web of relationships. As members of networks, people can help and care for others; pursue aspirations for a better life in financial clubs aimed at saving and investing; express belonging by sending gifts and contributions; find prestige and recognition by mobilizing others and solving problems; and secure assets for their communities and their heirs. But being a member of these networks also requires access to technology, social connections, collateral, and skills. People without these means may be left out or risk shame. As a result, they may through their own strategies of non-use find the margins and liminal spaces of wealth-in-people. Money networks are thus creating new divides, barriers, and inequalities, which need to be addressed if digital finance is to fulfill the promise of inclusion.

Notes

1. Real-time gross settlement allows interbank transfers to be settled individually and without a waiting period, potentially increasing the oversight of the Central Bank and reducing the risk of error and fraud.

2. Maurer 2015.

3. Tilley 2011.

4. Ndemo and Weiss 2017.

5. Sen 2010.

6. CGAP 2019a.

7. Fine 2010; Roodman 2011; Roy 2010.

8. Klapper 2019.

9. For example, see Loizos 2018.

10. Jack, Ray, and Suri 2013; Kikulwe, Fischer, and Qaim 2014; ApplePay, Venmo, and WeChat Pay.

11. Suri and Jack 2016.

12. Rhyne and Kelly 2018.

13. Duvendack and Mader 2019.

14. Duvendack and Mader 2019; Mader 2017; Rhyne and Kelly 2018.

15. Wyche and Olson 2018; Roessler 2018.

16. Smart Campaign 2017; Microsave 2019.

17. Dalinghaus 2019; Jenkins 2018; Jeong 2016.

18. Susan Johnson 2004; Susan Johnson 2012; Susan Johnson 2017; Susan Johnson and Frichte Krijtenburg 2018; Maurer 2015; Zelizer 2017.

19. Geertz 1998, 70–71. What he calls here “localized, long-term, close-in, vernacular field research” is the model for anthropology.

20. Bohannon 1959; Guyer 2011; Maurer 2015.

21. Zelizer 2017, 42–44.

22. Zelizer 2005, 37

23. Morduch 2017.

24. Radcliffe-Brown 1952.

25. Bledsoe 1980, chapter 3; Cooper 2017; Guyer 1995; Guyer and Belinga 1995; Kopytoff and Miers 1977; Kusimba 2020; Makhulu 2017.

26. Zelizer 2005, 37.

27. Gershon 2000.

28. Baumer et al. 2015.