Keywords

1 Development Challenge

Since the 1990s, cash transfer programs have been an important part of social protection policies in low-income countries. As of May 2020, approximately 159 countries had 700 types of social protection programs in place, over 200 of which were cash-based measures (Gentilini et al., 2020). While implementing such programs raises numerous challenges, from targeting, to funding, to choosing the modality, one key issue is distribution. In higher- and middle-income countries, such programs are often implemented electronically, via either bank transfers or prepaid debit cards. Yet in lower-income countries with limited financial infrastructure, social programs often require physically distributing cash in small denominations to remote rural areas. Globally, 1.7 billion adults remain unbanked, without an account at a financial institution or through a mobile money provider (Demirguc-Kunt et al., 2017). This lack of access to financial services not only increases the logistical challenges associated with implementing cash transfer programs but also potentially creates substantial direct and indirect costs for program recipients. This is especially the case in sub-Saharan Africa, where money transfer costs are among the highest in the world (World Bank, 2017). In such an environment, how can cash transfers or salaries be distributed more efficiently using digital technologies? In addition to efficiency, can digital transfer mechanisms improve the welfare of program recipients along other dimensions? Could it benefit or disadvantage particular subgroups? And could public investments in transfer infrastructure lead to spillovers for person-to-person (P2P) transfers, especially in an area of the world where remittances represent 2.5% of GDP (World Bank, 2018)?

These questions are at the heart of this case study on Niger, a landlocked country in the Sahelian zone of West Africa and one of the poorest countries in the world. The Sahel is the transition area between the Sahara Desert to the north and the tropical zones to the south, receiving approximately 200–800 millimeters of rainfall per year. The region has witnessed some of its most serious climate-induced food shortages in the 1970s and 1980s, with approximately 250,000 drought-related human fatalities occurring in the 1960s, 1970s, and 1980s. Since that time, Niger has been subject to frequent droughts, the most recent of which occurred in 2018 (OCHA, 2018).

Given that agricultural production in Niger is primarily rainfed, with a unimodal distribution, inter-annual deviations in rainfall are strongly correlated with fluctuations in agricultural output, income, and food security. If financial markets are performing optimally, then households could save or borrow to cope with such shocks. Yet, given the limited access to financial services – in fact, Niger is one of the most financially excluded countries in the world – such strategies are difficult to implement, especially for the rural poor (Collins et al., 2009; Karlan & Morduch, 2010; Dupas & Robinson, 2013; Rutherford, 2000). As a result, rural households often rely upon external assistance – whether remittances or external aid – to cope with idiosyncratic and covariate shocks, both of which require money transfers.

This case study focuses on a particular crisis in Niger, the 2009/2010 drought and corresponding harvest failure, which affected more than 2.7 million people (FEWS NET, 2010). In response to this crisis, governmental and nongovernmental organizations (NGOs) implemented a series of social protection programs, including food aid, vouchers, and cash transfers. While seemingly simple, the context was not: At the time, Niger had one bank for every 100,000 people (Demirguc-Kunt et al., 2017), few paved roads, and small-scale conflicts along the Niger-Mali and Niger-Nigeria borders. Thus, the Nigerien government and NGOs typically distributed cash transfers manually, placing cash into individual envelopes and transporting it with armed security forces into remote rural areas (Aker et al., 2016).

In January 2010, a relatively new technology – mobile money – was introduced into the country by one mobile network operator (MNO), known as “Zap.” Similar to M-PESA in Kenya, the mobile money product allowed users to transfer money via a text-based system on their phone and pick up their cash at a local agent. In the context of the food crisis, the technology offered a unique opportunity: Rather than physically distributing cash to thousands of beneficiaries, the government and NGOs could disburse cash transfers electronically via the mobile money system. This digital transfer system could potentially (1) reduce the transfer costs for the implementing agency and program recipients, thereby improving program coverage and outreach; (2) lead to other improvements in program recipients’ well-being, primarily due to time savings; and (3) allow program recipients to use mobile money for remittances, an important income source in Niger (Aker et al., 2020a, b; Jack & Suri, 2014). To explore the feasibility, cost, and impact of using mobile money for cash transfer programs, researchers collaborated closely with an NGO, Concern Worldwide, to design and implement a randomized control trial (RCT) across 96 villages in one region of Niger.

Between 2010 and 2020, many of the conditions under which this case study took place have not significantly changed in Niger. Niger is still one of the most financially excluded countries in the world (Demirguc-Kunt et al., 2017), and climate-related shocks and food crises are relatively common. These shocks have been further aggravated by the escalation of armed conflict: As of 2019, there were 4.5 million people displaced and 12.2 million people suffering from food insecurity within the West Africa region. While mobile money exists in Niger, with products offered by three different MNOs, its adoption has not taken off as predicted. M-money adoption was estimated at 9% as of 2017 (Demirguc-Kunt et al., 2017), with relatively lower rates in rural areas, despite mobile ownership rates of over 80% (Aker et al., 2020a, b). Thus, similar challenges as those encountered in 2020 were also apparent in 2018, during a second cash transfer program.

It is easy to dismiss the low rates of mobile money adoption as specific to Niger, with limited relevance to other contexts. Yet, many of these statistics are mirrored in the West Africa region. While average mobile phone adoption in the region is 67% and there are 59 mobile money deployments, mobile money has been slower to take off as compared with East and Southern Africa. For example, despite the fact that there were 163 million accounts in 2019, there is significant heterogeneity in adoption across and within countries (GSMA, 2019). In addition, there is a stark contrast between adoption and usage; out of the total number of registered accounts, 34.6% have shown some activity, with the number of active users ranging from 1% in Niger to 20% in Ivory Coast (Fig. 10.1). This appears to be due, in part, to the limited mobile money agent infrastructure, limited interoperability between MNOs within and across countries, and regulatory frameworks in place (Aker et al. 2020a, b; CGAP, 2016). As a result, mobile money has not yet become the transformative technology in countries such as Niger, nor for some of its neighbors, despite potentially high demand for the service.

Fig. 10.1
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Number of accounts and active accounts per population per country

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Despite these caveats, digital financial services may still offer significant potential for small-scale farmers to save, invest, and smooth consumption in West Africa. Since 2012, a number of “second-generation” digital financial services – namely, digital credit, savings, and insurance – have proliferated in East and Southern Africa. As of 2015, 20% of Kenyans were using Safaricom’s M-Shwari digital credit and savings product (Cook & McKay, 2015). There are numerous concerns that have been raised with digital credit products, such as high effective interest rates (CGAP, 2016), as well as high delinquency and default rates. While rigorous evidence of their impact is nascent, early studies in this area suggest that such digital products enabled households to smooth consumption in the face of shocks and encourage short-term savings, although they have not specifically studied agricultural outcomes (Bharadwaj & Suri, 2020; Bharadwaj et al., 2019). While MNOs in West Africa primarily offer first-generation digital financial services – i.e., mobile money – there have been more recent digital credit deployments in countries such as Benin, Ghana, Ivory Coast, and Nigeria. Existing studies in this area promise to shed new light on their impacts in the years to come.

2 Implementation Context

Niger is one of the largest countries in sub-Saharan Africa, with relatively limited access to roads, financial infrastructure, or electricity. The first mobile money system in Niger was introduced in January 2010. Known as “Zap,” the product was developed by one of the MNOs, Zain (later Bharti Airtel). Like most mobile money systems, Zap allowed users to store value in the mobile money account, convert cash in and out of the account, and make transfers by using a set of text messages personal identification numbers (PINs) (Aker & Mbiti, 2010). The cost of making a US$ 45 transfer using Zap was US$ 3 in 2010. Initial coverage, usage, and growth of Zap were limited and geographically focused in the capital city (Niamey) and regional capitals.

Given the context, there were a number of challenges to designing, implementing, and evaluating a mobile money cash transfer program. The first of these was mobile phone ownership: While mobile phones were initially introduced in Niger in 2000 and had grown substantially between 2000 and 2010, adoption rates were at 30% by 2010. Although there were high rates of phone sharing within and across households, the nature of the cash transfer program – which targeted vulnerable households within villages and targeted women within the household – meant that mobile phone ownership was a potential constraint to implementation.

Second, beyond the issue of mobile phone ownership, few households in Niger – and specifically in the study region – knew about (or had used) mobile money. Since mobile money had only been introduced in January 2010 and the first transfer was scheduled to take place in May 2010, adoption in remote rural areas was less than 1%. This not only meant that households were not registered for mobile money – a process that required some type identification – but they also did not have the special SIM required for the platform.

Third, the mobile money platform was text- and number-based: The program recipient would receive a text notifying her of the transfer with the amount and was required to remember a four-digit PIN number in order to pick up the transfer from the agent. This was therefore the fourth challenge: Niger had, and still has, some of the lowest literacy rates in the world, with an average literacy rate of less than 30% and an average of 2 years of completed schooling (Aker & Ksoll, 2019). In our study area, 58% of women had attended some school, but literacy rates among women were less than 15%. This led to challenges in manipulating the mobile phones, as well as recalling PIN codes.

The final challenge was related to the density of mobile money agents: As a new product, there were few agents located outside of the capital city, and there were no mobile money agents in the study area. Thus, while the mobile money product had the potential to reduce the costs associated with distributing the cash transfer for the NGO, it also had the potential to increase the costs for the program recipients, essentially shifting the risk to the private sector: the MNOs and the agents.

Designing and implementing the program and corresponding research required close consultation and collaboration with a diverse set of stakeholders: (1) the NGO, Concern Worldwide, who was the implementing agency for the cash transfer program; (2) the 116 villages who were part of the cash transfer program and were responsible for identifying vulnerable households within the community; (3) Zain, the MNO, who was the only mobile money operator at the time; (4) local traders and retailers, who were the primary mobile money agents in the region; (5) the local data collection firm, Sahel Consulting, and Tufts University, who were jointly responsible for designing the research and data collection during the evaluation; and (6) the Ministry of Social Protection, who was responsible for overseeing and coordinating diverse cash transfer interventions during the food crisis of 2009–2010.

Close collaboration among these different sets of stakeholders allowed for creative resolution of the four challenges identified above. In order to address the issue of low mobile phone ownership, it was decided to purchase simple mobile phones for program recipients. The team also discussed how the provision of mobile phones might affect program recipients’ behavior and hence the research results, which led to the modification of the original research.

Fig. 10.2
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In order to address the challenges related to mobile money awareness and literacy, Concern Worldwide, the MNO, and researchers collaborated along two key dimensions. First, in addition to the mobile phones, program recipients also received SIM cards that were “Zap-enabled,” meaning that that could be registered for (and use) the Zap product, and second, Tufts University and Concern Worldwide developed a training manual and corresponding trainings on how to use mobile money in a low-literate environment (Fig. 10.2). Building upon research done by Tufts University on a mobile phone literacy project in Niger, Concern Worldwide also distributed a mobile phone poster, which allowed program recipients to find their PIN code on the handset, as well as memorize the number (Fig. 10.3).

Fig. 10.3
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Mobile phone poster

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Finally, in order to address the issue of agent network, Concern Worldwide worked closely with Zain to identify potential agents in the region, in particular by informing Zain of the location of the cash transfer villages. In addition, Concern Worldwide notified Zain of the timing of the cash transfers in advance, so that agents would have sufficient liquidity for program recipients to cash out.

3 Innovate, Implement, and Evaluate

3.1 Innovation

In light of the high costs involved in distributing cash transfers in Niger, the introduction of mobile money offered a new mechanism for disbursing cash transfers to food-insecure households. The starting point for the intervention was therefore two models of distributing cash transfers – manual and electronic cash (in-person) – and adapting this to the particular context.

The cash transfer intervention in this context was relatively simple: Program recipients among 116 food-insecure villages of the Tahoua region of were provided with a monthly transfer of US$ 45 over a 5-month period, for a total of US$ 225. The transfer was provided on the hungry season (from May to September), in the hopes that this would reduce the likelihood of more severe food insecurity, malnutrition, and the distress sale of assets. While 116 villages were eligible for cash transfers, based upon drought and production data, 20 villages were removed from the evaluation sample, as they either did not have mobile phone coverage (and hence were not eligible for cash transfers via mobile money) or were in highly insecure areas (and hence were not eligible for cash transfers in person). This therefore left a sample of 96 villages for the evaluation.

Eligible households within each village were identified by a village-level vulnerability exercise. Using indicators such as livestock ownership, landholdings, and the number of household members, households were classified into four vulnerability categories (A, B, C, and D), with C and D households selected for participation in the cash transfer program (Aker et al. 2016). The number of program recipient households per village ranged from 12 to 90% of the village population, with an average of 45% (Aker et al., 2016). All targeted households were scheduled to receive the same amount, at about the same time, each month.

Villages were assigned to one of three innovation models:

  1. 1.

    Manual cash, whereby program recipients in a given village received the cash transfer in the village or via a nearby village, using the standard model of cash delivery. Program recipients thus received a beneficiary card and were required to travel to the cash delivery point on a specific day of each month. At the cash delivery point, program recipients had to wait in line and have their identity verified before receiving their cash in an envelope.

  2. 2.

    Manual cash with a Zap-enabled mobile phone, whereby the program recipients received their cash in a similar mechanism as above but also received a Zap-enabled mobile phone, worth approximately US$ 5. The mobile phone had a Zain SIM, and program recipients could use mobile money if they wished, but they did not receive their transfer via mobile money. They also received the training on how mobile money worked, as explained below.

  3. 3.

    Zap transfer, whereby program recipients received the Zap-enabled mobile phone (as was the case in the second model) but received their transfer via the mobile phone. This involved not only distributing the phone to households (with the Zain SIM) but also conducting an interactive training with households to explain how mobile money worked and what they could expect. This model also required collaboration between Concern Worldwide and Zain to create a web-based, password-protected interface with program recipients’ phone numbers, transferring money to a bank account connected to the Zap account, identifying and verifying program recipients, uploading an encrypted file onto Zain’s system (so that they would not have program recipients’ personal identifying information), and sending the cash transfer via SMS to program recipients’ Zap accounts.

Among these three models, the primary innovation of interest was the third one. While mobile money could have affected household outcomes in a variety of ways, the primary hypothesis behind this research was related to transfer costs. In other words, by providing the cash transfer via mobile money, it was hypothesized that this would reduce program recipients’ costs in obtaining the transfer, in terms of both transport and waiting time. It was further hypothesized that mobile money would affect household outcomes in the following ways:

  • The reduction in transfer costs would allow program recipients to invest time in other productive activities during the planting period, as well as change the timing and location of purchases, particularly if they were able to purchase food and nonfood items from agents.

  • The introduction of mobile money would allow program recipients to use mobile money for private (person-to-person) transfers, therefore increasing the amount of remittances available from migrants, as well as allowing remittances to arrive when they were needed the most (Jack & Suri, 2014).

  • Because the mobile money cash transfer mechanism was more private than the manual cash transfer (as program recipients only received a discreet “beep” letting them know that the transfer had arrived), this could have allowed program recipients – all of whom were women – to have more control over the cash transfer resources.

3.2 Implementation

The design and implementation of the above interventions were developed collaboratively between Concern Worldwide and Tufts University. Initially, Concern Worldwide only wanted to compare two interventions: the manual cash group and the mobile money cash transfer group. When it was realized that mobile phone ownership was only 30% among the target population and that mobile money adoption was essentially zero, the teams quickly realized that improving program recipients’ access to mobile phone technology (by providing mobile phones), as well as the mobile money technology (by facilitating registration, SIM cards, and trainings), was required.

The provision of Zap-enabled mobile phones to the mobile money cash transfer recipients therefore required one primary modification to the initial interventions. The first was the addition of the “cash transfer plus mobile phone” intervention group (model no. 2). Since the Zap program recipients were supposed to receive the mobile phone plus the cash transfer via the mobile phone, this would imply that there were two differences with the manual cash transfer approach: the mobile phone and the use of mobile money for the cash transfer. If the mobile phone on its own improved program recipients’ welfare – either by improving communication on agricultural prices or allowing households to increase access to private transfers – then it would be difficult to disentangle the impacts of the mobile phone from the impacts of the mobile money product. By comparing the manual cash group with the manual cash plus mobile phone group, we were able to answer the question “Conditional on receiving a manual cash transfer, what is the additional impact of the mobile phone?” Then, by comparing the second intervention group with the third, we were able answer the question “What is the additional impact of receiving cash via mobile money?” The addition of the second intervention group created numerous discussions, as this required additional resources (cash to purchase the mobile phones) and trainings. The researchers and Concern Worldwide decided, in consultation, that the primary objective of the research was to measure the impact of the new mobile money transfer technology and that the impact of the mobile phone needed to be netted out.

The second modification was related to the availability of agents in the targeted region. Despite intense work with Zain to encourage them to register agents in the region, the MNO was unable to register a sufficient number of agents by the time of the first cash transfer. As a result, one agent distributed cash to 32 mobile money villages for the first transfer. After additional discussions with Zain, the company was able to register more agents in the region, based upon their own criteria for choosing suitable agents. One key concern, however, was that these agents were equitably distributed across all 96 villages in the evaluation sample, rather than simply focusing on mobile money villages, in order to minimize differences between the mobile money group and the manual cash transfer groups. This was verified during the evaluation stage; the number and density of Zap agents was similar across all groups, without a statistically significant difference between the two. This implied, therefore, that any differences observed between Zap and manual cash villages would not be driven by the differential presence of mobile money agents.

3.3 Evaluation

In order to measure the impact of the mobile money cash transfer innovation on outcomes of interest, we used an RCT at the village level. The 96 evaluation villages were first stratified by administrative division and randomly assigned to one of the three cash transfer innovations, with 32 villages in each group. The primary outcomes measured were those in the original theory of change: (1) transfer costs, both for the implementing agency and for program recipients, including when, where, and how they obtained their cash; (2) uses of the cash transfer, including the different categories; (3) welfare measures associated with the cash transfer, including food security, diet diversity, and nutritional outcomes; and (4) indicators related to mechanisms, in particular related to access to remittances, as well as intra- and inter-household sharing of transfers.

The evaluation collected a wealth of data, including a baseline (May 2010), a midline soon after the transfers (December 2010), and a final round 1 year later (May 2011). The data were a panel dataset, with the primary program recipient as the survey respondent. For each survey found, intensive survey piloting was done; the survey was first written, with the team trained, and then piloted in the field at least three times before being deployed. In addition, before the midline and final survey rounds, qualitative data were also collected before the quantitative surveys, in order to gain insights into impacts that were not initially expected in the initial theory of change. This led to some useful insights about the observability of the transfer within the household (as women wore the mobile phones around their necks and reported that only they knew of its arrival) and a module on intra-household decision-making. In the current context of using pre-analysis plans (PAPs) for rigorous evaluations, these findings may not have been fully integrated into the study or made it into the final paper.

Overall, the evaluation had six key findings:

  • The marginal costs of the mobile money cash transfer were 20% lower than the costs of distributing the cash transfer manually, but the fixed costs were substantially higher, primarily due to the purchase of the mobile phones. Unlike other studies on digital transfers, we do not find evidence that the m-transfer mechanism had any impacts on leakage (Muralidharan et al., 2016).

  • Mobile money program recipients traveled shorter distances to obtain their transfer as compared with their manual cash counterparts (both cash only and cash plus mobile). While the manual cash and mobile program recipients traveled an average of 4 km (round-trip) from their village to obtain the transfer, Zap program recipients traveled 2 km to the nearest agent. This is equivalent to a travel time savings of approximately 1 h for each cash transfer or 5 h over the entire program. However, this analysis excludes the cash program recipients’ waiting time, which averaged 4 hours per cash transfer, as compared with 30 minutes for Zap recipients, equivalent to a savings of 2.5 days (Fig. 10.4).

    Fig. 10.4
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    Travel cost by treatment group

    Source: Aker et al. (2016)

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  • Mobile money cash transfer recipients that used their cash transfer to buy more diverse types of goods were more likely to purchase protein- and energy-rich foods. These diverse uses of the transfer resulted in a 9–16% improvement in diet diversity as compared to the cash and mobile groups, primarily associated with the increased consumption of beans and fats. In addition, children in the Zap group consumed an additional one-third of a meal per day (Aker et al., 2016). Yet, Zap households did not reduce their ownership of other durable and nondurable goods, suggesting that other household members were not decreasing their contribution to household goods as a result of the transfer.

  • These results can be partially explained by two factors: 1) Zap program recipients spent less time on obtaining the transfer (Fig. 10.4), and 2) female program recipients in Zap villages had increased bargaining power within the household. In terms of time savings: While the magnitude was relatively small – approximately 2.5 days over a 5-month period – this is a probably lower bound on actual time savings. In addition, the savings occurred during the planting season, a time when opportunity costs were high, implying that the time savings could have enabled Zap program recipients to engage in other productive activities or invest more time in childcare. There was some suggestive evidence in support of the former channel: m-transfer households were more likely to cultivate marginal cash crops primarily grown by women (Aker et al., 2016). In terms of intra-household decision-making, program recipient reported that mobile money was less observable to other household members, thereby allowing them to temporarily conceal the arrival of the transfer (Aker et al., 2016). This was supported by proxy measures of intra-household decision-making: Zap program recipients were more likely to travel to weekly markets, spend more on children’s clothing, and maintain the improved diet diversity results 6 months after the program, well after the cash transfer had been spent (Aker et al., 2016).

  • While program recipient households used mobile money to receive their transfer, they did not use it to receive remittances or to save, and there were no significant differences in the frequency or amount of remittances received. These results were perhaps not surprising, as the agent network was not widespread at the time, and the mobile money system could not be used for transfers to Nigeria, the destination for a majority of migrants.

  • There were no differences in costs, expenditures, or other measures of well-being between the cash transfer or mobile phone plus cash transfer groups, suggesting that the mobile phone (on its own) had no additional effect on household welfare.

While these results are promising, there are several limits to the generalizability of these results. First, our case study studied the impact of different transfer mechanisms during a food crisis, when the marginal utility of income can be high. And as a result, uses of the cash transfer could be more diverse and less focused on food items in other contexts. And second, since Niger is one of the poorest countries in the world, with low rates of literacy, financial inclusion, and mobile money adoption, the context might be different from other countries with higher rates of financial inclusion and a more thoroughly developed mobile money infrastructure, especially those in East Africa. Nevertheless, Niger’s educational, financial, and mobile money indicators are not vastly different from other Sahelian countries in West Africa, including Burkina Faso, Mali, northern Ghana and northern Ivory Coast, suggesting that these results might be informative for those contexts (GSMA, 2019; Findex, 2017).

3.4 Adaptation

In 2018, the question of how to safely and efficiently distribute cash transfers arose in the context of another project in Niger, one which studied the impact of training and cash transfers on the adoption of an environmental technology (Aker & Jack, 2020). The study took place across 180 villages in the Zinder Region, with 110 villages assigned to receive either conditional or unconditional cash transfers. Overall, 1750 program recipients were supposed to receive a one-time cash transfer between April and June 2018. Located in the far east of the country, the villages were relatively close to the Nigerian border and had relatively high rates of migration and mobile phone ownership (over 60%). The project was a collaborative effort between Tufts University (the research lead), Sahel Consulting (the data collection firm), and the Ministry of Environment, neither of whom had the capacity to distribute cash transfers manually.

Based upon the Zap research in 2010, the team understood that distributing cash transfers via mobile money required substantial investment and that several preconditions were necessary: mobile phone ownership, mobile money usage, and a mobile money agent. Despite high rates of migration and intense demand for money transfers, fewer than 3% of households had used mobile money as of 2017 (Aker et al., 2020c). In addition, there were only four mobile money agents in the entire region. This suggested that neither mobile money infrastructure nor adoption had changed significantly since 2010.

In light of these conditions, the stakeholders generated four options for distributing the cash transfers: (1) the manual distribution of cash transfers by Sahel Consulting, similar to the role of Concern Worldwide in 2010; (2) the electronic distribution of cash transfers via local money transfer providers, similar to Western Union and MoneyGram; (3) the electronic distribution of cash transfers as airtime credit, which program recipients could then convert into cash; or (4) the electronic distribution of cash transfers via mobile money.

Options no. 1 and no. 2 were rejected by the implementation partners. The first option (manual distribution) was rejected as too risky, as it would require transporting US$ 35,000 in cash to remote rural areas, and security would be needed to reduce the likelihood of theft. The second option (electronic distribution via local money transfer companies) was rejected because it was not a relative improvement over mobile money: The location of the money transfer agents was similar to the location of mobile money agents, and the money transfer agents could not guarantee that they would have sufficient liquidity on hand.

As a result, the stakeholders focused their discussion on options no. 3 and no. 4, each of which had advantages and disadvantages. As each stakeholder had different opinions on the relative merits of each option, the team used a technique called “Analytical Hierarchical Process” (AHP) to weight the options and make a decision (Saaty, 1980; Leal, 2020). In essence, this approach involved stating the goal of the exercise (finding the best cash transfer mechanism) and the criteria as to how this decision would be made (viz., the costs to the program recipients, the number of agents, the knowledge of the technology, and the risks to the implementing agency). Each individual on the team assessed each option along each criteria and used this to come up with a ranking. The rankings are all compared, and weights were developed.

Based upon this exercise, option no. 4 scored relatively higher on a number of criteria, in particular the lower risk to the Ministry and Sahel Consulting, as well as the program recipients. As a result, the team decided to implement option no. 4 but with a slight modification. In essence, this involved sending the money via the mobile money to the program recipient’s mobile phone number, as this did not need to have a mobile money account (called “envoie code”). The recipient received a code and was able to take this code to the nearest mobile money agent to pick up the money. If the program recipient did not have a mobile phone, then they were asked to provide the number of someone whom they trusted. This modification did not require providing mobile phones, nor registering program recipients on the mobile money platform, as was necessary in 2010. With some additional monitoring – namely, by calling program recipients and the village chief and working closely with the MNO – over 98% of program recipients received their cash transfer and received the full amount of the cash transfer.

4 Results and Lessons Learned

Overall, this case study shows how the introduction of a new digital technology could be harnessed to quickly distribute cash transfers in the context of a slow-onset emergency, where access to financial institutions and money transfer providers is limited. While the original case study took place in 2010, given the fact that over 100 million adults received their cash transfers manually as of 2017 – as well as the growth in cash transfer programs in response to the COVID-19 crisis – the results provide a number of lessons learned for cash transfer programs for the unbanked in urban and remote rural areas. In the 10 years since this study has taken place, there have been a number of other studies using digital platforms to provide cash transfers (Muralidharan et al., 2016; Haushofer & Shapiro, 2016), showing reductions in transfer costs, leakage, and improvements in other welfare measures. Many, yet not all, of these studies have taken place in certain contexts, such as Kenya and India, which have robust and well-developed digital technology systems.

Outside of these areas, several things are clear. First, mobile money offers significant opportunities to distribute cash transfer programs at scale, especially among the poor, who tend to be less likely to have a bank account. Nevertheless, it requires significant increases in the density of mobile money agents, as well as increases in mobile money adoption among the unbanked, which has been a constraint in many countries, especially in West Africa. Increasing the density of mobile money agent may require some innovation on behalf of regulators, banks, and mobile phone operators to register different entities as mobile money agents. If the number of agents cannot be increased in the short term, then distributing such transfers can impose higher costs on cash transfer recipients, as well as added risks associated with a “rush” on mobile money agents. Beyond increasing the number of agents, creative solutions may also be required to encourage mobile money adoption, especially among the urban poor, either by having a more flexible approach to registration or by using a technology that allows a user to send money to a nonmobile money user, similar to our work in 2018. These issues, of course, will need to be balanced with concerns regarding corruption and leakage.

There is significant room for more research on the constraints to the growth of digital financial services (Fintech) in many countries in sub-Saharan Africa, especially in West Africa. While digital credit, savings, and insurance have taken off in countries such as Kenya, Uganda, Rwanda, and Tanzania, many of the digital financial services (DFS) products are still “first generation” in West Africa. This could be due to four related and interconnected issues: (1) the regulatory framework in West Africa, which leads to competition between the “bank-led” and “MNO-led” models of mobile money; (2) the effect of the regulatory framework on MNOs’ interest in, and profits from, mobile money; (3) the incentives provided to mobile money agents, which therefore reduces their number and activity; and (4) the lack of interoperability of mobile money products within and across West African countries, which affects the potential for its use for remittances, the main driver of demand in the region.

5 Summary and Interpretive Text Boxes

6 Discussion Questions

  • Did you think that the current model of distributing cash was a problem in Niger prior to the program? If so, why? If not, why not?

  • Do you think that providing mobile phones was necessary in this context?

  • What other factors might have been taken into consideration to increase the sustainability of the adoption and usage of mobile money in the medium and long term?

  • Should the identification and registration of mobile money agents be left solely to the responsibility of the MNO or in collaboration with the public sector? What is the best way to ensure collaboration?