Getting access to credit is a critical challenge for small-holder farmers all over Sub-Saharan Africa . A new breed of financial-technology firms (fintech) promises to address this issue, claiming that digital technologies can lower the barriers for borrowers and cut transaction costs for lenders. As part of our ongoing project on digitisation and data in US and Kenyan agriculture, we have been examining these claims, studying how tech companies translate them into business initiatives and exploring the implications for knowledge production, economic growth and value redistribution.
In rural Kenya, fintech innovations are premised on greater efficiency and transparency and inspired by narratives of digital disintermediation. Similarly to what argued for migrant remittances by Vincent Guermond in a previous post of this blog series , digital lenders harness data (extracted through digital infrastructures) and algorithms to make farmers more legible and, therefore, more predictable. In order to expand their pool of data, Kenyan fintechs are increasingly embedding themselves into inter-connected digital infrastructures, or platforms. These platforms provide farmers with end-to-end solutions, and thereby bundle together financial services with the provision of agricultural inputs and information extension services. In so doing, lenders recalibrate and harmonize their risk-assessment procedures, and construct an ideal type of farmer whose financial behaviours and importance in the local value chain can be clearly pinned down.
Proponents of the ‘platformization of agricultural finance’, as we call it, assert that such platforms create shared market legibility and increase efficiency for all groups across the agricultural value chain. Thus, in their view, financial institutions can reduce the risk of default by using the digital footprints of the applicants to improve their underwriting process; small-holder farmers can protect themselves from exploitative middlemen and gather a more thorough view of the market; input providers can gain a better understanding of their customers; and buyers can trace the journey of their goods and offer safer, fresher food to their customers.
In the course of our investigation in Kenya so far, this narrative has become blurrier. Despite the positive private sector discourse associated with the emergence of platforms in agriculture, there are reasons for apprehension and caution. The business model of the digital platform itself is premised upon network effects: in order for the platform to make accurate tailored decisions among a diverse set of users, it must deepen and broaden its database and centralize insights across data sources. This commercial logic makes it likely that single dominant players or groups of dominant players with shared commercials interests will come to control these new digitally enabled market functionalities, and monopolize the production of value and knowledge. In such a context, abuse of power and the entrenchment of pre-existing inequalities are possible.
Digital financial inclusion in the Silicon Savannah
The strong support for agriculture that characterized the post-Independence years has declined over time. The Central Bank of Kenya now calculates that agricultural finance accounts for less than 5 per cent of the outstanding national credit. After receiving a blow during the SAP period in the 1980s, state support never fully recovered (Gitau et al., 2009). The withering of state-provided services to smallholder farmers in rural areas (such as extensions and lines of credit) has left a vacuum that for long the private sector has been hesitant to fill. Informal money lenders and local traders/input stockists cover 20% of their financial needs (Njeru et al., 2017).
Despite the fact that smallholder farmers represent 70% of Kenya’s agricultural production, small-scale agricultural finance remains a risky business. Banks are reluctant to invest in rural areas where infrastructures is poor and the population is scattered. Building brick-and-mortar branches and supporting an agent network are costly endeavours. Furthermore, the return on the investments is far from certain. Smallholder farmers are elusive financial subjects. They often lack records on both transactional income and the overall performance of their farms and collaterals (such as title deeds) to secure loans. Moreover, agricultural production is increasingly volatile because of erratic weather patterns (Njeru et al. 2017) and fluctuating commodity prices at the global level (Addison et al. 2016; Kharas 2011). As a result, small-scale agriculture remains underfunded, hindering farmers’ resilience to shocks and limiting their capacity to invest in inputs (Njeru et al. 2017).
Organisations such as UNCTAD (2015) have advocated for new financing mechanisms for smallholders (44). This focus on innovation for small-scale agricultural finance stems from a broader plan to expand financial inclusion among so far excluded segments of populations (Schwittay, 2011; Ouma et al. 2017). As argued by Gabor and Brooks (2016), the development agenda emerging from the 2008 global financial crisis has been strongly dominated by the financial inclusion imperative. “Banking the unbanked” has become the rallying cry to mobilize a well-aligned constellation of international organisations, philanthropic investment firms and intergovernmental bodies (Mader, 2016). Digital payment systems occupy a central position in these strategies (Demirguc-Kunt et al., 2014). Old and new financial institutions, international organisations and corporate-philanthropic foundations increasingly see digital technologies as a bridge to reduce the gap between supply and demand for financial services in rural areas.
A platform to rule them all
Kenya has emerged as the quintessential laboratory for digital financial innovations due to its permissive financial and technological regulation and the overwhelming success of M-Pesa, a mobile money service launched jointly by DfID and the Kenyan subsidiary of Vodafone, Safaricom in 2007 (Muthiora, 2015). Propped up by foreign venture capital, fintech companies have proliferated in the years since then. A growing number is making inroads into rural areas.
Fintech for farmers can be either business-to-person (B2P), those lending directly to farmers; or business-to-business (B2B) providing financial institutions such as banks and MFI with farmer credit scores (MercyCorps, 2017). Some firms (such as Juhudi Kilimo and Musoni) were originally microfinance institutions (MFI), which then moved into digital finance and data analytics. These firms use both conventional financial data, data related to productivity, prices, and weather and what they term ‘alternative data’ to make better-informed decisions on whether to lend and, if so, how to calculate the risk (Partnership for Finance in a Digital Africa, 2018).
In order to amplify and refine the predictive power of their algorithmic models, digital lenders are thus computing not only farmers’ behaviours but also their mobile and social media data, their psychometric data, their geospatial data and broader data about the value chains in which they operate. Over the past years, a growing number of fintech such as Farmdrive, Intelipro, Musoni have therefore partnered with existing agricultural platforms to diversify data points and expand their pool of data.
The most prominent Kenyan agricultural platform is Digifarm. By leveraging the market power of Safaricom, the parent company of M-Pesa, Digifarm has so far reached almost a million farmers and has been able to convince a variety of partner firms specialized in credit scoring, market information, credit provision and inputs supply to integrate into its system. Other platforms include Musoni and Acre Africa. Equity, a bank with a large customer base among smallholder farmers, proposes a holistic package of solutions for saving groups. Platform developers present their platforms as ideal sites for rational decision-making and therefore as perfect behavioural engineering devices to reformat farmers’ attitude to commercial agriculture. They emphasize their role in ensuring the quality of information flows pertaining to livestock and plants, inputs and credit.
At the moment, financial service providers occupy a central position in broker-driven platforms, in which tech companies collapse the intermediary steps into a single, centralized, digital platforms integrating different service providers through application programming interfaces (so-called APIs). However, they are increasingly integrated also in buyer-driven platforms, in which agribusiness use digital technologies to better coordinate the producers’ activity, digitize payments and monitor production; and in producer-driven platforms, in which grassroots farmer organisations use digital technologies to facilitate the delivery of services to their members. Embedded in these agricultural platforms fintech companies single out the unbanked farmer, classify and monitor her and, possibly, constitute her as an entrepreneurial subject, a risk-taking investor and a keen adopter of innovations.
A blurred picture: Potential risks and downsides
Framed by the proponents of digital finance as a win-win game for both lenders and borrowers, this approach to agricultural finance remains shrouded in hype. However, behind the enthusiasm, the strategies of most platform-based Kenyan fintech appear still inchoate and tentative, driven more by a vision of future profits than by a solid business case.
As Kenyan regulators have so far proven unable to catch up with digital innovations, there are risks that alternative credit scores may end up reinforcing existing forms of inequality and uneven rural development. For instance, according to a financial service provider partnering with a Kenyan agricultural platform, farmers living far from urban centres and major infrastructure typically have higher default rates. Part of the reason is that they have less access to non-farming activities. Yet in the absence of redressal mechanisms, farmers who default on even small amounts may gain bad credit scores, hindering their access to loans in future from either traditional or digital lenders. It is a paradox, and a sad one, that those supposedly most targeted by the financial inclusion agenda end up being blacklisted by the Kenyan Central Bank’s Credit Reference Bureau.
Also, credit scoring aims to turn qualitative differences into measurable, quantifiable indicators that can be read, processed, repackaged and eventually transferred through calculative infrastructures governed by financial actors. As suggested by Clapp and Isakson (2018), “creating new arenas for capital accumulation through financial investment mechanisms […] requires reformatting food and agricultural activities according to financial metrics” (450). It is probably premature to suggest that the platformization of agricultural finance in Kenya is paving the way to the financialization of local agricultural production (which, as Clapp and Isakson suggest, is advancing in North America). But, in the course of our research, we have noticed an interest in data-driven agriculture in Kenya, and in Africa in general, from hedge funds and other speculative actors (as witnessed by the authors during a closed-door workshop in Nairobi in July 2018). This interest betrays the expectation that financial practices and behaviours of smallholder farmers, and the wider socio-economic relationships underpinning the food system, could be translated into a language that speculative markets can understand and master.
Other risks are built-into the platform structure itself. Despite their claim to cut out traditional middlemen, reduce transaction costs and address information asymmetries, platform developers actually re-intermediate the market and are able to reap profits through lock-in and control over market governance (Srnicek, 2017; Schwarz, 2017; Zuboff, 2019). Constraints, design values and updates of the user terms decided by the platform’s managers are hidden transaction costs. Instead of being neutral marketplaces, as claimed by their owners, platforms embody a politics (Schwarz, 2017), controlling the rules of the game and reshaping economic relations in the process. Platform managers can exert enormous bargaining power over access to the wider market and can, therefore, pressure smaller actors into data sharing protocols that allow them to corral valuable data and determine the framework through which the data is transformed into tangible markets and assets.
It remains to be seen whether the future of agricultural finance lies in digital platforms. But, as has been the case of M-Pesa, development practitioners and firms targeting the Bottom of the Pyramid are taking note of digital innovations in Kenya in order to replicate strategies and technologies elsewhere in the Global South. Policymakers and development scholars should monitor closely.
Addison, T., Ghoshray, A. & Michalis, P., 2016. Agricultural Commodity Price Shocks and Their Effect on Growth in Sub-Saharan Africa. Journal of Agricultural Economics, 67(1), pp.47–61.
Andersson Schwarz, J., 2017. Platform Logic: An Interdisciplinary Approach to the Platform-Based Economy. Policy and Internet, 9(4), pp.374–394.
Clapp, J. & Isakson, S.R., 2018. Risky Returns: The Implications of Financialization in the Food System. Development and Change, 49(2), pp.437–460.
Demirguc-Kunt, A., Klapper L., Singer D., and Van Oudheusden, P., 2015. “The Global Findex Database 2014: Measuring Financial Inclusion around the World.” World Bank Policy Research Working Paper 7255.
Gabor, D. & Brooks, S., 2016. The digital revolution in financial inclusion: international development in the fintech era. New Political Economy, 0(6), pp.1–14.
Gitau, R. et al., 2008. Agricultural Policy-Making in Sub Saharan Africa: Kenya’s Past Policies, Tegemeo.
Mader, P., 2016. Card crusaders, cash infidels and the holy grails of digital financial inclusion. Behemoth – A Journal on Civilisation, 9(2), pp.59–81
MercyCorps. 2017. Digital Financial Services for Smallholder Farmers. What data can Financial Institutions Bank on? November.
Muthiora, B., 2015. Enabling mobile money policies in Kenya – Fostering a digital financial revolution, GSMA.
Njeru, T.N., Wainaina, P. & Onyango, K., 2017. Credit Constraints, Off-Farm Participation and Productivity; Case of Kenyan Rural Sector.
Ouma, S.A., Odongo, T.M. & Were, M., 2017. Mobile financial services and financial inclusion: Is it a boon for savings mobilization? Review of Development Finance, 7(1), pp.29–35.
Partnership for Finance in a Digital Africa, 2018. “Focus Note: Can Big Data Shape Financial Services in East Africa?” Farnham, Surrey, United Kingdom: Caribou Digital Publishing.
Schwittay, A., 2011. The financial inclusion assemblage: Subjects, technics, rationalities. Critique of Anthropology, 31(4), pp.381–401.
Srnicek, N., 2017. Platform Capitalism Polity Press: Cambridge, UK.
UNCTAD, 2015. Commodities and Development Report 2015: Smallholder Farmers and Sustainable Commodity Development. United nations conference on trade and development, pp.1–20.
Zuboff, S., 2019. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power Profile Publishing: London, UK.
Gianluca Iazzolino is a Postdoctoral Research Fellow in the International Development Department and the Firoz Lalji Centre for Africa at the London School of Economics and Political Science and Laura Mann is Assistant Professor in the Department of International Development. Photo by Neil Palmer (CIAT).
This blog post is a part of the blog series Inclusive or Exclusive Global Development? Scrutinizing Financial Inclusion, in which a new perspective on financial inclusion is published every #FinanceFriday of February, March and April 2019.