Big data could mean big opportunity: Why we should stay excited for data analytics in smallholder finance
This brief (PDF), by the Mastercard Foundation and Rural and Agriculture Finance Learning Lab, aims to provide a high level understanding of how data analytics is used for smallholder farmers, introduce a new framework to understand the economics of data analytic investments, and highlight key innovators in the space. The gap in smallholder financing remains wide and financial institutions by and large continue to find smallholders farmers a difficult and cost segment to serve. The authors of the brief believe there are ways to transform the underlying economics to serve farmers profitably and at scale – and that data and technology could be fundamental drivers of this shift. On one hand, the progress made is encouraging: the use of data analytics for credit scoring is maturing, and other use cases are emerging, the value proposition for financial service providers (FSPs) seems compelling, there is better insight into what data is useful and what is not, and the interest and investment in the sector remains healthy. However, the use of data analytics to expand access to credit for smallholders is still in its infancy. Outstanding questions center on proving the nature and strength of the business case for FSPs to invest in data analytics; how FSPs can build the capabilities they need to leverage data analytics effectively and; how FSPs can gain access to useful data at a reasonable cost. The best way to advance this field is for FSPs and data service providers (DSPs) to work together on a commercial scale to prove the business case and develop blueprints of success. DSPs are actively innovating and FSPs are beginning to buy into the potential. Smartly deployed philanthropic funding can reduce cost and risk and help to mobilize private sector players.