Filling Data Gaps in Smallholder Finance
Understanding the relationship between smallholder households and access to financial services is not a simple task. Only recently has it been possible to quantify how many small farms and family farms are actually in operation around the world. There is still very little available data on the characteristics of smallholder farmers’ financial needs.
The IMF’s Financial Access Survey provides data on the general supply of financial services at the national level, which allows us to make comparisons between countries. However, the complex realities within each country are quite varied and it is subnational data that gives us a clear picture of the financial inclusion challenges within a particular territory.
To address this gap, MIX launched FINclusionLab, which combines information on supply and demand for financial services in 16 countries with socioeconomic characteristics of the population. Among the datasets currently included in FINclusionLab are some initial clues about the relationship between financial services and smallholder farmers. At a basic level, we know that most potential demand for the financial products and services suited to smallholders (such as pre-planting loans for the purchase of fertilizer) is located in rural areas, zones already well-known as underserved in terms of financial access. Gathering data on the distribution of the population living in rural areas allows us to observe, for example, that in Peru the banking correspondent or agent model has paved the way for an expanded presence of financial institutions in districts with a higher proportion of rural population. Similarly, data on the economically-active population engaged in agricultural activities shows which providers already have greater presence in zones where agriculture plays a major economic role.
Of course, smallholder families are not homogenous and different segments of this group present specific challenges for financial service providers. In this sense, CGAP’s work on segmenting smallholder households is tremendously useful as we look to understand the characteristics of potential demand. Surveys are useful instruments to learn about the needs of smallholders. FINclusionLab includes some data from the Living Standards Measurement Study-Integrated Surveys on Agriculture and from Finscope, which offers a detailed look at demand. The national surveys now underway at CGAP in Mozambique and Tanzania will soon give us even more information.
In an effort to structure available data and enhance its potential utility, the MIX, together with MicroSave, has developed a framework for collecting data on smallholders and agricultural finance. Using the farming household as the unit of analysis, the framework connects data on access to agriculture finance with contextual data from the agriculture sector, examines both quantity- and quality-related issues, and includes 17 specific indicators (both supply- and demand-side) categorized by five parameters (see the table below).
Agricultural Framework Parameters and Indicators
Financial service providers and other stakeholders can use this framework to quantify the state of smallholder finance in their countries, assess demand for financial services, and design appropriate products and services for smallholder clients. Because the parameters included are only related to the agriculture sector, it will be important to look at the data gleaned through the framework in relation to overall financial inclusion data as well.
The MIX has also launched a campaign to gather data on agricultural and smallholder finance. Although there are inherent constraints due to the scarcity of available information, the agricultural finance data framework has the potential to provide a more complete picture of the number of smallholder families with access to credit and insurance products, as well as the distribution of credit among different categories of smallholders. To kick off the campaign, the MIX is collecting data from five Indian states: Andhra Pradesh, Jharkand, Karnataka, Odisha and Uttarakhand. Results of this initial effort will be published via FINclusionLab in the form of maps, charts and other customizable visualizations. Ultimately, the project hopes to contribute to the broader effort to better understand and serve smallholders, identifying gaps in financial services for these potential clients and providing the data necessary to fill those gaps.
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