Introduction

Smallholder farmer’s financing has seen an increasing trend over the years. Notwithstanding the significant progress, there is a huge gap in lending to agricultural enterprises especially smallholder farmers and rural SMEs. But the economics of lending to smallholder farmers requiring smaller loan sizes and operating in less developed value chains for food crops, do not add up.

In sub-Saharan Africa alone, the lending gap to agricultural SMEs is estimated at around USD 100 billion annually. Closing the USD 150 billion smallholder finance is no easy feat – but it is possible. With 450 million smallholders worldwide, key stakeholders will need to develop new solutions and scale existing ones to help close the gap.

The reality is that smallholder financing comes with inherent risks, often leading to failure for many. Moreover, organizations that provide loans or product financing to smallholder farmers in Africa are still struggling to find profitable, scalable business models².

In this article, we explore the information requirement underpinning smallholder lending for crop production. We discussed four success factors and their potential implementation, and how they could develop over time.

Loan Appraisal & Monitoring

The financial need of smallholder farmers is increasing at an increasing rate while loan defaults amongst these farmers are also increasing. Agribusinesses and other organizations providing input credit and loan facilities are concerned with the loan collector and loan repayment. With the current situation and the dire need to reverse it, lenders must be more thorough with the type of data gathered during loan appraisal and loan monitoring.

Data that provides insights into farmers’ loan history, seasonal variations, agricultural practices, field activities, farm ownership, and ability to pay can usher in a new era for smallholder financing. And lessen the risk of loan defaults, as well as encourage more participation of value chain actors.

Before you commence loan disbursement, make sure you have in place data systems to provide you with most or all the data points in the image below.
Good lending to smallholder farmers requires the collection and analysis of;

1. The farmer the loan is meant to benefit,
2. The farm in which the production will occur;
3. The commodity of focus and
4. The risk factors that could hinder production.

Automation of data collection can reduce errors, increase efficiency, and support on-spot decisions.

The Smallholder Farmer

An honest farmer repays, a dishonest farmer defaults, and an opportunistic farmer chooses whether to repay or default based on the loan appraisal and monitoring system. Evaluating farmers and their cooperative activities is crucial since their credit record, business ethics, and input need is a significant and major determinant of loan performance.

Farmer loan providers mostly collect farmer biodata, credit worthiness, production record, and group structure but given the loan amounts and the scattered smallholder farms, the verification, and validation of this information becomes an operational bottleneck.

Inputs and loans provided to smallholder farmers MUST align with the need of the farmers. Farmers that don’t believe in the use of agrochemicals tend to sell them immediately after input disbursement to local agro-dealers.

Loan recovery has been shown to do better in some smallholder communities than in others,which is majorly due to belief, culture, and socio-economic status. Also, farmers that perceive loans as national cake and or grants are not willing to repay due to their perceptions. A farmer group in a community of Jigawa state received input credit financing for 2018 wet season rice production. After all due process was followed, the rice production encountered severe flood which was insured. The farmers insisted on repaying the loan, they search for the company’s address in Kano and transported some bags of paddy rice to assure the financier they also want to share in the loss. Their loan recovery for the subsequent seasons was 100%. Another farmer group in a community of Jigawa state was financed and the production was a huge success but they refused to pay when asked why the group leader reported they did not expect the input credit will be repaid.”

The Farm

An assessment of the smallholder farms and their production history and pattern is required to ensure that field monitoring and assessment including harvest calendar are designed or adjusted to meet smallholder field activities. Smallholder financiers may also benefit from further information on the soil type, weather, and production system of the host communities to reduce the risk of field swaps and delayed or elongated harvesting periods. Financing smallholder crop production is particularly risky as the land ownership and leasing system is poor due to the inability to trace or document a farmer to specific farmland. Seasonal movement of some farmers from one farm to another compounds this problem. More than 13% of farmers change their fields after field mapping, input distribution, and or during transplanting. Also, the same farmland is used to access multiple input credits from multiple financiers for the same commodity in a season.

Projects that are after numbers, mostly make the mistake of compelling farmers to provide 1 hectare of land, this is not feasible in most cases, especially during the dry season. More than 74% of fields monitored by EXAF show that a majority of these farms have less than the hectares they received input credit for. Farmers in a community in Kano state abandoned an input credit scheme halfway due to a lack of funds to complete the production cycle. Farm clustering helped smallholder farmers access more financing through which they have reduced the risks associated with loan monitoring logistics and other issues mentioned above. Furthermore, the in-grower model of contract farming removes most of the risk associated with the farm.

Loan repayment that is based on future commodity prices compared to loans that peg price requires study before concluding as the performance varies by commodity type. A tomato out-grower program launched by a tomato processing company pegged a price during the agreement stage. The loan recovery performed badly as tomato price fluctuations were high during the harvest period. Farmer sold their tomato in the open markets and paid back their loan in cash as against in-kind.

More than 13% of farmers change their fields after field mapping, input distribution, and or during transplanting.

The Commodity

Loan default also varied by commodity type. Recently, loan default among smallholder rice farmers in Northern Nigeria increased tremendously due to the increased demand for paddy rice and increased prices.

Production activities and agronomic practices affect production activities, yield, and productivity. Spending a few Nairas to enlighten farmers on good and climate-smart techniques to meet expectations in terms of quality, price, and timing of their harvest supply, and ensures adequate yield and enough for a buyback.

Communities that practice intercropping (cereal + legume) as compared to sole cropping tends to spend more time with loan package, thus production system does not directly affect loan repayment, but it affects loan duration and input utilization.

Some pests and diseases are peculiar to communities while common diseases have different resistance levels thus the number of liters applied varies.

Inputs such as fertilizers which are used for all crops are sometimes diverted by smallholder farmers to other fields but customized fertilizers are appreciated by farmers and reduce fertilizer diversion.

Adequate input should be provided about the field size and on time especially pre-emergence chemicals and seed. More than 50% of smallholder farmers in most contract farming programs commenced nursery establishment and planting activities before seeds are distributed to them. This will affect productivity, especially knowing that most of these farmers use recycled seeds as compared to quality seeds provided to them. One of the strategies adopted by a financier to reduce loan diversion and loan default is to accept multiple commodities such as maize and soybean.

Loan repayment that is based on future commodity prices compared to loans that peg price requires study before concluding as the performance varies by commodity type. A tomato out-grower program launched by a tomato processing company pegged a price during the agreement stage. The loan recovery performed badly as tomato price fluctuations were high during the harvest period. Farmer sold their tomato in the open markets and paid back their loan in cash as against in-kind.

The Risk Factors

Nigeria and other developing countries are witnessing frequent and severe weather vagaries and increased pests and disease incidence which are beyond the control of farmers leading to financial losses. These risks, threats, and others should be documented and monitored using the risk trackers. The field monitoring applications and digital solutions support monitoring the susceptibility of fields to weather threats while its effect on loan recovery is yet to be documented.  Insurance packages added to input credit or loan package help farmers mitigate the risks they face as effectively as possible.

A participatory loan agreement between smallholder farmers and loan providers ensures that the agreement is perceived as fair and equitable for both parties. Agreement perceived to be fair by smallholder farmers performs better in terms of loan recovery, farmers that responded to not understanding the loan agreement and see this as a system brouhaha have higher tendencies to default and side sell.

Better contract enforcement and control of farmers through their cooperatives, rural leadership structure, religious leaders, and involvement of force and strong monitoring system deter farmers from defaulting while honoring the loan agreement.

Conclusion

Loans targeted at smallholder farmers suffer the problem of an information gap between smallholder farmers, farms, and financiers. The digitization of farmer loan monitoring has overcome some challenges, but its use remains limited. Over the years of tracking smallholder farmers’ loans, EXAF developed a hybrid system that relies on its FAMEX technology and frontline extension agents to bring up-to-date information to financiers and make farmer field monitoring more efficient and cost-effective. Furthermore, our farmer business advisors aggregate dispersed smallholder farmers in their communities; facilitating access to advisory services and other productive resources in order to increase and stabilize farmers’ economic well-being.

Reference

Andrianova, S., B. Baltagi, and P. Demetriades (2011). Loan defaults in Africa’ University of Leicester Discussion Paper in Economics, # 11/36

Honohan, P., and T. Beck (2007). Making Finance Work for Africa Washington, DC: The World Bank

International Finance Corporation (2014). Access to Finance for Smallholder Farmers: Learning from the Experiences of Microfinance Institutions in Latin America, The World Bank

International Finance Corporation (2019). Agricultural Lending: A How-To Guide

Patrick Honohan and Thorsten Beck (2007). Making Finance Work for Africa, The World Bank Richard L. Meyer. (2015). Financing Agriculture and Rural Areas in Sub-Saharan Africa: Progress, challenges and the way forward. IIED Working Paper. IIED, London.