Nigeria’s financial services sector is failing to meet the needs of the single most important group in its agricultural value chain and perhaps the entire economy: smallholders.
Globally, smallholders manage over 60 per cent of the world’s estimated 500 million small farms and provide over 80 per cent of the food consumed in a significant part of the developing world.
While many public and private sector players agree on the importance of developing agricultural value chains, there is under-investment in the challenges facing smallholders in the SME agrifood sector. Over per cent of sub-Saharan Africa’s 48 million smallholder farmers lack access to formal credit.
Issues like affordable access to finance, low levels of productivity and regulatory burdens still loom large, further restricting the ability of many smallholders to grow from micro to small businesses, and from small to medium businesses.
These challenges are more pronounced when we consider that smallholders in Nigeria, who like most countries, make up the highest number of informally employed people. Most of their activities are in small and undocumented transactions — attributes that make it challenging to design affordable financial services, source high-quality inputs and develop best-practices in agronomy to meet their needs.
Thus, their lack of access, especially to financial products like loans and insurance, hugely affects their capacity for scale and chances of moving from subsistence farming to more mechanised and modern farming techniques.
So why are financial inclusion initiatives not addressing the needs of smallholders? The answer is simple: little is known about their transaction history. Therefore, it is difficult to estimate their creditworthiness, and by extension, design appropriate risk-adjusted products and services.
The Identity glitch
Looking specifically at one of the most crucial financial products, loans, we can see that two things determine the outcome of any application—first, up-to-date data on the prospective borrower and second, well-tested credit scoring processes that determine creditworthiness. Today, Nigeria does not have the aggregated data records needed to produce credit histories for prospective borrowers.
When Financial Service Providers (FSP) know their customers, they can put them in specific cohorts and price their products accordingly. Typically, less creditworthy borrowers have a higher cost of capital and risk. For example, the Central Bank of Nigeria (CBN) reported that a specific bank’s interest rate for the most creditworthy borrowers (prime lending rate) for agriculture, forestry and fishing was 6 per cent. However, the same publication reported the highest lending rate for the same industry in the same bank as 36 per cent.
As most smallholders do not have a means of proving immutable identity or a financial footprint, it is difficult to access information necessary that allows lenders to evaluate their creditworthiness and design low-cost financing solutions for them. Without this data, it becomes quite costly and unattractive for loan providers to develop accurate pricing and risk assessment models for these customers. Consequently, loan providers mitigate their risks either by refusing to lend to them at all or charging them punitive interest rates, up to 45.5 per cent in some cases.
In the end, these smallholders face a catch-22 scenario: FSPs refuse to lend to them because they have limited credit histories, and they are unable to build credit histories because they are excluded from the financial system. This unfortunately, contributes to the inverse multiplier effect of making smallholders poorer by shutting them out of the formal financial services ecosystem.
However, this information gap creates an opportunity. Conventional risk assessment models like the American FICO system and the 5 Cs approach (Character, Cashflow, Condition, Capital and Collateral) require borrowers to fulfil standard conditions to be granted a loan. But, if the financial system is going to build truly scalable models for financing underserved market segments, then we need more diversified sets of data to determine creditworthiness, including information not covered in standard credit reports (alternative data) or non financial data in general.
This is where innovative data-driven players like FarmDrive come in. FarmDrive generates real-time credit reports for small farmers, allowing them to access loans from financial institutions and agricultural input providers via their mobile phones. FarmDrive collects expense and revenue data from farmers via SMS and combines it with satellite imaging, remote sensing technology and alternative data points (e.g., soil analysis, weather forecasts), to create detailed yield estimates and assess credit risk.
When the financial institutions can view comprehensive profiles of a farmer’s economic performance, they are more likely to approve loans.
Gone are the days of a loan repayment history being the only way to determine how creditworthy a borrower is. After all, a previous loan is a lagging indicator (meaning that it can tell you whether the borrower had a high credit risk in the past) but what is needed are leading indicators that predict whether or not the borrower will repay in the future.