Annalisa BIANCHESSI, of the Microinsurance Network, opened the session by stressing why African agriculture needs transformation: it employs two thirds of the African population, mostly risk-averse smallholders with diverse livelihoods. How can financial services, and in particular insurance, serve as a vehicle of transformation? She shortly introduced the panel, and highlighted that the panellists' organisations have formed a partnership that has led to the development of an innovative model to achieve just that: transformation in African agriculture.
Stewart MCCULLOCH, from VisionFund International, introduced the innovative model: it combines insurance with credit and capacity building; brings in insurance tools at the micro and meso levels; and addresses both portfolio and client level risks.
He then took one step back, stressing that farmers are smart in how they deal with risks and financial resources in their specific context. As such, their diversified livelihoods make sense. Getting out of poverty, however, means investing, making choices and thereby concentrating on activities which generate higher incomes. Concentration of activities however, also means concentration of risk. It is here that insurance can play a transformative role. He explained it as theory of change. Taking away, or minimising risk, can encourage farmers to invest and increase their income, and can also encourage financial institutions to lend and partner with aggregation ventures where risks are concentrated (for example, due to a focus on a single or limited number of products and sectors). Different solutions are combined to address risks efficiently at these levels: offering good insurance products at the micro level that adequately and quickly handle pay-outs, while portfolios with concentrated risks are protected against major disasters at the meso level.
Emily WHITE, of Global Parametrics, provided further insights into the meso-level. She described Global Parametrics as a for-profit social enterprise combining science and finance to improve disaster resilience of MFIs. In terms of science, parametric triggers link insurance pay-outs and credit drawdowns to the physical strength of a disaster at relevant locations, and the exposure of an MFI's portfolio to such a disaster. The financial response by the overall system, including from the National Disaster Fund, managed by Global Parametrics as part of the innovative model, can thus be rapid, even before the disaster triggers loan write-downs, capital erosion and a resulting decrease in lending. The response from the overall system is in the form of an insurance pay-out from the Natural Disaster Fund, transformed ultimately into a capital injection for MFIs, as well as a liquidity response in the form of a contingent credit facility from third-party Blue Orchard, triggered using Global Parametrics's disaster indices, to facilitate recovery lending by the institutions. McCulloch stressed the importance of this scheme, as it allows the MFI to continue doing business and serve affected households during their recovery instead of pulling out due to capital and liquidity constraints.
Olga SPECKHARDT, from the Syngenta Foundation for Sustainable Agriculture, further explained how the model is working in embedding the index based insurance solutions into microloans for improved inputs (seeds, fertilisers). She added that loans also act as an ideal distribution network, not only of the product but also of training and awareness-raising to farmers. McCulloch added that this makes the product more attractive to the farmer, as they see insurance as an input like fertiliser that protects their crop.
Regarding a question from Bianchessi on how this innovation is different from other index insurance schemes, White stressed that the scheme is applied at the meso-level, for MFIs rather than directly to their customers, and is parametric; it models what happens physically (for example, using soil moisture to indicate emerging drought conditions) while considering this in close relation to the growing season. Parametric insurance can provide a quick response, but it doesn't perfectly capture loss experience as it uses a proxy (the physical hazard) for what is happening on the ground. The schemes perform effectively at the meso-level, rather than when applied to the experience of individual farmers, as they are better at capturing the experience across a portfolio, and also where they can be used to determine when to shore up the balance sheet of an exposed MFI with a well-timed injection of capital.
Bianchessi then asked Speckhardt to explain how the model was able to achieve such high increases in incomes through insurance. Speckhardt indicated that we need to approach farmers in the right way. They are excellent risk managers and do not need weather-based insurance; what they want is their harvest to be stable. That is why the programme's combination of agricultural support (training on farming techniques to increase yields), credit (e.g. for better inputs) and climate insurance works well in reaching scale and changing ecosystems. However, this requires both good partnerships (for example, with insurance companies), the necessary regulatory support to scale up distribution channels, but in particular technology and better information.
A first question from the audience brought the discussion to how the model builds on local safety net systems and how it addresses low-cost behaviour changes that can impact risk, such as improved soil management. McCulloch stressed that it builds on local practices both in terms of insurance as well as agricultural practices. Insurance is a last resort. White added that insurance is not a silver bullet, but can cover for large shocks which will overwhelm traditional coping mechanisms. Speckhardt agreed and added that optimisation of agricultural practices is needed, both as local risk mitigating solutions to ensure insurance costs remain manageable, but also to increase yields and directly benefit the farmer.
Based on questions around costs, price and amounts of pay-outs, White indicated that the Natural Disaster Fund is capitalised by the UK government, through the Department for International Development. The way the products are structured allows the fund to respond in a flexible way to different impacts, in terms of determining a useful amount to inject. The cost of access to the financial system depends on how much cover MFIs wish to purchase, and is calculated using historical data on probability of occurrence of hazard conditions and on how timing (for example, during the growing season) and severity of the occurrence affect impact and ultimately the index against which pay-outs are made. This also allows the coverage to be focused on the part of the year when the risk occurs. McCulloch also indicated that the client is responsible for the payment, emphasising that the low cost per month has not been considered an issue for clients.
Regarding product design and its applicability to female farmers, Speckhardt answered that it all depends on good data. Better data can make products more affordable. She also stressed the opportunities offered by FinTech, for example in bringing down prices, faster distribution and fast pay-outs. Moreover, competition is needed among insurers at the micro and meso level. She also added that the model addresses any type of farmer, no matter whether they are men producing cash crops or are women producing subsistence crops, as it shores up the MFI to continue lending to them.