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Discuss the challenges faced by insurance companies in providing insurance to smallholder farmers (25 marks).
Agricultural insurance is a major form of insurance provided by insurance companies to smallholder farmers.
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Wenner (2005) define agriculture insurance as a financing contingency that transfer production risks from the farmer to the insurer in exchange for a premium that reflects a true long term cost of the insurer assuming those risks. In addition, agricultural insurance enables farmers to stabilize their incomes (Cole et al., 2012), protect them from the impacts of crop failures, encourage farmers to adopt technologies that increase production; and it can reduce loan default risk, allowing farmers to secure more favorable credit terms (Nnadi et al., 2013).
The various types of agricultural insurance includes multiple peril crop insurance, named peril, rainfall index, livestock and aquaculture insurance, index-based insurance products and input-based insurance products (Yusuf, 2010).
Despite the various benefits provided by agricultural insurance in mitigating risks of farming, insurance companies are faced with numerous challenges in providing insurance to smallholder farmers. This is evidenced by most insurance companies globally.
Insurance companies encounter two critical information problems that is the adverse selection and moral hazard. Adverse selection is a phenomenon whereby the insured has more information about risk of loss than does the insurance company (Harwood et al., 1990). Thus, adverse selection can result in high losses and claims payments which can strain the financial capacity of insurance companies (Chen, 2011). Additionally, adverse selection makes it cumbersome or exorbitant for insurers to distinguish between high-risk and low-risk insurance applicants and therefore fail to set premiums commensurate with risk hence negatively affecting the insurer’s profitability (Wenner and Arias, 2003).
To overcome adverse selection problem, insurers will have to invest heavily in gathering information, especially on farm level yield data over long periods, in order to appropriately classify the risk (Prabhakar et al., 2015).
The other related information problem is moral hazard. Chen (2011) defines moral hazard as a subjective hazard that increases the probable frequency or severity of loss due to the risk insured and is present in all forms of insurance, and it is difficult to control (Rejda and McNamara, 2014). Moral hazard arises from the fact that farmers can take great many actions that affect their final yield (Roth and McCord, 2008). The fact of being insured creates incentives for policyholders to engage in more risky behavior and may not innovate to minimize production risks. This problem give rise to underwriting losses in the insurer’s book since monitoring the behavior of the clients requires high costs hence making the line of business unfavorable (Prabhakar et al., 2015). Insurers can substantially reduce moral hazard through innovation in the design of the crop insurance scheme. For instance, the pay-outs on index-based insurance are based on an independent and exogenous weather parameter, independent of farmer’s behavior meaning that farmers have no incentive to influence the claims thus reducing moral hazard (Levin and Reinhard, 2007).
Another critical challenge is the under-development or non-existence of formal insurance and reinsurance in developing countries (Sadati et al., 2010). Prabhakar et al (2015) assert that without reinsurance, insurers may not be able to meet the demand for agricultural insurance or may be exposed to default risk which can contribute to an inefficient agricultural insurance market performance. Failure to have access to reinsurance can make insurance companies vulnerable to catastrophic risks such as floods, storms, and hurricanes, thus in the event that risk materializes insurance companies are unable to compensate their policyholders because of limited financial capacity. To overcome this barrier, index-based insurance can be used to transfer the risk of widespread correlated agricultural production losses more easily to the international reinsurance market (Levin and Reinhard, 2007).
Moreover, fraud is another challenge faced by insurance companies. It is a deliberate misrepresentation by the policyholder, claiming that an insured event has transpired when it has not (Roth and McCord, 2008). The most common type of fraud in crop insurance is side-selling. More so, fraud is also very severe in livestock insurance where farmers have the tendency to lodge “framed” claims knowing very well that insurers can barely prove otherwise. This can strain the financial capacity of the insurance company. For instance, in the case by Burnett, cited by Roth and McCord (2008) called the “great tomato insurance fraud”. The insured threw ice over the tomato field to look like the repercussion of a hailstorm, having colluded with loss adjustors to perpetuate the fraud. Along with eight others, the insured pleaded guilty to swindling the government and insurance companies out of more than US$9 million in bogus insurance claims from 1997 to 2003. Thus fraud can be extremely cost for insurers in extreme cases and force them out of business. Therefore, Collating and sharing data at the industry level can, moreover, help to mitigate fraud, which in turn reduces the cost of insurance (USAID, 2006).
Loss assessment is a challenge for any traditional crop insurance product as indemnity is based on individual loss assessment, hence the need to mobilize large numbers of skilled or semiskilled assessors who possess some agronomic knowledge. Loss assessment can be costly and vague especially when assessing multiple claims separately due to systemic weather events such as drought or for large farms that are geographically dispersed (World Bank, 2014). Furthermore, if loss assessment is done on an individual farm basis the costs can be very large in comparison to the premium paid. To overcome this, index-based insurance can be used since it is possible to make pay-outs without field assessment thereby reducing administrative costs by eliminating the need for assessors (World Bank, 2011).
Last but not least, access to information by insurance companies can be a great challenge (Pizarro and Jama, 2008). The decision supporting tools to aid decision-makers to allocate limited resources among a range of risk management tools are limited. Likewise, the database that can be used to support assessment such as weather data to design a viable insurance product are not always available, particularly in developing countries thus a key challenge (Kapphan, 2011). Therefore, to overcome such challenge gaps need to be identified before any insurance scheme can be effectively promoted for the most vulnerable groups and the design of insurance should take into account poverty and multidimensional inequalities to enhance resilience among vulnerable communities (Prabhakar et al., 2015).
The Association of Kenya Insurers (AKI) survey (2016), asserted that agriculture insurance as a product and the implementation process of agriculture insurance has not been well understood by farmers hence this makes it challenging for insurance companies to disburse their products. Among other reason is that agricultural insurance is unattractive for many poor farmers (Fisher et al., 2012) and they view insurance as an unnecessary expense rather than an investment to curtail future risk because farmers prefer to manage their production risk through old methods such as diversified farming systems, low input utilization strategies and off-farm income (Falola et al., 2013). To address this challenge, knowledge dissemination to farmers through the media particularly through radio broadcasts and in the form of extension services will offer the prospect of increasing the awareness of the benefits of agricultural insurance hence this could increase the participation rate (Ellis, 2016).
In conclusion, marketing and education should be run throughout the year, with a focus on different themes, to build knowledge and value for agriculture insurance as well as addressing the challenges mentioned above.
AKI (2016), Association of Kenya Insurers (2016). Situational analysis of agriculture insurance landscape in Kenya
Chen, Y. (2011). Weather Index-Based Rice Insurance: A pilot study of nine villages in Zhejiang Province, China. Swiss Federal Institute of Technology, Zurich.
Cole, S. A., Gine, X., Tobacman, J., Topalova, P. B., Townsend, R. M., Vickery, J. I. (2012).Barriers to household risk management: Evidence from India. Journal of AppliedEconomics, 5(1):104–135.
Ellis, E. (2016). Farmers Willingness to Pay for Crop Insurance: Evidence from EasternGhana
Falola, A., A.E. Ayinde and B.O. Agboola. (2013). Willingness to Take Agricultural Insuranceby Cocoa Farmers in Nigeria. International Journal of Food and Agricultural Economics1(1): 97-107
Fisher M, Cook S, Laderach P, Lundy M (2012). Weather Indices for Designing Micro-Insurance. Products for Small-Holder Farmers in the Tropics.
Harwood, J., Heifner, R., Coble, K., Perry, J., Somwaru, A. (1990) “Managing Risk inFarming: Concepts, Research, and Analysis” USDA/Economic Research Service,Washington, DC
Kapphan, I. (2011). Optimal weather insurance design- a quantitative exploration. Paper presented at modeling and simulation society of Australia and New Zealand, MSSANZ. Perth, May 2011
Levin, T. and Reinhard, D. (2007) Microinsurance Aspects in Agriculture insurance, Munich:Munich Re. Foundation
Nnadi, F. N., Chikaire, J., Atoma, C. N., Ihenacho, R. A., Umunnakwe, P. C., and Utazi, C. O. (2013). Agricultural insurance : A strategic tool for climate change adaptation in theagricultural sector. Net Journal of Agricultural Science, 1:1–9.
Rejda G. E., and McNamara M. J., (2014). Principles of risk management and insurance. 12th edition.
Roth, J. and McCord, M. (2008). Agricultural Insurance Global Practices and Prospects
Sadati SA, Ghobsdi FR, Mohamadi Y, Sharifi O, Asakereh A (2010). Survey of effective factors on adoption of crop insurance among farmers: A case study of Behbahan County. African Journal of Agriculture Research, 5(16), pp: 2237-2242.
Sivapuram V.R.K. Prabhakar. (2015). Effectiveness of Insurance for Disaster Risk Reduction and Climate Change Adaptation: Challenges and Opportunities Institute for Global Environmental Strategies
The World Bank (2011). Weather index insurance for agriculture: Guidance for developmentpractitioners. Agriculture and Rural Development Discussion paper 50. Washington, DC: The World Bank
The World Bank (2014). Agriculture and Rural Development.
UNCTAD (1994). Agricultural Insurance in Developing Countries. United Nations Conference report on Trade and Development (UNCTAD), New York.Wenner, M. (2005) Agricultural Insurance Revisited: New Developments and Perspectives inLatin America and the Caribbean. Washington, DC: Inter-American Development Bank.
USAID, (2006). Assessment on How Strengthening the Insurance Industry in Developing Countries Contributes to Economic Growth, publication produced by Chemonics International Inc. for review by the United States Agency for International Development
Wenner, M. (2005). Agricultural Insurance Revisited: New Developments and Perspectives inLatin America and the Caribbean. Washington, DC: Inter-American Development Bank Province, China. Swiss Federal Institute of Technology, Zurich
Yusuf, K. K. (2010). Insurance Options in Risk Management in Agriculture Finance. Beingthe full text of paper presented on the occasion of the AFRACA Conference in Abuja.
Delivering Insurance to Smallholder Farmers. (2020, Sep 23). Retrieved from https://studymoose.com/delivering-insurance-to-smallholder-farmers-essay
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