User:Zzqqskqpe/Index-based insurance

Justification for index-based insurance
Insuring risk in small-scale agriculture faces particular problems that are not usually encountered by the broader insurance sector. Production relies on natural conditions, such as rain, temperature, and sunlight, which cannot be controlled easily by poorer farmers, other than by those with access to irrigation or plastic tunnels in the case of horticultural crops. Consequently farmers face problems on a regular basis. Unlike other insurance, adverse events cannot easily be predicted statistically, large numbers of people tend to be affected at the same time (known as "concurrency" by the insurance industry) and losses for each of them tend to be significant. The opposite is the case for more traditional insurance such as home theft insurance, where actuaries can make a good forecast of the likely incidence of claims, thefts are (relatively) rare, all the houses on a block are not entered at the same time, and entire contents of a house are not usually stolen.

Traditional insurance has two cost categories. First is the underlying risk that is being insured and, second, the costs involved in operating the insurance, such as carrying out individual risk assessments and loss adjustments. In the agricultural sector these costs tend to be high and premiums are often unaffordable for most poorer farmers. The fixed costs of loss verification make it uneconomic to investigate losses for small-scale agriculture producers whose total insurance premiums are small. In practice, this can lead to poor loss verification, morally hazardous behavior and high loss ratios for insurance companies.

In theory, index-based insurance can cover many farmers while avoiding the need for loss assessment and adjustment. This can reduce some administrative and implementation costs, and also has the potential to limit payouts caused by fraud or poor farming practices.

Index-based insurance in practice
There are considerable challenges that must be overcome to effectively service farmers in remote areas. The lack of historical rainfall data, yield data, or information on livestock mortality has complicated the development of indices, while the small size of farms, low value of crops or animals to be insured, and high costs of operation have made it difficult to design a workable scheme. Offsetting that, ICTs, particularly smartphones, are reducing costs, while increasing use of satellite measurements for the purposes of index development has also been effective.

Index-based insurance does not always provide farmers with indemnities when they experience crop or animal losses and the indemnity payments sometimes do not accurately reflect the size of the losses they experience. This is because an index is based on a geographical area within which farmers may have different experiences with, e.g., rainfall. As a consequence some farmers may achieve a good crop when most others in the area experience a crop failure. However, under an index-based system all farmers receive payouts. This problem has become known as "basis risk", where farmers with good yields are given payouts and farmers with bad yields aren't. As a direct consequence of basis risk, farmers are usually reluctant to pay the same premiums for index-based insurance that they would for standard insurance. Reducing basis risk by incorporating newly upcoming data sources is of central interest in current research. One emerging method of mitigating basis risk is by crafting indices that track indicators of yield and not only weather intensity.