Index insurance is a relatively new but innovative approach to insurance provision that pays out benefits on the basis of a predetermined index (e.g. rainfall level) for loss of assets and investments, primarily working capital, resulting from weather and catastrophic events. Because index insurance doesn't necessarily require the traditional services of insurance claims assessors, it allows for the claims settlement processes to be quicker and more objective.
Before the start of the insurance period, a statistical index is developed. The index measures deviations from the normal level of parameters such as rainfall, temperature, earthquake magnitude, wind speed, crop yield and livestock mortality rates.
Insurance is important for development because uninsured losses lock vulnerable populations in a vicious cycle of destitution. Unfortunately, agricultural insurance and disaster insurance are either unavailable or prohibitively expensive in many developing countries. Combined with other risk management solutions such as extension services, adequate farm management and quality farming inputs, index insurance can be an appropriate solution to overcome these obstacles.
Index insurance can be used to cover agricultural risks faced by small-scale farmers and herders (See examples on groundnut insurance in Senegal maize insurance in Benin). However, index insurance also goes beyond agriculture. In Indonesia for instance, GIIF’s implementing partner PT Reasuransi Maipark provides insurance protection for MFIs against earthquakes, so the MFIs can avoid liquidity crisis and continue to provide access to finance to microentrepreneurs after a calamity.
Index insurance can cover risks at experienced at various levels.
Micro-level index insurance covers individuals and has been implemented in countries like Senegal and Haiti.
Meso level index insurance covers “risk aggregators” such as banks, microfinance institutions, agribusinesses or national export companies and has been promoted in countries like Dominican Republic with the National Federation of Cocoa Growers. (See partner projects Kilimo Salama/Syngenta. MicroEnsure, Guy Carpenter.) Most GIIF private sector implementing partners are now providing index insurance at the meso (portfolio)-level.
Macro-level index insurance covers contingent liabilities that the Government might face in case of a disaster or a weather-related event, and has been promoted in countries like Uruguay to protect the Federal and/or Provincial budgets in years of catastrophe.
Microinsurance is the protection of low-income people against specific perils in exchange for regular premium payment proportionate to the likelihood and cost of the risks involved. This definition is exactly the same as one might use for regular insurance except for the clearly prescribed target market: low-income people. Given its focus on low-income people, microinsurance usually differs from regular insurance in terms of types of risks covered, types of delivery channels, premiums level and types of claims documentation requirements.
Microinsurance can cover a variety of risks, including death, illness, property, or crop loss. When index-insurance is sold to low-income people such as smallholder farmers (See GIIF projects with small-scale farmers in Senegal and Benin) or micro-entrepreneurs ( See GIIF projects with microentrepreneurs in Haiti, MiCRO). It often takes the form of microinsurance with business models explicitly targeting the low-income population. Sometimes, index-insurance regulations are part of the microinsurance legal and regulatory framework (See GIIF project with CIMA code).
Area-yield index insurance: Area-yield index insurance was first developed in Sweden in the early 1950s and has been implemented in India since 1979 and in the United States since 1993. With this type of insurance, the indemnity is based on the realized (harvested) average yield of an area such as a county or district. The insured yield is established as a percentage of the average yield for the area (typically 50–90 percent of the area average yield). An indemnity is paid if the realized average yield for the area is less than the insured yield, regardless of the actual yield on a policyholder’s farm. This type of index insurance requires historical area yield data on which the normal average yield and insured yield can be established. (See GIIF partner Kilimo Salama/Syngenta in Africa.)
Crop Weather index insurance: With this type of insurance, the indemnity is based on realizations of a specific weather parameter measured over a pre-specified period of time at a particular weather station or for a given satellite grid. The insurance can be structured to protect against index deviations that are expected to cause crop losses. An indemnity is paid whenever the realized value of the index exceeds or falls short of a pre-specified threshold. The indemnity is calculated based on a pre-agreed sum insured per unit of the index (for example, dollars/millimeter of rainfall). It has been commercially underwritten since 2002. (See example : Drought index-based insurance for groundnut farmers in Senegal; GIIF partners Kilimo Salama, MicroEnsure, PlaNet Guarantee.)
Normalized difference vegetation index (NDVI)/satellite index insurance: With this type of insurance, indices are constructed using time-series remote sensing imagery. For example, there are applications of false color infrared waveband to pasture index insurance, where the payout is based on a normalized difference vegetation index, which relates moisture deficit to pasture degradation. It has been applied to pasture in a few countries. (See examples: NDVI index-based insurance for Livestock (Cattle) Producers in Uruguay.)
Basis risk in index insurance arises when the index measurements do not match an individual insured’s actual losses. There are two major sources of basis risk in index insurance. One source of basis risk stems from poorly designed products and the other from geographical elements. Product design basis risk is minimized through robust product design and backed by testing of contract parameters. Geographical basis risk is a factor of the distance between the index measurement location and the production field. The greater the distance between the measurement instrument and the field, the greater the basis risk. Some households that experience loss may not receive compensation while others that experience no loss may receive payments. This basis risk is reduced when the area covered by the index is homogeneous both in terms of weather and in terms of farming techniques. Therefore, as the density of weather stations and satellite pixels is increased basis, risk is minimized.
| Advantages of Index Insurance | Disadvantages of Index Insurance |
| Adverse selection and moral hazard are minimized. The payout is based on an objective index that the farmers or insurers cannot influence. | Basis risk can arise if an individual insured’s loss experience does not correlate with the index payouts. In this case, some households that experience loss may not receive compensation while some who suffer no loss receive insurance payouts. |
| In the long term, once product structures have been standardized and most administrative processes, automated, administrative costs are reduced which offers the potential for lower premiums. For example, an insurance company does not need to conduct pre-inspections on individual farms or to assess individual grower in-field area losses, which is time-consuming and costly. In particular, transaction costs of index insurance can be significantly reduced with meso/portfolio-level approaches (eg.with microfinance institutions and agribusinesses) as opposed to micro-level direct sales to individual farmers. |
There is a lack of high quality weather and yield data in many developing countries. Ideally, 20-30 years of historical weather data is needed to allow product design teams and risk carriers to perform robust actuarial analysis and product pricing.
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| Timeliness of payouts after an event is improved, as an insurance company does not need to assess individual grower in-field area losses. This advantage is particularly true with weather station indexes and satellite indexes. | In most developing countries, there is not an enabling environment for index insurance. The GIIF Team is invested in working with government ministries and regulatory agencies to develop the requisite laws and regulations to govern the index insurance market and to allow it to grow. |
| In the early years of each market, a lot of financial and human capital is required before standardized products and systems can be developed. The products are technically complex and yet they have to be packaged in a way that is understandable by most people. Awareness-raising activities have been a sizeable component of pilot start-up costs in developing countries. |
The GIIF IFC Team has provided grants to implementing “broker” partners in the private sector globally to build index insurance markets. The GIIF WB Team has focused on creating an enabling legal and regulatory environment for index insurance, feasibility studies and pilot projects. (See GIIF projects in sub-Saharan Africa, Latin America and the Caribbean, and Asia Pacific.)
GIIF assists Governments and Regulation authorities at all stages of the legal and regulatory process. From the assessment of the current legislation, to the drafting of a new bill, GIIF legal experts provide technical assistance to Governments in order to build sustainable insurance markets in the long term. In some cases, GIIF experts also prepare regulatory and supervisory documents and train executive staff on the implementation of the new legislation. These activities can be carried out at national level (See WB-Legal and regulatory work) or at regional level (See GIIF project with CIMA code).
GIIF project partners have benefited from the experience gained with the following WB projects:
In 2003, the World Bank has provided technical assistance to the Government of India to the first weather insurance pilot in India, and in the developing world. Today, about 30 million farmers are covered with index insurance. For more information, see:
In 2005, the government of Mongolia asked the World Bank for technical assistance in the design and implementation of a pilot program for index-based livestock insurance in order to protect herders against major livestock losses caused by harsh winters. This is the first time an index insurance product has been used in Mongolia. In 2012, nearly 11,000 herder households and over 1.5 million heads of livestock were insured. For more information see: