Index insurance is one of the most modern forms of insurance, tapping into the latest technological innovations, both in the use of Big Data [4] and in the measurement of parameters provided by satellites, mobile technologies, weather stations etc.
These data interconnections lead to a good global risk management in terms of underwriting, management and compensation. However, the efficiency, transparency and speed of execution cannot conceal the limits associated with the use of this form of insurance.
Index insurance is a complex product, after all
The creation of an index insurance [5] product faces many challenges, the first of which pertains to basic risk modeling. Thus, the main pitfall is in the potential gap between the modeled risk and the one actually observed in the real world.
The crucial point lies in the choice and use of adequate indices.
Index identification
| Index | Rainfall | Temperature and humidity | Wing – Power generation |
|---|---|---|---|
Compensation trigger threshold | For each period of 4 days or more during which it rains for less than 2 minutes | For each hour when the temperature is > 35° and relative humidity (1) is > 90% | If average production is below a certain threshold at the end of the month (2) |
Compensation | Number of rain-free days during these periods X Euros | X Euros | X Euros |
(1) Quantity of water vapor in a particle of air
(2) The contract is linked to the electricity production curve of the wind turbine type installed
The choice of an index that does not adequately describe the risk can lead to two situations:
- An insured receives no indemnity even though he/she suffers losses. For example, a farmer covered by insurance in case of heavy rain sees his livestock destroyed by drought. This loss cannot be paid to the farmer because the drought risk has not been underwritten.
- The reverse is also possible. An insured may receive an insurance indemnity when he does not suffer a loss.
Not all risks are objectively measurable
Index insurance is not suitable for coverage of all risks. It is not possible to measure the severity of a fire or a medical error based on a predetermined index.
Another risk excluded by parametric insurance [6] is pandemics, which are unpredictable events that cannot be parameterized in advance.
The coverage of these risks does not fall within the scope of this new form of insurance.
Data Source
The proper functioning of index insurance depends on the quality of the data used to build the product.
Free data available in "open data" is becoming more and more abundant. Unfortunately, they are not always accurate. Other more reliable data, from private organizations, are more complex to obtain because they are often considered "sensitive".
Another disadvantage is that it can be technically difficult to have sophisticated measuring equipment available in remote locations to record data such as sensors.
In addition, it is important to select trusted third parties who can provide guarantees of reliability to both the insured and the insurer.
A costly measure
Despite the many advantages of parametric insurance, the implementation of these solutions remains not only complex but sometimes costly. The additional costs are linked in particular to the efforts exerted to identify the index that would best reflect the loss of yield or income.
The availability of climatic data can be difficult, and their reliability can be questionable. Obtaining climate data can also be costly.
In the long run, open data can be a way to develop index insurance. This tool makes it easier to obtain data and therefore helps make this solution more affordable. Thus, for crop protection, data can be obtained in two ways: either by accessing observation satellites or by setting up more or less sophisticated weather stations.
The data transmitted by these systems will then be used to decide on the activation of the guarantee. It is therefore obvious that the installation of a sufficient number of weather stations and their good distribution can contribute to reduce the risk of non-indemnification.
However, adding additional equipment can have a significant cost in terms of installation and maintenance.
Technical expertise
High-level human resources are essential to develop technical expertise and allow this emerging product to flourish in the market.
The other requirement pertains to the training of specialized sales representatives and brokers with pedagogical skills to effectively market and educate potential customers.