The topic of this article today will be special. Not only because I'm going to go through an insurance solution but also because it is a less-known topic even among insurance solutions. Today's topic is parametric insurance, also known as index insurance. Their specificity lies in the fact that in the case of these insurances, both the amount of the claim and the event that triggers it are precisely defined in advance. Well, isn’t that the case with all insurance?
Not necessarily, if you think about it, if you have home insurance and a water pipe breaks in your house and dampens your living room after you have reported the damage to your insurer, they will send an adjuster to determine what kind of damage you have and how much and will pay you on that basis. So the difference between traditional insurance and parametric insurance is that with parametric insurance, there is no need for an individual damage assessment, as only the occurrence of a predetermined damage event needs to be detected so the claims process can be completed quickly and cost-effectively.
So in parametric insurance, all we have to do is validate the occurrence of claims, nothing could be simpler, you might think, but the reality is that there are many pitfalls here too. As with an accurate assessment of the damage, it takes a lot of work to validate the occurrence of a claim. But let's look at this through examples, parametric insurance is most commonly used in the agricultural industry and in natural disasters. For farmers, it can be a great help if they can access compensation quickly and if some of the financial losses due to lost production can be covered immediately. In order to detect the event that caused it, in addition to the farmer declaring it, we need real data, which could be weather data from different providers, satellite images, or an IoT device placed on the farmer's field that continuously monitors the temperature or detects rising inland water.
So one of the most important pillars of parametric insurance is data. However, this alone is not enough, as more precise qualitative data is needed to establish the occurrence of a loss event clearly. A solution may be to use several different data sources that compare and validate the data to determine the final outcome. I can give you a concrete example from my own, as we develop parametric insurance solutions at Insurwiz. In our case, we insure travelers' flights, so if the insured's flight is delayed or canceled, we immediately initiate the compensation within 24 hours. We believe that such an inconvenience can be quite annoying for the traveler and we surely can help to alleviate this with such financial assistance. Use the compensation for a late-night taxi from the airport or an extra day's hotel booking.
In our solution, of course, the most important thing is that our system detects immediately if something has happened to the policyholder’s flight, but our experience is that one data source is not enough, it can happen at any time that we don't receive data in time or at all. Therefore, we need more data sources, but in this case, validation can be a problem. It is best if there are at least three or more data sources available to investigate an event, in our case this means 8 data sources, which our system constantly compares and makes the decision on compensation on the basis of these data sources without any indication from the customer.
I've gotten this question a few times because it's like putting some money on red in roulette and if it comes up, I can get a nice payout. Hence I would definitely not consider it gambling, as in every insurance case, the policyholder, unfortunately, suffers damage, which the insurer can mitigate. On the other hand, we could say the same for all insurance policies, because if we had enough data, we could accurately predict the amount of damage and the amount of compensation. Of course, this is science fiction, but if, for example, in the event of a leak caused by a burst water pipe, the insurer already had all the necessary data of the insured home and could model and detect the leak using IoT tools, the whole process could be automated without any administration or manual work.
So why is parametric insurance useful for customers? Well, in a nutshell, because there is NO need for any manual claims reporting, the entire claims process can be automated and the process can be completely transparent, as all the conditions need to be specified in the policy. For the insured, it is a convenient and reliable service and for insurers, it can help reduce the cost of claims assessment and facilitate the provision of new coverages.
In addition, the world is going digital by leaps and bounds, more and more data is available in real-time, wearable devices, our online presence and IoT devices can all help to ensure that more and more parametric insurance will provide safety for customers in the future.
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