How technological development and big data can improve the resilience of companies to natural disasters. Parametric insurance is establishing itself as an alternative to covering natural catastrophe. Swiss Re reports!

The demand for parametric insurance policies is growing, last but not least because their benefits go beyond weather-related events. From the Internet of Things, automation and sensors, to artificial intelligence and big data to smart data, the business world is technologically more advanced than ever before.
Existing systems and supply chains are digitised, production facilities are becoming automated, and factories and microchip sensors are starting to predict maintenance requirements and potential breakdowns before they occur.

All this technology generates a lot of data – big data – that can offer great insights into the next major risk event. And insurers are making this data the focus of their innovative risk solutions so that their clients can be more resistant to diverse risks such as climate, weather and natural disasters.

Wind risk as an example

Let us take a practical example. An energy supply company in Europe classifies winter storms as a major risk to its power lines. Strong winds may not only cause direct damage to the distribution network, but also uproot whole trees or break off branches which then fall onto the (power) lines.

The client was searching for efficient protection for its nationwide low-voltage distribution network. The risks for power lines were practically not insurable with traditional insurance solutions. The client was also keen to avoid any uncertainties with claims processing (due to it being difficult to estimate the costs for the reconstruction and upgrading of the network) and to ensure that quick payment was made in the event of a claim.

The parametric insurance solution enabled the client’s wind risk to be covered. An index was developed in close cooperation with the client, which describes the damage as a function of the measured peak wind speeds. As the wind data is calculated independently and is available quickly, the client can expect the claim to be dealt with fast and simply in the event of an incident.

As there are sometimes large sums of money at stake, many industries are actively looking for more innovative risk transfer options to protect themselves against the increasing threat caused by weather-related damage.

Technology and data are a considerable part of the solution here. Weather stations and measuring instruments provide clear and independent information on wind conditions. Along with the historic data from these measuring stations, the information is structured as a customised payment formula in order to depict the underlying risk in the best possible way.

The data from the measuring stations is aligned with predefined triggers determined in cooperation with the client in order to define the time and amount of the payment.

The advantages

There are three main advantages to parametric insurance.

  1. Parametric insurance policies are a simplified and more transparent version of traditional insurance policies, as fixed payments are made if the measured data (e.g. wind speeds, water levels, soil accelerations) reach or exceed critical threshold values. Parametric insurance policies are therefore geared towards the incident and not the actual loss.
  2. Another advantage is the quick payment of claims. It often takes months or even years with a traditional insurance policy until claims resulting from business interruptions (BI) are settled, as the loss must be analysed and confirmed before a payout is agreed. A parametric insurance policy reduces the steps to payment of the claim. On-site visits no longer have to be made and forensic examinations and claims settlements no longer have to be completed before a claim is paid. If the insurance trigger is activated, the payment will be made in a few days without delay.
  3. The certainty of compensation is also advantageous. There are often uncertainties with traditional insurance policies: you sometimes only know how high the insurance cover is once a loss situation has been examined. There may also be disputes about the amounts. Parametric insurance policies put an end to these uncertainties, as all payments are agreed in advance and are therefore fixed. The payments can be used to cover all direct and indirect costs incurred as a result of the insured event.

Parametric natural disaster cover may also make sense in addition to or for the restructuring of property programmes, as these risks to individual exposed locations can be systematically “outsourced” and covered. High limits for individual locations and rapid compensation in the event of a loss that guarantee liquidity, can offer great added value in sectors such as Construction, Energy, Automotive, Transport & Logistics, among others.

Outlook: extending triggers

Despite the fact that the solution is typically applied to weather-related events (to improve resistance to climate risks), we are starting to discuss how we can also apply the principle of parametric insurance to other risks.

AI, IoT, sensors, automation. All these components generate so much data on all risks in all industries, from machine failures to business interruptions without physical damage, that it is only a question of time before an agreement is reached on triggers from sensor data for risks which go beyond weather events and natural disasters.

As long as we can ensure that data is collected objectively, independently and reliably, we can develop parametric insurance policies for many complex risk situations.
The future for parametric insurance policies is indeed bright and is continuously expanding with new data that can be collected and analysed systematically.

Tanja Dippel
Customer & Distribution
Manager Austria,
Swiss Re Corporate Solutions
T +49 89 38441024
tanja_dippel@swissre.com

Jan Bachmann
Head Innovative Risk Solutions
EMEA
T +41 43 285 21 42
jan_bachmann@swissre.com

Martin Hotz
Head Parametric NatCat
T+41 43 285 68 57
martin_hotz@swissre.com
Swiss Re Group

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