When claims are adjusted automatically

The basic principle of parametric insurance is relatively simple: the insurer adjusts claims based not on information provided by the policy holder after the fact, but rather on information available directly when the damage occurred. The adjustment is therefore calculated from verified measured values for certain parameters which were defined previously. In a conventional weather or natural disaster insurance policy, for example, the temperature, magnitude of the earthquake, size of the hailstones or the flood water levels may be set out as parameters to be used in the adjustment process in the event of a claim.

Evolution of the transfer of risk

‘The potential in terms of efficiency is obvious,’ says Manuel Zimmermann, Beyond Insurance Manager at Funk. ‘It’s even more exciting to consider what other insurance products could be implemented as parametric solutions and how existing data sources can be combined with new technology.’ So far, parametric insurance solutions have often lagged behind the high expectations of both insurers and policy holders. Nevertheless, the increasing digitisation of industry and economy could now bring about an evolution of risk transfer mechanisms. After all, there is an increasing number of potentially suitable parameters available thanks to sensors and other state-of-the-art technology especially in factories and on modern machinery and large-scale systems. These parameters could be used to implement parametric solutions in machine breakdown insurance, for example. The prerequisites for new product developments in this area are met through three specific technological disciplines:

1. Sensors: a digital reflection of the actual damage

Extensive use of low-cost sensors and the development of powerful multi-sensors make it easier to record a number of real-world status data in digital systems. The key words ‘digital shadow’ and ‘digital twin’ outline the aim of this development: to create a perfect digital image of the physical world. ‘All insurance-relevant damage becomes noticeable in a change of states, which can then be seen in the data flows in a corresponding digital environment,’ explains Manuel Zimmermann. ‘This makes implementing parametric solutions in some insurance contexts fundamentally conceivable.’

2. Artificial intelligence: data patterns as a basis for new solutions

With computer processor performance continuously growing, ever more powerful algorithms and new methods of data analysis are able to be put to practical use. They make it possible to analyse large amounts of unstructured data – ‘big data’ – and integrate volatile real-time data in historical datasets. This means that the key requirement of parametric insurance is met: it must be ensured that insurance-relevant events are reflected as specific patterns in recorded data flows. With weather insurance up until now, it was adequate to refer to individual data types, such as local precipitation per unit of time, in order to establish a sufficiently high correlation between the data and the damage. ‘In the industrial environment, when we look at insurance-relevant machine damage, for example, significantly more parameters are needed,’ emphasises Dr Alexander Skorna, Head of Business Development at Funk. ‘But thanks to the Internet of Things, or IoT for short, these parameters are available and can be used by companies.’

However, the technological requirements are not just limited to being able to reliably identify the occurrence of damage in data flows. In order to calculate appropriate premiums for parametric insurance policies, an exact correlation of the claim amount with specific parameter configurations is required. This is where historical data and the use of artificial intelligence (AI) are becoming more relevant, as they are used to link different types of damage from past experience to representative claim amounts. As Dr Alexander Skorna says, ‘This overall look at patterns in the recorded data, with indicated damage and the resulting claim amounts, makes it possible to map out the insurance process ‘end-to-end’ using modern technology.’

3. Blockchain: transparency and trust using digital seals

Last but not least, progress with blockchain is also helping to open up new practical potential in parametric insurance solutions. Blockchain’s main contribution is that it builds trust between the different players involved: the policy holder, insurance broker and risk carrier. Unlike with weather insurance, insurance-relevant trigger parameters in machinery cannot be measured by an independent third party that provides the data with no influence from outside sources. More often than not, the sensors responsible for measuring the trigger parameters are located directly on the insured objects, such as the production system, and therefore can be easily accessed by the policy holder. From the risk carrier’s point of view, the authenticity of the data may come into question when it ultimately results in an automatic claim payout. This is where blockchain solutions come in. ‘By sealing the measured values directly on the IoT device, such as a smart sensor, it makes an undetected retroactive change impossible,’ explains Manuel Zimmermann. All values are instead made immediately available to everyone involved via a cloud architecture. As a result, if damage occurs the risk carrier can validate the data automatically.
 

A worthy investment

Practical parametric insurance solutions based on innovative IoT-based triggers are very time-intensive at their first inception. Product development and underwriting of conventional policies are much more straightforward, comparably. However, once the insurance contract has been hammered out and signed, the insurance process in the event of a claim becomes much easier compared to conventional procedures. 

While normally after a loss event a great deal of effort is expended by several parties to settle it, all necessary processes run automatically within the framework of parametric concepts. Funk has therefore set itself the goal of identifying suitable use cases in various industries and insurance sectors for which parametric solutions are both scalable and transferable with manageable adaptations. 

A wide variety of sensor systems and other basic components of IoT are inexorably finding their way into the process landscapes of policy holders - with or without the intervention of the insurance industry. Applications from the field of artificial intelligence are also becoming increasingly controllable and are being made available to a wide range of companies via specialised suppliers. In this way, they can be used as a building block of digital transformation and instrumentalised for the further development of the company's own business model. This constellation represents an optimal starting position for the development of innovative approaches in the form of parametric insurance solutions. In this way, the players in the insurance industry can continue to build on their original core competencies without closing their eyes to digitisation.

16 September 2020