It solutions for telematics tariffs: via central ‘data hub for sensor data’ to valuable information

It solutions for telematics tariffs: via central 'data hub for sensor data' to valuable information

The use of telematics fundamentally changes business processes at insurers. For example, individual sensor data is enabling a whole new way of assessing risks and setting premiums. The use of real-time data even turns the traditional role of insurance as a claims adjuster on its head. In the future, insurance companies will be able to participate more proactively in loss prevention by helping policyholders to avoid loss-triggering events or to identify them at an early stage so that they can take the appropriate countermeasures in good time. IT takes center stage: Ralf Kufner provides some valuable tips here.

by Ralf Kufner, Associate Partner Infosys Consulting

I n car insurance, it's already a reality: While classic insurance models rely on general statistical assessment factors, here individual sensor data on the driving style and habits of the car owner form the basis for the insurance premium. Among other things, information on speed, acceleration and braking behavior as well as the time of day and type of road are evaluated for this purpose. Prudent drivers can expect a discount from their insurance company.

In the long term, other insurance sectors will also use this data-driven approach."

This would be possible in healthcare, for example, with wearables that collect detailed information about activity and bodily functions such as heart rate. These could also be used as an early warning system for patients at risk and ensure immediate treatment by the emergency physician in life-threatening situations. The same is true for homeowners and buildings insurance. For example, insurance companies could offer personalized discounts to customers who install networked security systems, statistically reducing the likelihood that a costly claim will occur.

Three-tier IT infrastructure conquers telematics data mountains

Common to all telematics insurance is the large amount of data that needs to be collected and evaluated from various sources. To achieve this, insurers need a comprehensive IT strategy that supports them with three core elements.

The first architecture layer is for flexible data collection. Because data sources keep changing in the course of business development, the insurance IT strategy must be designed in a scalable hub-and-spoke configuration.

The second layer is the data staging area. Insurance companies must assume that data they receive from telematics "black boxes" is not all in consistent formats. That's why they need a standardized data hub, supported by translation middleware. The middleware layer allows incoming data in formats such as XML to be broken down to its basic data elements via appropriate interfaces. They are then loaded into the Data Hub in a common format where they can be tagged and categorized accordingly.

The final element is the external communications network. Put simply, data collected from devices and people and put into a standardized format needs to be shared with third parties in a way that meets individual data needs. Third parties can be, for example, internal systems such as operational ERP, core legacy, CRM and sales systems, or external partners such as auto repair shops or home protection companies for real estate telematics. By architecting a system with the central data hub, companies can ensure that new data sources and partners can be incorporated at any time as their business evolves.

It solutions for telematics tariffs: via central 'data hub for sensor data' to valuable information

Ralf Kufner is an associate partner at Infosys Consulting, where he is responsible for the insurance practice in Germany and thus also for digitization offerings in the German insurance market. Based on his 20 years of professional experience, he focuses on optimizing core insurance processes and the associated IT systems and also supports his customers in the areas of digitalization and artificial intelligence.

Before insurers set up an appropriate architecture, individual telematics maturity levels should be determined. This enables a transparent and efficient analysis of the current state of affairs in the company and identifies any gaps. Depending on the degree of maturity, the market launch starts with the integration of the inventory management and distribution system into the telematics solution for a department. Then comes technology and process optimization. This includes fully integrating telematics solutions across different business units with a strong customer focus. With improved use of telematics data, both existing risk management and the sales approach itself can be optimized.

Keeping an eye on the data

Insureds are aware of the advantages of telematics tariffs, but often fear for the security of their data. After all, every journey is recorded and various events such as excessive acceleration or conspicuous braking behavior are logged in detail.

But what happens to the data? Who owns them and who is allowed to access them at all and to what extent? To avoid this dilemma, insurance companies should work with independent service providers who evaluate telematics data anonymously."

The respective service provider receives the data only with the associated ID without any information about the insured person itself. It analyzes the data based on the defined criteria and determines the respective bonus or malus. He then forwards this to the insurance company with the corresponding ID. This will ensure that customers' privacy and the protection of their data is maintained.

Data-driven future

Telematics has the potential to bring about major change in the insurance industry. In addition to providing a more accurate calculation of risk, it offers a new channel for interactive dialogue with consumers.

In order to benefit from these developments, it is essential to design an IT infrastructure that allows for an expandable telematics infrastructure."

It should be able to capture information from a wide variety of sources and share that data seamlessly with third parties. 

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