Digitalization is shaking up the insurance industry


 

Artificial intelligence, robotics, the Internet of Things are all buzzwords that are currently being thrown at management in every sector in Germany. Their concrete impact on people's everyday life, for example, on the number of jobs, is debated among experts. Digitalization will change the insurance industry. There is no doubt about that

For four years, founders have been able to get venture capital in the TV show "Höhle der Löwen" and attract media attention, whenever the prominent financial backers are impressed by the new business models. Financial and insurance products are hardly part of this, because insurance and insurance technology are considered tedious and sedate. Neither of these characteristics is good for an appearance on a prime time TV show.

 

Straight through processing – Digitalization does not happen on its own

The frequent accusation of insurtech founders directed at traditional insurance companies is that they are too slow. This is easy to sell to the media, but shows poor understanding of reality in the companies.

For insurers, process automation is actually nothing new. Since the 90s, insurers have been working on "straight through processing" in their processes. But the topic is much more complex on the back end of an insurer, than in sales. For example, statutory health insurance companies can only choose from a limited offer of sector software. The choice of provider is thus a long-term investment decision, which defines the IT strategy for a longer period. Unlike commerce or industry, insurers are not free to decide which products they do not want to offer in the future anymore (for whichever reason). And legislators set the framework for processes in many areas.

To use the potential of straight through processing and digitalization, they need a partner that does not only understand this complexity, but offers a solution that fits into this existing IT and process landscape by way of interfaces. The higher the number of transactions in one area, the greater the savings potential from automation. Since the ongoing business operations cannot be interrupted and synchronization of activities between IT and different departments is needed, an automation strategy should be guided by threshold values: How many minimum cases are there for one transaction and which degree of automation can be achieved? Consideration also needs to be given to how such automation impacts marketing and customer loyalty. Based on these parameters, a schedule can be developed for automation implementation.

 

IoT opens up new business models

The Internet of Things describes the phenomenon of networking of all kinds of objects by way of the smallest components. Classic examples are Smart Home devices, which do not only include devices that control light and heating, but also all kinds of sensors that check the home for damage or incidents, such as smoke detectors or surveillance devices. Allianz was one of the first companies to create Allianz Assist, a supplementary product around this growing market.

In auto insurance, SIM cards and other components built into vehicles can be used for networking to analyze driver behavior and constantly transmit this information to the insurer. A risk profile of the driver is created based on the usage data. Based on this data, drivers are offered a pay-as-you-drive policy.

Thus, digitalization leads to new approaches to rate-setting or completely new insurance models. Cyber insurance is another example. At the same time, traditional insurers should not ignore that these paths are open to new market players or unexpected competitors, such as reinsurers.

 

AI in communication with customers and claims management

Permanent data evaluation for several thousand vehicles produces a data volume that is hard to imagine. It is much too high to evaluate manually or using classic IT technology. Analysis methods summarized under the name "Artificial Intelligence" are needed to identify patterns in this pile of information.

AI will provide support to insurers in many ways and thus make processes more efficient and cheaper. An announcement by Zurich last year caused a stir, when the company stated that it had saved several thousand working hours by using AI in claims adjustment. A typical claim that takes 52 minutes to process by an employee is processed within five seconds by adaptive software.

The Chronos solution from Lapetus Solutions seems even more utopian. Using AI and image recognition, the new company wants to make medical questions in the framework of health and life insurance superfluous with a selfie from the applicant.

In the area of customer communication, bots can automatically classify incoming e-mails and letters and answer routine questions. Google impressively demonstrated the extent of this technology at the beginning of the year, when Google Assistant held an automated phone call with a customer. People can no longer tell the difference.

 

Innovative insurtechs digitalize processes

Digitalization in insurance does not necessarily mean automating application or processing right away. Even the increase in efficiency of certain areas can make sense. Most insurtechs are rushing into the area of sales or sales support. There are exceptions worth mentioning:

SkenData has specialized in the building insurance segment with its "Wert 14 direkt" offer. SkenData reduces the normally extensive process of appraisal to a few entries online. The basis is formed by data from the land registries, official 3D building data, and aerial images, which are used to develop a realistic image of the building based on recognized calculation methods. Only expansions and fittings need adjustment. The result is all the important building dimensions such as cubage, gross floor area, living area, and residential units.

Digitalization will continue to leave its mark on the insurance industry. Insureds will also benefit from it, for example, through faster processing times or better availability of the insurance company.

 

 

Read how we, too, use straight through processing and machine learning in our software solutions:

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