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How to organize underwriting of insurances in this digital decade

The beginning of 2020 is a good moment to reflect on the next decade in the insurance sector. This is the second part of a series of three main topics: distribution, underwriting and claims. How will the underwriting in 2030 be different from how it’s done in 2020?

Transformation is mostly digital

When we wanted to look into the future in recent years, we turned to Silicon Valley. Today, more and more, we look to the east, to China. In the insurance sector ‘Zhong An’ is making waves. You can already guess why when you look at the companies behind this start-up: insurance company Ping An, Tencent (social media and online payments) and Alibaba (online shopping). Since the start in 2013, Zhong An sold already more than 8 billion policies.

They have more than 200 products, mostly small ones, low premiums and limited coverage. They work very fast, only online, and mostly guided by artificial intelligence and machine learning. Most communication is done via chatboxes. They launch new insurances quickly and if not successful, they end them just as fast. In China privacy hasn’t such a high priority, so Zhong An can use data from Ping An, Alibaba and Tencent to offer specific products to specific (potential) clients.

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Automated

Always be careful with comparisons, but Zhong An can learn us a lot. Also in Western economies, with a stable insurance sector and well-insured consumers/companies, the process of underwriting will keep moving to automation, with artificial intelligence and machine learning. External and internal information will be gathered in data repositories. By using these data, insurers will be able to make early decisions about underwriting and pricing, by offering the right insurance products in accordance with the profile and the needs of the client.

The influence of regulators, for example concerning privacy, is much more important in the Western world. The EU Commission is looking hard into all models using data, artificial intelligence, machine learning, …. The use of data has to be within limits. Certain data can’t be used, or can be restricted to avoid overly antiselection or excessive pricing.

Pricing

Since it’s much easier for consumers to compare prices, and then go for the lowest price, innovation to limit competition purely on price is important. A group of insurances will remain in the segment of price competition with very thin margins, and –hopefully- a large and automated turn-over. But there will also be platforms were customers and insurers connect and were differentiated experiences, features and value can be offered. Insurance companies could link their offer to related services or products, to make life easier for the customer.

It will be a challenge for the professionals in the sector to make the distinction between both groups, in the different markets/countries/age-groups. Which offer should be made to what customer in/by what way? Do we go for a low price or can we make an offer with real added-value?

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New risks

Not only the insurance sector is changing, many more technological breakthroughs happen. And the insurance sector has to find an answer to this. In the products that are offered, but also in the way the underwriting is organized.

Look at the cyber risk. The Wannacry ransomware had a cost of billions of euro worldwide. In Belgium recently an important manufacturer of aircraft parts and a major producer of machines for the textile industry were forced to close due to a cyberattack. And those are only the stories that pop up in the media. How do you understand, assess and price this risk?

When we talk about autonomous or shared cars, we talk about a shift of the risk: away from the car and the liability of the driver, towards the corporate liability of the car manufacturer, the network players and telecom operators. The local insurance agent will no longer sell his product to the individual driver, but global insurers or reinsurers will cover the liabilities of a whole fleet. This requires a whole different dimension.

Data

The most popular four letter word is no longer rude language but ‘data’, the fuel of the 21th century economy. Established insurance companies already have a fast amount of information. They now work hard to structure it and make it usable for advanced data insights and data enrichment.

This will gradually change the risk assessment and the pricing. Knowledge is a crucial advantage and data are just that.

The data will be actionable by the use of artificial intelligence and machine learning. Insurance companies will become data-driven organizations. Risks are today price based on historical experience, data processed by modern technology offers more future oriented risk assessment.

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