How can insurers assess risks for new emerging products

Source: Actuarial Post

Date: 21/08/17

The future of technology is fixated on intertwining the virtual world with the physical world. Digital sensors now sit in billions of cars, buildings, and wearable devices globally, continuously transmitting data to facilitate an endless stream of transactions, decisions and opportunities. By turning objects into network computers, the Internet of Things (IoT) is reducing friction and inefficiency across every major industry, from retail to healthcare.

By Richard Hartley, CEO of Cytora

It is revolutionising the way consumers and businesses interact, and consequently ushering in new schools of risk related to privacy, cyber security and liability.

The growth opportunities for insurers are huge. As the world becomes increasingly connected, the demand for new and dynamic insurance products is increasing exponentially.

How will insurers rise to the challenge?

According to research conducted by the Association of Risk and Insurance Managers (Airmic) with AXA Corporate Solutions, Chubb and JLT Specialty, the traditional insurance model is not fit for emerging risks.

Tesla, the self-driving car maker, is planning on offering its own insurance policies, rather than buyers having to rely on unfairly priced policies from a third party insurer. Due to its first-hand access to journey data, it can assess the risk in this area better than anyone else. Similarly, Amazon, leading the way with delivery drones, could be in the best position to insure its own fleet.

One of the key obstacles to offering relevant limits and affordable pricing for products such as autonomous vehicles is a lack of historical data. Insurance as a business is traditionally backward-looking, and underwriters today still largely rely on claims experience to decide how much to charge new customers. Reliance on hindsight means insurance is falling behind in relevancy as change in the world is speeding up.

Insurers are increasingly recognising that when it comes to new risks where claims data is immature or sparse, a new approach is required, and more importantly, that the publicly available data on company websites, social media and in news articles can be used to help understand, price and manage emerging risks.

A dynamic approach to risk pricing

To meet the rapidly evolving risk transfer needs and expectations of businesses and consumers today, insurers must develop dynamic insurance products that react to real-time information about risk.

Using AI and alternative data sources like the web, insurers can not only understand new areas of risk – they can identify profitable niches and enter new insurance lines rapidly without any historical claims data or underwriting experience. This offers the industry significant opportunity, particularly in markets such as Lloyd’s that are at the cutting edge of innovation but have historically been unable to commit meaningful insurance limits to new and unknown exposures.
This approach is already gaining traction within personal lines. In retail motor for instance, the rise of aggregator websites and access to external rating factors from telematics devices and industry fraud databases, allows carriers and brokers to offer their customers differentiated pricing, in real-time, without the need for excessive form filling.

By using publicly available, real-time data from the web, insurers can calculate accurate prices for risks outside of their exposure based on the true loss frequencies and intrinsic characteristics of each individual risk.

This will result in dynamic pricing, meaning much shorter contracts and fairer policies for businesses.

The benefits extend beyond premium growth. With access to a multitude of data sources, insurers can offer relevant, well-priced products to consumers operating in new and growing areas of business.


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