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The digital transformation of data analytics in insurance

The digital transformation of data analytics in insurance | Insurance Business

The digital transformation of data analytics in insurance

It has come to that time again when consideration turns both to the year that has passed and to the 12 months stretching ahead.

To provide some insight into the key surprises 2019 held for the insurance sector and the upcoming challenges and opportunities 2020 is likely to offer, Insurance Business talked to two leading professionals within the industry.

Looking over the last year, global pricing and underwriting leader at Willis Towers Watson, Dave Ovenden (pictured above), noted an unusual rate of market adoption.

The market is very dynamic when it comes to pricing, he outlined - it moves quickly depending on external market factors and the ambitions of individual players. In 2019, he said, several Latin American markets moved almost overnight from being relatively sleepy to quite dynamic.

“To see a whole market move like that quite quickly over the course of a year is quite surprising to watch from a distance,” Ovenden said.

The resolution of data ingestion issues has been another significant marker of 2019, Ovenden stated, highlighting how the level of accuracy machines can be trained to achieve when it comes to large data sets has been surprising.

“Lots of industries are carrying out this development,” he said, “but, with insurance, you can really ramp up the accuracy.”

Meanwhile, for Rich Sega (pictured below), global chief investment strategist at Conning, 2019 was less a year for surprises and more the year for unmaterialised threats, as tech innovations brought more positives than negatives to the industry. In particular, he identified the enormous impact of digital transformation on the insurance sector. The volume of data involved in insurance is enormous, he said, and the digital transformation of data analytics has dramatically accelerated.

Sega hopes that a major development in 2020 will be seeing data analytics starting to pay off for insurance companies.

“We’ve done all the infrastructure to build out the acquisition, categorisation and processes,” he said, “so the question is when does it lead to better outcomes, better underwriting, and more intricate and tailored product design for the customers of insurance companies?”

For Willis Towers Watson, which has been providing predictive analytics and vendor support for around two decades, Ovenden said, data analytics has seen rapid and instrumental growth in the last year. This has been led by more machine learning in the personalised space, he said, and also a sustained rise of analytics in commercial lines.

“When I joined the business seven years ago,” he said, “our revenue was around 5% commercial and 95% personal, and this year will be pretty close to 50:50, and personal hasn’t shrunk.”

This is illustrative, Ovenden said, of a steady climb, particularly within the last three years, in commercial analytics, and reflective of the energy and effort that has gone into this sector. Analytics is essentially an arms race, he said, and if you can’t deploy things quickly then you are always playing catch-up.

Wider implications
A lot of people in commercial lines are waking up to what technology challenges around deployment mean for the wider architecture of technology, Ovenden said, and this is driving a more global conversation around pricing and how pricing is governed and driven. Large multinationals, he said, are starting to really consider the wider implications of leveraging the data which is their greatest asset.

“‘How do I help people with my underwriting data?’ and ‘how do I help my underwriters better with my claims data?’ and ‘how do I share elements of our data internationally when it makes sense to do so?’ are the questions they are now considering,” he said.

These questions are particularly relevant to brokers, who, Ovenden outlined, are supported by the recent developments in this sector.

Brokers are building models which allow them to look back on what’s being offered to them, and to sort and prioritise this data, he said, and detailed how the conversations which brokers are having with their clients can be enriched by these analytics.

This digitisation will likely bring about opportunities for more automation, he stated, which will either remove simpler tasks from the broker's day-to-day work schedule or simply make these processes faster.

The progress brokers are making in the digital analytics space should, in turn, be something of a spur for insurers who are lagging behind, Ovenden said, as it could be another area where brokers leverage further advantage in the insurance distribution network.

“Overall,” he said, “I think the place of the broker in providing advice to the client is secure.”