First of two parts
The insurance industry is widely considered to be a conservative one, but massive developments in technology are now forcing it to evolve. As a result, many in the industry are unsure how to deal with these changes and how to apply these in their business models.
James Maudslay (pictured), global head of insurance at major data centre and colocation services provider Equinix, spoke with Insurance Business about five major technological issues that insurers grapple with.
“The real problem is all the points between those two ends,” he said. “And insurers must do all of these equally well. Serving all customers the way they want to can be a huge problem from a technical perspective. It wouldn’t be too far-fetched to say that insurers haven’t been the best in looking after their customers.”
Another problem insurers face is the emergence of insurance technology companies, or insurtechs. According to Maudslay, most insurtechs don’t go as far as setting up an insurance company, but instead focus on certain parts of the value chain better than insurers, mostly in the distribution and customer service aspects.
“Historically, insurers haven’t been quick in embracing new technology,” he said, adding that insurers deal with insurtech companies in four ways: collaborating with them to produce a new solution, develop technology in-house, buy the insurtech firm outright, and partner with insurtechs in joint ventures.
This means that many insurers are running on legacy systems. He explained that these systems are becoming increasingly hard to maintain, and they aren’t very flexible, making it hard to adapt to present-day needs.
As a result, many insurers create satellite solutions around their old computer mainframe systems in order to handle new technology. Many insurers also own their data centres. When these systems were created, companies such as Equinix, which specialise in data centres, didn’t exist, he said.
“As technology advances and they wind down their legacy systems, [insurers] think they’ll be able to repurpose their data centres,” he said. “But the reality is, winding down a mainframe is very difficult and extremely dangerous.”
Maudslay cited the incident of TSB Bank in the UK, where the bank transferred the data of its 5.2 million customers from its old system under previous owner Lloyds Banking Group, to a system under new owner Sabadell. However, problems emerged during the migration, which led to customers reporting that they couldn’t access their accounts or their accounts reflecting incorrect balances. It escalated to a full-on IT meltdown lasting weeks and prompted the Financial Conduct Authority to step in.
“I think the issue they have right now is that because of the sheer quantity of data that is available, [insurers] haven’t been able to point it to any truly valuable commercial use yet,” he said. “It’s only now that we are genuinely able to see them start using things such as AI and machine learning properly.”
According to Maudslay, insurers are now beginning to harness technologies such as AI, machine learning, and robotic process automation (RPA), and these could lead to a great transformation in the industry by using the technologies to produce tailored offerings for the public.
The greatest application of analytics is in connection with the Internet of Things (IoT), he said. Insurance is likely to be one of the most affected industries by IoT due to the huge amounts of data it provides. For example, the use of telematics has been a game-changer for the motor and life & health insurance industries. Through devices worn by users or installed in their vehicles, insurers are able to monitor their behaviour and provide rewards for safer driving or a healthy lifestyle.
This may lead to insurers being able to shift themselves away from being reactive to events to more of a trusted advisor role. With technology such as AI, they can start making predictions to help prevent loss from taking place.
It is with these huge amounts of data that Equinix can help, Maudslay said.
“We can interconnect parties so they can ingest, analyse, and use the vast amount of data produced by these technologies,” he explained.
Read the second part here.