AI can help close the insurance capacity gap
The industry aims to become more investor-centric if it is to close a gap in capacity that exists in the industry, which remains unfilled despite the hard market. But one additional way it can do this is to make better use of data and technology, including artificial intelligence (AI).
That is the view of Arndt Gossmann (pictured), chief executive officer of DGTAL, a Germany-based Software-as-a-Service company, which has launched an AI data capturing and process automation tool. He says the industry must get better at making it attractive to capital providers.
“The cycle came as predicted but new capacity has not flowed in,” he said. “That means we need to keep investor needs top of mind: they want operational efficiency and transparency.”
Irrespective of the overall gap of capacity, Gossmann believes the industry will aim for extending the business further, in primary insurance and in reinsurance. He believes the ambition has to be to grow the pie whoever possible.
“To do so in the current environment the focus has to be on the quality of the business,” he said.
An increasingly important tool in developing a good book of business is using technology to be cost-efficient and transparent. AI offers—at least in theory—everything that insurance needs to get to a different dimension by taking advantage of the data it has.
“We are starting to understand how AI can help to go much deeper into data and that allows for more transparency. Today, insurers and reinsurers only use a fraction of the data available to them,” Gossmann explained.
“But the tools available now, especially AI, can change this. The first stage is translating the data into something we can analyse. But then we can the drill down into that data to get a better understanding of claims development, for example.
“If you understand that better, you can better understand performance. That in turn allows me to attract capital.”
DGTAL has launched its latest product, called Grabber, which builds upon DGTAL’s flagship product, Driller, by using new techniques in optical character recognition, natural language processing, computer vision, machine learning, and AI.
Grabber is designed to deal with a number of documents across claims portfolios. It utilises similar AI approaches to Driller, while going much deeper by looking for specific information in specific documents.
Gossmann said that in addition to savings and efficiencies, such tools aid transparency. And, he says, the industry should not hesitate in trying AI for different tasks.
“AI is maturing in a way that makes it very usable. My message is don’t wait—start using it. The possibilities are amazing and the journey is starting now.”
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