Reducing human error

The distribution chain in the insurance industry is winding and complex. A series of middlemen examine information between the insured and the carrier, leading to a lot of human error and manual work that slows the process, said Breen. However, AI is already starting to fix that problem.

Algorithms can reduce the time and number of errors as information is passed from one source to the next. By logging into a portal and uploading a PDF, the amount of data entry and re-entry is reduced and accuracy is increased, Breen said.

“People get tired and bored and make mistakes, but algorithms don’t,” he added.

For Pogreb, bridging the gap between the insured and the insurer is as important as reducing error. With better data, both customers and insurers benefit, she said, because insurers can develop better products based on more accurate assessments, and customers will pay for exactly what they need.

“With machine learning, I think we’ll be able to do a much better job giving the consumer that advice automatically,” Pogreb said. “Based on what you tell me about your business and what I know about similar ones, [I can say] I believe this is the right combination of coverage for you. So it’s putting the onus neither on the agent nor on the customer – who frankly doesn’t have the experience or knowledge – but letting the data provide the advice.