AI can help drive insurance innovation
Published: February 28, 2018
Updated: July 24, 2018
Author: Luke Jones
CATEGORY: Industry News
Innovative technology like artificial intelligence (AI) through machine learning is often viewed as a clear and present threat to the insurance industry, especially in auto where driverless technology is predicted to be hugely disruptive. However, there are also positives that many insurers overlook, such as the ability to machine learning to be used for faster underwriting.
Munich Re Canada’s director of application development highlighted Tuesday how technology can help insurers. As well as expediting underwriting, Lawrence Wong says machine learning can help to reduce fraud and make assessing vehicle damage more efficient and accurate.
Wong offered is assessment at the 16th annual Insurance-Canada.ca Technology Conference in Canada. He said AI is no longer a speculative technology and will increasingly become part of everyday life, something insurance companies cannot ignore. Instead, machine learning should be embraced to augment how business is completed in insurance.
“The power of machine learning is that you don’t have to explicitly program it,” Wong said during the session Case Studies in AI. “As you show [a self-learning machine] more and more pictures of bumper damage, it will, with experience, become more accurate at defining what’s vehicle damage versus what’s quirky vehicle design from the car manufacturer.
“Notice I said the word experience,” Wong added. “That’s exactly how a human loss adjuster would learn about vehicle damage. AI is about augmenting people.”
During a separate session, Charles Dugas, director of insurance solutions at Element AI said vehicles are already ahead with an array of sensors installed.
“So what you could try to do is assess the damage in real-time, leveraging sensor data,” Dugas said. “Obviously, that would require working with manufacturers themselves in order to understand how and where the sensors are placed and what kind of data can be related to shifts in the sensor.”