As regulators and insurers work to understand the level of regulatory oversight that is needed for AI innovation, there is a path forward by looking to the recent past. The massive 2015 breach of Anthem’s customer data was a catalyst moment for insurance regulators and led to the Insurance Data Security Model Law now being adopted across the U.S. In this piece, former insurance regulator Jillian Froment lays out five core goals common to AI and cybersecurity that could accelerate the adoption of AI regulation.

In other news: Amerisure implements One Inc ClaimsPay tech; California drivers report distracted driving is getting worse; HSB adds social media income to home cyber protection.

Jerry launched a car insurance comparison service in 2019 using artificial intelligence and machine learning. The company has more than 1 million customers across the U.S. and has expansion plans.

The pandemic has served as a catalyst for putting digital transformation across insurance on the fast track, and claims is one of the focus areas that is primed for implementing digital capabilities. As more claims information is captured and managed digitally, new opportunities to leverage artificial intelligent technologies arise. This leads to a vision of full automation, high levels of straight-through processing, and (logically) a diminishing role for claims professionals.

A new report, IT’s Changing Mandate in an Age of Disruption conducted by the Economist Intelligence Unit, supported by Appian, suggests that to continue with various digital transformations and increase adaptability for the future, some IT improvements must be made.

Several companies are using artificial intelligence and data analytics to better map properties for coverage in potential high-risk wildfire areas.

More homes that had been excluded due to wildfire risk are insurable with more granular data, company says.

The insurtech has deleted the post, which raised concerns about bias.

AI systems that aggregate data from actual anonymized claims, bills and other data could be trained to identify and update records, managing identities persistently and in real time.

Artificial intelligence (AI) is increasingly gaining ground in a number of areas of banking and financial services. However, there is growing evidence that AI systems are biased.