Back when Munich Re launched the industry's first insurance coverage for artificial intelligence (AI) at the end of 2018, the policy, aiSure, found few takers. In subsequent years, as more companies digitally transformed their business and AI models and machine learning tools went mainstream, business picked up, prompting Munich Re last year to form a dedicated AI insurance team to scale aiSure and develop additional AI insurance policies. Online bonus: Munich Re provides a real-life example of an actual AI risk insured with the aiSure offering. Chief among the reasons is that Munich Re's estimable reputation and clout is sure to inspire other insurers and reinsurers to develop innovative AI-based products, culminating in a new insurance market. Given the rapidly growing use of AI software by companies on a function-by-function basis, viable risk transfer solutions absorbing the risks of AI-generated errors are sorely needed.

The California Insurance Commissioner and the California Department of Insurance (CDI) recently issued a bulletin regarding industry bias and discrimination. The bulletin acknowledged allegations of bias and discrimination in the industry and gave notice to insurance players that the CDI is watching and that "bias and discrimination in any form will be investigated and will not be tolerated." The bulletin is addressed to "All Admitted and Non-Admitted Insurance Companies, Licensees, and Other Interested Parties" -- clearly intending to cause awareness and attention beyond the carrier ecosystem. So, what does this mean? California has been a leader in following Europe regarding consumer protection laws.

Artificial intelligence and machine learning are increasingly embraced by U.S. carriers as they seek to remain competitive and modernize their operations, a new LexisNexis Risk Solutions study has found. Struggles remain, however, in terms of figuring out staffing and proper use of the technology to optimize its benefits. LexisNexis' look at how the top 100 U.S. carriers are using and benefiting from artificial intelligence and machine learning found a robust adoption of the technology and a strong belief in the benefits it will bring. Approximately 62 percent of respondents said they worked for insurance carriers that have already adopted artificial intelligence (AI) and machine learning (ML) initiatives. About 75 percent said they believe AI and ML can provide carriers with a competitive advantage through better decision-making.

It is difficult to open an insurance industry newsletter these days without seeing some reference to machine learning or its cousin artificial intelligence and how they will revolutionize the industry. Yet according to Willis Towers Watson's recently released 2019/2020 P&C Insurance Advanced Analytics Survey results, fewer companies have adopted machine learning and artificial intelligence than had planned to do so just two years ago (see the accompanying graphic). In the context of insurance, we're not talking about self-driving cars (though these may have important implications for insurance) or chess-playing computers. We're talking about predicting the outcome of comparatively simple future events: Who will buy what product, which clients are more likely to have what kind of claim, which claim will become complex according to some definition. The better insurers can estimate the outcomes of these future events, the better they can plan for them and achieve more positive results.

Next Insurance has begun formally marketing a portal designed to help independent agents quickly quote and sell its policies. Next said the system, dubbed "Next for Agents," had been in beta testing since April 2019, though more than 3,000 agents are already using the platform, including some from BTIS, London Underwriters and First Connect Insurance. The insurtech startup focuses on commercial insurance for smaller businessowners, and its policies zero in on areas including general liability, professional liability and commercial auto insurance. As envisioned, independent agents can quickly quote and sell those policies now either through Next for Agents or through other independent agent platforms. Next CEO Guy Goldstein has previously argued that agents were no longer a necessary part of the equation if the buying process became automated, particularly for commercial lines. "If computers can give you exactly what you need, why use an agent?,"

I was working with a business intelligence executive who told a story to illustrate this problem. His internal client wanted to use a machine learning algorithm to improve his operations. His team was only about 25 percent accurate at predicting certain events using traditional analytics approaches. He wanted a machine learning algorithm that could improve their performance, with a target of 85 percent accuracy. When he was told that the machine learning algorithm could probably get him to 50 percent accuracy (twice as good as what his team could do), the client refused to implement it.

Together, the last two responses add up to 71 percent of respondents, and Accenture reports that insurers are investing in AI in several areas of the business, including distribution, claims and underwriting. They are looking to empower agents, brokers and employees to enhance the customer experience with automated personalized services, faster claims handling and individual risk-based underwriting processes, Accenture said in a statement. Separately, Carrier Management interviewed representatives of four global insurance groups--XL Catlin, Allianz, QBE and Zurich--who described some of the AI initiatives already underway at their firms. They range from condensing lengthy engineering reports for swifter underwriting, reassigning some of the claims administrative services handled by offshore humans to robots, interpreting crop risk information delivered by drones, and deciphering communications from customers with heavy accents using natural language processing. Also detailed is Zurich's use of a multilingual natural language processing product called Cogito from Expert Systems that mines complicated, voluminous claims data to rapidly provide more refined information to claims adjusters for faster decision-making.

Insurers are increasingly under pressure to cut costs and offer better digital services to their customers. While core systems replacement and modernization activities close the gap to a degree, carriers are looking to a range of automation technologies to improve service, reduce costs and increase profits. One type of technology insurers are examining is artificial intelligence. This is a broad and decades-old discipline covering a range of technologies where machines demonstrate "intelligence." A challenge in artificial intelligence and psychology disciplines has been defining intelligence.