AI and Insurance: Whats in That Black Box?

Artificial intelligence business solutions and other "cognitive" systems have the power to transform insurance. Here's a sci-fi scenario for 2030, courtesy of the McKinsey consultancy: You're using your mapping app when your digital personal assistant warns you that your planned route entails a high likelihood of accidents and auto damage. The assistant then offers a small reduction on your motor vehicle and life insurance premiums if you take its suggested route instead.

AI has already begun making its way into every aspect of the insurance business, including claims processing, fraud detection, risk management, marketing, underwriting, rate setting, and pricing. The potential for creating business efficiencies is enormous: Juniper Research predicts that cost savings to the insurance industry from AI will reach $2.3 billion by 2024.

AI leverages big data to find correlations, inferences, and predictions, and to make recommendations on that basis. But this cutting-edge technology may prove to be a double-edged sword. "These systems are built through the harvesting of personal information from millions of people and are used to make decisions affecting millions more," says Laura Foggan, a Crowell & Moring partner and chair of the firm's Insurance/ Reinsurance Group. "They're exciting new business tools, but they also pose liability issues under existing laws and regulations. In addition, state and federal officials are considering new laws and regulations that are specific to AI systems."

DATA, DATA EVERYWHERE

More insurers today are mulling the use of "nontraditional" sources when assessing premium rates--sources that go beyond public or official filings. These include social media postings and data from sensors that can increasingly be found

in our smartphones, vehicles, wearables, and elsewhere. Real-time collection of individualized data from these sensors opens the door for behavior-based policy pricing. The data mining and predictive modeling capacities of AI systems provide a way to turn the billions of data points provided from nontraditional sources into more detailed and objective risk assessments. Some customers will gladly provide personal information in exchange for savings on their premiums.

AI systems can also vastly improve insurers' ability to detect fraud. Advanced predictive modeling can generate red flags during the claims intake process, routing suspect claims to investigation while proper claims are paid more...