Insurance is an industry built on information. From ship cargo losses in the 17th century to identity theft in 2018, insurers have always tried to gather as much data as possible in order to effectively evaluate risk. The exponential leap forward in data processing capabilities that has occurred over the past decade has given underwriters and actuaries more information to analyze than ever before. It’s a shift that is revolutionizing every part of the industry.
“Insurance will be enormously different in the future,” says Scott Walchek, founder and CEO of TROV, a San Francisco based insurtech startup. “We’re at the beginning of technology being applied to risk management.”
New technologies are allowing insurance companies to offer more personalized policies and dynamic pricing to increasingly sophisticated and educated consumers. Big Data has revolutionized many industries, but how have the notoriously conservative insurance companies embraced it to help generate greater profits — by taking less risk? Let’s take a look.
More Accurate Pricing
For an industry based around the law of large numbers, advances in data analysis can only help its bottom line. But this wealth of information is not the only way insurers benefit. While in the past, insurers relied on historical data, but now they can now view loss information in real time, allowing actuaries to identify trends as they develop. This enables insurers to price their policies without delay. Insurers can also tailor losses data to better price risks. By expanding the type of information stored and analyzed for each claim, insurers can identify how other factors affect losses and price their policies accordingly.
While this is good news for those who represent good risks, someone still needs to pay. A report by the Actuaries Institute in Australia states the obvious — that while big data will decrease premiums for some, “there will be a smaller group of consumers [who] have to pay more for insurance because they are considered higher risk.” The bottom line is that insurance companies rely on better data to take much of the guesswork out of their pricing systems.
Buying insurance has typically been a dry process, with the customer expected to fill out long questionnaires needed to help the underwriters determine risk. But with the help of big data, insurers are able to answer many of those questions themselves. Rather than relying on the insured to know the age of their home or whether it has ever suffered a flood, open-source data sets allow for automated risk evaluation. Insurers can also use this information to market more specific products to customers, opening new opportunities for both parties. Insurers can even using big data technologies to analyze social media profiles and their effect on losses, as the British insurer Admiral suggested it would do to better price car insurance policies.
Identifying Subrogation Opportunities
Insurers tend to undervalue subrogation (the substitution of one person or group by another in respect to a debt or insurance claim), with many reluctant to risk throwing good money after bad. “A lot of companies will only look at it as a cost,” said Joseph Turcotte, vice president and operations claims manager for FM Global. Turcotte believes that it could possibly be “10 to 20 points of your loss dollars that can be recovered through subrogation,” but that some insurers are too worried about expense costs to pursue them properly. Big data may change that. With analytical modeling able to better identify subrogation opportunities, insurers can prioritize which claims they devote their expense dollars to — and attempt to maximize their recovery.
Big insurers see a large volume of claims, and it can be difficult to determine which ones are genuine just by the first notice of loss. Insurance fraud is estimated to make up 5-10% of costs to U.S. and Canadian insurers, according to The Coalition Against Insurance Fraud. But analytical modeling can be used to determine which sorts of claims are most often fraudulent, allowing insurers to direct investigative resources towards suspicious claims, and provide faster claims payouts for ones that are not. This keeps costs down by limiting fraudulent payouts and keeps customers happy by speeding up claims processing.
The insurance industry is changing rapidly, and it’s hard to tell where it will end up. New technology is opening doors to insurers and policyholders alike, and both sides are profiting. Andrew Lo, CEO of Kanetix, says tailoring your product to the individual user is the way of the future. “Most carriers, if they are using telematics, they’re collecting data in order to determine driving behavior that is catered to the individual, versus underwriting that is based on statistics,” says Lo.
Telematic devices installed in vehicles allow auto insurers to access real time driving data from their policyholders, leading to lower premiums for safer drivers. These devices can also be used to track when an insured is actually driving, leading to so called “Pay As You Drive” policies. And technology is opening up other opportunities for insurers. The Insurance Research Council found that 45% of consumers would consider allowing their insurance company to receive information about the status of their home through a smart device or system. A similar concept is presenting itself in life and health insurance, with wearable smart watches and fitness trackers allowing insurers to analyze policyholder exercise habits in real time.
Insurers are using big data and analytics to reduce losses, increase recoveries, and lower premiums on good risks. They are also offering new policies to clients, and new ways to communicate with those clients. By embracing technology, traditional insurers hope to stay ahead of the tech companies who are looking to disrupt the old industries.