Insurance companies are in the risk business. Their customers pay them for financial protection against all sorts of accidents and tragedies: hit-and-run car damage, illness and death.
Until recently, though, insurers had a hard time precisely determining how much to charge policy-holders, because it was difficult to reliably distinguish between high-risk and low-risk applicants. Their customers, meanwhile, endured a frustratingly slow application process.
It's not that insurance companies lacked sufficient data with which to build refined risk prediction models; they simply lacked the tools to store and analyze it. And so, for many years, they would analyze subsets of datasets and then essentially cross their fingers.
Those days are gone. Thanks to big data analytics, insurers can digitize and mine the information they’ve amassed for decades in order to glean predictive insights. They can also incorporate new data streams, from sources like Fitbits and connected cars, to further refine their risk models.
An executive at insurer John Hancock told Forbes, “[C]ustomers don’t mind giving up some data if you’re transparent about what data you’re asking for and they are getting real value back for it.”
Some customers and critics, however, argue that data-driven policy pricing poses ethical problems. For instance, do insurance companies' algorithms penalize people for being poor, or for not being white? Rate-wise, to what degree will the more fortunate and less accident-prone continue to subsidize their high-risk counterparts? And how much consumer data is too much?
Big Data in the Insurance Sector
So far, big data has certainly been advantageous to healthy people and safe drivers, who save on their premiums. Beyond risk prediction and policy pricing, big data has impacted insurers' customer service protocols and even what's displayed on their web storefronts. And its role in the insurance industry continues to evolve.
We’ve rounded up 21 insurance companies that are leveraging big data to improve policy coverage and customer experience.
How it’s using big data: This home and renters’ insurance startup gathers “inhuman” quantities of data on its users, which means it can tag its plans with ultra-personalized prices. Lemonade collects data in various ways, most notably through an AI-powered chatbot named Maya (based on a real employee named Maya). Bot-Maya can have thousands of simultaneous conversations with would-be customers while amassing data on their exact queries and needs.
Location: Richmond, Va.
How it’s using big data: The travel arm of insurance leviathan Allianz uses big data to personalize its user experience. Airlines often offer policies from Allianz and its affiliates when travelers book flights. Allianz created an algorithm that personalizes those add-on policy offers in less than a second, incorporating variables such as the number of travelers and the time between booking date and flight departure.
Location: Columbus, Ohio
How it’s using big data: Through its SmartRide program, Nationwide monitors drivers for four to six months before they sign up for a policy. Safe driving during this period can earn clients discounts of up to 40 percent.
The company offers more than car insurance, too, and its data analysts hope to expand programs like SmartRide to other arenas such as home insurance. As one Nationwide analyst explained to Diginomica: “We've got electric carbon monoxide readers and Nest and all these other things that are monitoring all this data and so, what do we do with it? How do we capitalize on it?”
Location: Bloomfield, Conn.
How it’s using big data: Cigna started a $250 million venture capital fund, Cigna Ventures, which supports early-stage startups that are approaching big data analytics in new ways and creating healthcare-relevant technology. The company has so far funded a bevy of ventures — including MDLIVE, which lets patients video-chat with doctors who are on call around the clock.
How it’s using big data: Liberty Mutual’s Solaria Labs functions like an in-house think tank dedicated to technological innovations. It has so far come up with two “Shine APIs,” which turn masses of company data into user-friendly tools for consumers making major purchases. The Total Home Score rates properties based on location-specific data, like noise levels and traffic patterns; meanwhile, the Vehicle Stats feature aggregates various vehicle specs and reviews in one convenient portal.
Location: Palo Alto, Calif.
How it’s using big data: The life insurance application process used to be almost prohibitively labor intensive. Ladder streamlined it with an online form that contains only a few simple questions. Ladder uses data to unlock the predictive power within each question so applicants no longer need to get physicals at a doctor’s office — which was once a typical and time-consuming requirement for life insurance clients.
Location: Columbus, Ohio
How it’s using big data: Via its proprietary app, this insurance company tracks drivers’ turns (for smoothness) and frequency at the wheel (less time driving means cheaper insurance) for a two- to three-week test period before offering a car insurance quote. That means it collects a lot of consumer data, including sensor data that's so nuanced, it can tell the company whether a phone is located in the driver's or passenger's seat.
How it’s using big data: In 2018, John Hancock announced that it would sell only “interactive” life insurance. In other words, every policy would offer rewards to clients who let the company to collect their health and fitness data through wearables like Fitbit as well as a proprietary app. On top of that, there would be extra rewards for healthy behavior. The approach sparked pushback, and the data-sharing feature remains optional.
Location: Carthage, Ill.
How it’s using big data: State Farm collects data on customers' driving behavior through a mobile app and in-vehicle OnStar systems for its Drive Safe & Save Program. Clients earn an automatic discount for enrolling in the program, and accrue further discounts if they accelerate and brake smoothly, avoid phone use in the car and drive at safe times of the day—avoiding rush hour and wee hours. It’s all carrot, no stick, too: Good behavior earns rewards, but drivers never get fined for, say, jerky turns.
Location: San Francisco
How it’s using big data: Using a dashboard device smaller than an orange, MetroMile securely collects data on how much its clients drive. In exchange, clients get a new model of insurance: pay per mile. The low monthly fee and an even lower charge per mile are cash savers for those who get around via a combination of driving, biking and public transit.
How it’s using big data: Safeco uses big data to forgive typically responsible drivers who get a ticket or are at fault in an accident. Through the company’s Rewind program, drivers can install a tracking device in their car for about four months. If the accumulated driving data verifies that they drive safely, their incident-inflated insurance premium drops back to previous levels. The data can even expunge an accident from a driver's insurance record.
How it’s using big data: Blue Cross Blue Shield’s BCBS Axis transforms internal healthcare data into a patient-facing research tool. A collective of more than 36 health insurance companies, BCBS has data on pricing and reviews for more than 90 percent of all doctors and hospitals in the U.S. They’ve used it all to create Axis, which is stocked with useful intel on both provider quality and procedure price variations by region and doctor.
Location: London, England
How it’s using big data: Founded in South Africa, this company insures clients based on their “Vitality Age" — a measure of illness and death risk that's based on a combination of biometric markers and lifestyle choices. When a client has a higher “Vitality Age” than their real age, Vitality generates personalized health plans, rewarding participants with gift cards and prizes.
The company amasses big data on consumers through the “Vitality Age” calculator as well as through wearables and affiliate organizations like gyms and grocery stores. Those affiliations help the company ensure that users are complying with their wellness plans by documenting clients' activity and eating habits.
Location: Mayfield Village, Ohio
How it’s using big data: Progressive monitors how much and how safely its customers drive via its Snapshot program, which tracks driver activity through a device that plugs into car dashboards. Less driving, and safer driving, means bigger discounts. Snapshot participants can also opt for monitoring via Progressive's app, which not only tracks driver technique but offers driving tips. App users can also flag rides for which they were passengers rather than drivers in order to avoid getting dinged for, say, a friend’s abrupt U-turns.
Location: Newark, N.J.
How it’s using big data: Prudential has used big data to reshape its customer experience. In the past, each Prudential department had its own customer service protocol. Now, big data from call centers and hundreds of Prudential websites helps the company craft a more cohesive and personalized customer service experience, determined by an individual user's preferences and not just by the department that's been communicating with them.
Location: Hartford, Conn.
How it’s using big data: Recently purchased by CVS Health, Aetna is now part of a data powerhouse. By pooling its insurance data with CVS’s pharmacy data, Aetna can track unfilled prescriptions — a costly problem termed “medical non-adherence”—and craft more robust public health initiatives for at-risk groups.
Location: Santa Monica, Calif.
How it’s using big data: Back in 2011, when Allstate started mining the data it had already amassed, the company began deploying its resources more efficiently. Using big data analytics, it started targeting customers that were most likely to leave for competing insurance agencies, making extra efforts to keep them on board. Analytics also helps the Allstate team pinpoint claims that are most likely to be fraudulent, which cuts down on needless inspections.
Location: Chase, Md.
How it’s using big data: Geico's marketing budget can exceed $1 billion a year, and it's allocated based on a big-data-driven strategy that started back in 1999 — the year Geico's gecko debuted. Initially a stopgap solution to an actor’s strike, it drove such a noticeable bump in sales that the company stuck with the little guy for 20 years, and has invested heavily in data-driven marketing strategies ever since his debut.
Location: Springfield, Mass.
How it’s using big data: MassMutual has opened a digital insurance startup called Haven Life that prices policies based on applicants’ MyLifeScore360, a mortality risk metric. It's calculated based on 48 variables — including family medical history and lipid intake — that emerged as significant when the company analyzed hundreds of thousands of MassMutual life insurance policies dating back 15 years.
Location: Lincoln, R.I.
How it’s using big data: At Amica, big data speeds up customer service during natural disasters. The company integrated its claims system with GIS technology, a trove of up-to-the-minute, location-specific data. When an earthquake hits, or a wildfire tears through a town, Amica agents see it happening in real time on their digital maps and prepare accordingly for the upcoming influx of claims.
Location: San Francisco
How it’s using big data: Big data fueled the creation of Esurance’s Coverage Rules Engine, a personalization platform that sifts through the company’s more than 8 billion coverage configurations and plucks the best one for each customer. The engine relies on nearly two decades of Esurance data on consumer habits and pricing, but it also collects customer data with every customer interaction.
Images via Shutterstock, social media and company websites.