Top 7 Big Data Use Cases in Insurance Industry

Big Data technologies are used comprehensively to determine risk, claims and enhance customer experience, allowing insurance companies to achieve higher predictive accuracy. Let’s take a look at the major uses of big data and its technologies in the insurance industry

Since the insurance industry is founded on estimating future events and measuring the risk/value of these events; volume, velocity, veracity and variety of massive datasets has become an essential tool for insurers.  With new data sources such as telematics, sensors, government, customer interactions and social media, the opportunity to utilize big data is more appealing across new areas of this industry nowadays.

Big Data technologies are used comprehensively to determine risk, claims and enhance customer experience, allowing insurance companies to achieve higher predictive accuracy. Let’s take a look at the major uses of big data and its technologies in the insurance industry;

One of the most important uses for insurers is determining policy premiums. Used mostly by automobile, home and health insurance companies, many insurers benefit from telematics (in-vehicle telecommunication devices) IoT devices and wearables (Fitbit, Apple Watch etc.) to track their customers in order to predict and calculate risks.

By using predictive modeling, the insurers can identify whether the drivers are likely to be involved in an accident, or have their car stolen, by combining their behavioral data with the exogenous factors such as road conditions or safe neighborhoods.

A similar use can be seen in the world of health and life insurance due to the growing use of wearable technology. Activity trackers can monitor users’ behaviors and habits and provide ongoing assessments of their activity levels. Many insurers are now offering services and discounts based on the use of these devices; in fact John Hancock is the first to offer customers a discount when they use Fitbit wristbands that allow exercise tracking.

You can also see how risk assessment is prioritized by the majority from the survey responded by U.S. property & casualty (P&C) insurance companies below.

As great as these uses sound, insurers should keep in mind to protect privacy of their customers and should take ethical concerns very seriously.

Insurers use Big Data to improve fraud detection and criminal activity through data management and predictive modeling.  They match the variables in every claim against the profiles of past claims which were fraudulent so that when there is a match, the claim is pinned for further investigation.

These matches could also involve the behavior of the person making a claim, the network of people that associate with (social media, credit reference agencies etc.) and partner agencies involved in the claim (e.g. vehicle repair shops).  These complicated matches might drop beneath the radar of a human; however they are successfully detectable by big data analysis.

Acquiring a comprehensive understanding of customer behaviors, habits and needs from various sources is very strategic for insurers in order for them to anticipate future behaviors, to offer relevant products and to identify the right segmentations.

Information gained from call center data, customer e-mails, social media, user forums and user behavior while logged into the insurers’ sites enable insurers to build unique customer profile.  Analytic systems can spot if a customer is about to leave by flagging up a high number of calls to a helpline.