Big data has been making waves in the insurance industry, helping with tasks such as determining rates and detecting fraud.
Big data has been making a significant impact on the insurance industry. With the help of big data, insurance companies have been able to calculate risks more accurately and offer better premiums to customers, predict and control fraudulent claims and offer personalized insurance products. To do the above, insurance companies have been taking input from a number of sources, such as wearable medical devices, which have been a boon to the medical insurance sector. Though the insurance industry had already been evolving its risk and premium calculation methods, fraud detection and offerings, the availability of more data has increased precision and enabled insurance companies to predict risk more accurately than before. (To learn more about wearable devices and health, see How IoT Data Analytics & Personal Fitness Devices Can Keep You Healthier.)
Insurance Industry Without Big Data
Big data is a pretty recent phenomenon, and obviously the insurance industry was quite different without it. So how did the insurance industry operate without big data? Let us take a look at a few scenarios:
Risk calculation – Insurance companies took into account a number of factors before calculating or assessing risks. For example, in the case of medical insurance, factors such as age, health profile, smoking or alcoholism were taken into account. The premium depended on the assessment of risk. The risk assessment method however, did not take into account many other factors; it missed a 360-degree view of risks.
Fraud detection – Fraudulent claims have been a scourge for the insurance industry and it has applied certain fraud detection methods. For example, if someone made a fraudulent claim, the insurer would store the details of the claimant and deny claims from the same claimant in the future. However, that did not prevent fraudulent claims from proliferating. Obviously, the insurers needed to do something different about it.
Personalized products – Insurance companies have always offered products that are tailored to a certain extent. However, the products were not tailored on an individual basis, rather on a group or category basis. For example, certain insurance products were designed for executives between the ages of 30 and 45 and their possible needs, but it was always difficult to cater to individual needs with such products.
Big Data's Influence on the Insurance Industry
It is important to understand that big data has not brought about any fundamental change in the ways the insurance industry goes about its business. It has simply enabled insurers to assess risk and understand customer needs with greater accuracy. Given below is a description of how big data has influenced the insurance industry.
Better Premium Determination
Setting premiums for insurance products is a complex job, as underwriters and actuaries will attest to. The insurers need to make sure that the premiums for their offerings are both within the customer’s budget and help the insurers stay profitable. The insurance industry is a highly competitive one because customers evaluate policies based on the price they have to pay. To set the right premium, it is important to accurately assess the possibility of the risk event occuring. For example, a person with a history of heart disease will have a high probability of claiming insurance for cardiac treatment.
Insurance companies need data to find out more about potential customers, and they now can have access to data that provides multidimensional information about customers – behavioral, financial, credit score, addiction history and many other factors. The data helps insurers to accurately assess the risk or possibility of claims. The case of the auto insurance sector is a good example. Some auto insurance companies now offer telemetry-based packages which provide the insurers detailed, real-time data about the customer as a driver. The information is transmitted to servers used by the insurer from a gadget fitted into the car or an app installed in the driver’s smartphone. For example, the gadget or app can provide information on the average driving speed, number of accidents, number of traffic violations and other variables. Such data can be of immense help in building a profile of the applicant for an insurance policy.
Better Assessment of Risks
Wearable devices such as the Apple Watch and the Fitbit activity trackers, which can monitor a person’s activity profile and other lifestyle aspects, have significantly influenced how medical insurance companies assess risk. Such devices provide a lot of data to the insurers based on which the insurers can increase the accuracy of their risk assessment. According to Accenture, one-third of insurance companies are now offering their products based on the analytics from these devices. For example, Hancock, a prominent insurance provider, offers discounts on premiums and also a free Fitbit wearable monitor. Customers can have their premiums reduced by working hard to improve their health. As their health improves, the risk reduces and the premium also reduces. (For more on wearables, see Wearable Tech: Geek or Chic?)
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Fraud Prevention
One of the biggest struggles in the insurance industry is containing fraudulent claims. Big data has helped insurance companies to fight fraudulent claims with the help of profiling and predictive modeling. For example, variables within each claim made are matched with variables of fraudulent claims made in the past. If certain matches are found, then the claim is flagged for a deeper investigation. Examples of such matching variables are behavior of the person who is making the claim, network of the claimant, data about the claimant as found on the social media or other sources of open demographic data. Data has made it easier and more efficient to find matches and investigate. Previously, it was extremely difficult to quickly detect signs of fraudulent claims, as the evaluation was done manually.
Summary
While big data has had a positive influence on the insurance industry, insurers have to strike a balance between using data and maintaining customer confidentiality. It is important to convince the customers that the data is being used and the benefits are going to come back to them. According to Brooks Tingle, the SVP of insurance marketing and strategy for Hancock, “customers 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.” The companies, of course, need mature and responsible handling of the data they collect.