Big Data Continues to Change the Insurance Industry

In both cases, specific ethical concerns exist. For instance, privacy should be a serious focus. The way driving telemetry works is by each road a driver takes being monitored, and each of them getting a grade for danger rate, which is based on how many accidents occurred on that certain road or similar roads that fall under the same profile. However, this does not suggest insurance companies should maintain a log for each trip the driver takes (although, because of a lack of transparency with the problem, some may).

Unstructured Data Can Be Transmuted To Usable Data

To a certain extent, it can be conducted anonymously using GPS location data that gets encrypted upon entering the insurance company’s analytic system. Then, the output is done in a way that does not breach the user privacy. For instance, it is not required to directly state the certain roads used by drivers back to the insurance company, as unstructured data such as that is not useful for analytics. Therefore, it may just show the driver had spent 50% of the time driving on ‘Grade A’ roads, categorized as safe. Another 25% spent on ‘Grade B’ roads, etc. That is one example of how unstructured data can be transmuted to usable structured data, with less chance of providing actionable insights.

Unfairness In The Health Care Industry 

When it comes to health insurance, there is more potential for more complex issues with ethics and privacy. Many people would likely agree that it’s efficient or even fair for those who choose to have unhealthy lifestyle decisions, such as not exercising or smoking, to have health insurance premiums that are higher. Although, it has been shown by science that the larger decider for a person’s health conditions, unfortunately, is more often genetics from birth. Therefore, it a type when genetic profiling is more common and the human genome has been mapped out, the most efficient approach would for those with unlucky genetics to have higher premiums. However, would that be fair?

Distinction Between Poor Health 

Through history, those with genetic disadvantages have costlier healthcare. However, with Big Data technology, behavioral analytics and genetic profiling has provided the ability to obtain empirical distinction between poor health is derived from poor decisions, or if it’s from genetic factors that cannot be controlled. It is significant to ensure there are safeguards to make the distinction fair. This situation is having a higher chance of being resolved by legislation, rather than just market forces.

Going past developing premiums that are more efficient and fairer, Big Data has proved useful for insurance companies by detecting fraud. Actually, the FBI stated fraud claims, not including health insurance claims, cost average U.S families between $400 to $700 a year due to increasing premiums.

Big Data's Use In Insurance Fraud Cases 

Big Data is used by insurer’s for tackling fraud cases by predictive and profiling models. This means, variables from each claim are compared to the prior claim profiles that were determined fraudulent. When certain variables match, it shows up as a likely fraud and gets flagged to be investigated more. The matches may include a person’s behavior when filing a claim, because those committing fraud often show particular behaviors that a computer analysis could detect, but could slip through human detection. Also, it could include examining the people they are associated with using open source demographic information, like credit reference agencies, or social media. It also includes reviewing partner agencies that are part of the claim, for instance, auto repair shops. Places where behavior patterns may indicate the establishment being involved in activity that is considered nefarious that the claimant could be complicit.

Marketing's Use In Big Data

Marketing is a third significant use for Big Data in the insurance industry. It allows a more complete understanding for customers from analyzing the data that’s available. Insurance companies are able to get more efficient with providing services and products that meet the needs of customers. Also, the better understanding is achieved by analyzing customer feedback and social media activity. Various algorithms search unstructured data from emails, phone calls, and information on social media regarding they like or do not like. This is then used to developed a marketing strategy that is personalized for individual customers. Also, the behavior of navigating the insurer’s website is logged, for instance the time spent on the FAQ or help sections, participation in message boards or forums, this information can be used to create a unique customer profile. American Family Insurance’s VP of strategic data and analysis, Justin Cruz stated “Our focus has always been on offering value to customers, but by zeroing by using data and technology, we can impact customers in an even more positive method.” Cruz’s company uses licensed analytics software called Talk & Learn from Applied Predictive Technologies. It was designed for increasing the understandings for customer data, making suggestions on services and products.

Use Big Data To Identify Risk

Insurance company’s marketing departments has also started using Big Data for identifying customers that are at risk for leaving or canceling services. Like with fraud detection and policy underwriting, the marketing department does this with comparing customer data from their activity with the activity of others that cancelled policies. For instance, the analytics system can put a flag up when a low or high amount of calls have been made to the helpline, indicating the potential for the customer to leave in the near future. An effort can then be made in an attempt to persuade the customer to stay. There are many ways this can be done, such as offering lower premiums or discounts. The most effective method however, is likely dedicating additional customer service to determining the customer’s problem.

Learn To Appreciate Big Data

There is no doubt that Big Data is a tool that can be used for bringing a large positive change for the insurance industry. It can be in the form of improved customer service, premiums that have more efficient prices, and reducing fraud. The insurance industry also has a set of challenges that are unique, with certain concerns with ethics and privacy issues. Of course, this is a situation that is likely to be discussed further the more technology advances, with particular focus on the healthcare insurance sector. Overall, it appears the insurance industry is proving Big Data is not to be feared, but appreciated when used correctly as it provides efficient support, services, and marketing.

If you are interested in learning how Big Data can help your insurance firm, contact TCORCalc today. Get started by reading "What New Insurance Brokers Need To Know".