The insurance industry exists on a strange form of gambling; depending on the type of insurance involved, a company usually collects money from a lot of people based on their individual risk factors for certain events, then pays out large sums of money to a small number of people who eventually make claims. The only way to remain profitable in this kind of setup is to use advanced math and logic to calculate exactly what it takes to be profitable.
Enter Big Data
Big data is, essentially, the next step in the evolution of data collection and analysis, multiplying our previous capacity for number crunching and making projections. The insurance industry is obviously thrilled to have the capacity to make better decisions, offer better terms to policyholders, and even strike a higher profit, but how exactly are these changes manifesting?
How Big Data Is Changing Insurance
These are just some of the ways big data is helping insurance companies improve:
- More quantified data. One of the biggest advantages of big data is that it can work to quantify variables that otherwise wouldn’t be quantifiable. For example, with a large enough sample size and the collection of enough data points, you could see the effects of a specific behavior in a person’s life, or solidify an abstract concept with real figures. For the insurance underwriter attempting to nail down more slippery variables, this is a godsend.
- Collection and interpretation of feedback. Don’t forget that, like every other type of company out there, insurance companies live or die based on consumer satisfaction. If customers are unhappy with their policies or if a competitor offers better service and a better deal, they’re going to switch and take their money elsewhere. Big data can also help companies collect, evaluate, and interpret customer feedback rather than relying on individual reviews. With just a handful of surveys, you could easily determine where your customers stand, and pinpoint at least a handful of areas where your company could improve.
- More accurate, precise risk calculations. Of course, most of the profitability of an insurance company boils down to how effectively it’s able to calculate risks. Different customers will have different risk factors, based on a number of variables, and the more accurate your risk calculations are, the more reliably you’ll be able to turn a profit. Big data gives companies the means to make more accurate, precise risk calculations, and pave a path toward more consistent revenue.
- Greater consistency. Overall, having more quantified, objective systems in place allows insurance companies to perform more consistently. Remember, the basis of insurance is something of a gamble, and that gamble can either pay off or burn you, depending on how it goes. Most insurance companies experience extremes based on random fluctuations, but keeping your data and policies tight with more accurate figures and more detailed insights results in a steadier performance over time, which should put owners’ and investors’ minds at ease.
- More flexibility with policies. Finally, having big data at your disposal means you’ll be able to offer more precise types of policies to your potential customers. You’ll be able to calculate exactly how much a customer should be paying for a given policy, and identify which policy variables would result in the best possible coverage for that individual.
As big data grows to become more sophisticated and cheaper to implement, we’ll uncover even newer applications for its abilities. Until then, the insurance industry (along with the medical industry) stands to benefit from the increased power and systemization that big data can offer.
If you’re in the insurance industry, the next few years are bound to be exciting ones, so keep watch as new tools, tricks, and customers start to permeate your realm.
