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How big data in the insurance sector is transforming the market

Big data in the insurance sector is paving the way forward, finding dynamic, practical solutions to real-time risk analysis.

Insurtech, most notably big data in the insurance sector, is revolutionizing what insurance has the potential to be. Many of the pain points for auto insurers in the past (like properly determining risk, detecting instances of fraud, and assessing driver behaviour) are suddenly no longer so painful.

Instead, big data in the insurance sector is finding dynamic, practical solutions.

With the right analytics tools by your side, you can consider the big picture. Although we’ll just be scratching the surface, we’ll show you how big data can redefine risk assessment, customer preferences, fraud avoidance, and overall cost savings.

Understanding external risk

When it comes to assessing motor insurance risk, far too many insurers put all their eggs in the “driver” bucket. How old are they? What is their driving record? What colour car do they drive?

It’s not to say these things are unimportant, but they don’t give you a complete picture. After all, other elements can (and do) impact driver safety.

External risk factors are more wide-reaching than you might think—some may have never even crossed your mind. The obvious ones include the weather and traffic, but these are just surface-level.

Consider the shape of the road. Where choke points and blind turns await. Historic collision zones. These external risk factors can be just as useful, if not more so, than an individual driver’s behaviour or traits when assessing individual risk. Why? Because they affect not only the driver but all the other cars on the road, as well.

It can be difficult to assess these external risks properly and accurately. However, we developed a proprietary risk engine designed to evaluate 85 external risk factors to calculate the “true price of risk.”

We believe this is one of the most effective plays for big data in the insurance sector so far.

Improving and understanding driver behaviour risk

External risk factors aren’t the only ones at play, of course. When it comes to assessing risk, analyzing driver behaviour is (of course) relevant. Once you have determined what causes them to drive well (or poorly), you have to find a way to encourage better driving performance (while correcting poor performance).

There are a number of ways you can do this. Some insurance companies utilize good driver discount programs, which reward safe driving by providing discounts—and penalizing poor driving with higher rates.

Similar rewards systems could include gamification, leaderboards, or friendly competition between customers to secure top safe driving records, as well as provide good-driver perks, like additional discounts, for continued good performance.

Understanding customer behaviour can also positively impact customer acquisition and retention. This is another instance of how big data in the insurance sector is revolutionizing the space. With accurate data detailing how customers behave, you can better determine which strategies are working for you, and which are not, and how you can alter these strategies to make them work better.

Suppose your data shows that a specific demographic—upper-income women, in their 30s, who drive faster than average—is less likely to use your insurance. With big data, you can conduct further research into why this demographic doesn’t use your insurance and put together targeted marketing strategies that are more likely to sway them to your company.

This level of data analysis can also be useful in understanding customers’ preferences and satisfaction levels, making it easier to keep and maintain customers longer. Algorithms fueled by big data in the insurance sector discover trends (like customer dissatisfaction) early, allowing insurers to move in and fix problems before they can snowball. This strengthens consumer loyalty and gives better insight into customers.

Detecting and preventing fraud

When it comes to insurance, fraud is no laughing matter. Fraudulent claims cost upwards of $80 billion in the United States every year, with property-casualty fraud claiming over $30 billion.

The truth is, insurers often end up having to pay out exorbitant amounts to cover fraud deficits, sometimes up to 10% of their total claims.

With our big data in the insurance sector, you can use an analytics and telematics system to better monitor vehicles and their assets. We help our customers sift through and analyze this data, significantly reducing the chance of auto insurance fraud.

Understanding the speed of the vehicle, the time of the accident, and any potential sounds in the vehicle prior to the accident, among other factors, can help insurers stitch together a clearer picture of what exactly happened.

The threat of this alone is enough to deter fraudulent activity, but it can also help catch those who are so bold.

Big data, little costs

Insurance fraud isn’t the only way big data can help insurers cut costs and keep them down. By leveraging things like UBI (usage-based insurance) and embedded insurance options, insurers can offer more affordable rates due to more accurate risk assessment scores.

This comes down to understanding, analyzing, and employing the data gathered from your customers and implementing them into the rates you offer. With usage-based insurance, policies are based on how safe a customer’s driving is overall. Insurers assess this by collecting data through the driver’s vehicle, then use it to paint a fair overall picture of their record and price policies accordingly.

Embedded insurance, meanwhile, allows insurance companies to offer lower-priced insurance policies to a greater range of consumers by integrating plans into products customers are already looking at, making it a welcome addition to their existing purchase journey.

Big data lets them monitor risk and reduce the chances of fraud, meaning insurers can spend less on distribution costs.

Let’s talk big data

If you’re curious to know how big data can change the way your company does insurance, let’s talk. Inaza is leading the way for big data in the insurance sector.

We offer plug-and-play and customized solutions for our partners, working with them to understand their goals and help them get there quickly.

Quantum Alliance Sees 30% Efficiency Gain with Inaza

Quantum Alliance Sees 30% Efficiency Gain with Inaza

Quantum saw a 30% reduction in non-core tasks in just a few weeks - now their underwriting team can focus on what matters.

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