22.03.2022 09:00

Big data Analytics Trends in the Insurance Sector

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Big data Analytics Trends in the Insurance SectorFor a long time, insurers have been using big data and AI regularly. They know that data analytics is essential in the insurance industry. Big data analytics allows underwriters to better assess risk, increase pricing, and provide more customized products. We will be looking at the use of big data by modern insurance companies in insurance.

Forbes reports that 54% of financial service organizations employing 5,000+ people have adopted AI. This is also true for big data analytics. We will be looking at how data analytics can help transform insurance companies in this article. Let’s get to it!

Insurance big data: Better product design, pricing, marketing

First off, we should mention that data analytics in the insurance sector helps in the broadly understood sales and marketing area. This is possible because of all the big data that underwriters have about their customers. The more data you have, the more information it is possible to extract. In fact, insurance companies know everything about their customers, from their homes and cars to their travel destinations and expenses. This knowledge is not collected for charity, be assured.

Big data Analytics Trends in the Insurance SectorTo create more customized products and services, underwriters make use of big data in insurance. With the advent of social media, they have new targeting options that allow them to reach their intended customers with tailored products that meet their needs. Insurance companies can use predictive analytics to analyze customer habits and make new offers based on what they think a customer will need shortly.

This is a solution that’s already standard in insurance companies like Lemonade and Hippo. Insurtech companies can take advantage of data-driven technology.

Every service and product in the insurance industry is tailored to meet customers’ needs. Lemonade went even further and created a smart assistant to help customers purchase a policy online. There is no paperwork and no waiting for someone else to answer your call. All of it happens in the app. It’s quick and efficient.
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Risk and claim management

Big data Analytics Trends in the Insurance SectorThis is by far the most important aspect of any insurance company’s work. Everything starts with profiling when it comes to managing risk and claims. To streamline the evaluation process, each customer must be thoroughly examined. Underwriters can provide accurate premium calculations to their customers in a matter of minutes. The entire process can be done online.

This knowledge, which we have just discussed, can also be used to better assess risk. Customers can benefit from correctly calculated rates that reflect their needs and habits. Customers who are reliable and unlikely to cause problems can receive lower premiums.

Insurtech companies often use big data to ensure customers and properties. It is often sufficient to provide the address to the insurer. Insurers use data from multiple sources to determine the risk associated with this person/location and then provide a quote. You can get an exact quote for your situation by using the Hippo insurance app.

Claims Management

Big data Analytics Trends in the Insurance SectorWe’ve already covered claims management. This is equally important, as underwriters deal with hundreds upon hundreds of damage reports each month. Claims management and analysis are essential in such a dynamic industry.

Data analytics is a great tool for the insurance industry! Insurers use big data to prioritize claims. They can, for example, decide to prioritize the most important and complex claims and hold off on those that are less urgent. Customers who require immediate assistance will be served first.

Another scenario is that you can choose to first deal with the undisputed claims so they can be closed quickly. It’s also possible with big data insurance! You can even prioritize any case! It is important to improve the customer experience while prioritizing cases. A PR crisis can arise when you prioritize “wrong cases”.

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