Data analytics could become a game-changer for the insurance sector. Conversations about applications include business intelligence initiatives, data management, and analytics/AI. The practitioners of analytics believe that they can drive growth in many ways. That’s due to the enormous amount of information most insurance companies end up collecting regularly. The promise is that by analyzing this data, companies can make better, more informed decisions.

So, how are insurers using data analytics to boost their businesses and better serve their customers?

How Data Analytics Helps Insurers

1.     Helps Set Competitive Prices

According to one report, 91% of the insurance carriers surveyed say they’re prioritizing the use of data analytic technologies to power their pricing decisions. Many of the small and medium-sized carriers interviewed said they found data to be most valuable in creating actuarial pricing models. That’s important because knowing how to price offers optimizes businesses when they scale up. That helps the insurance provider get more from their efforts. It helps them build their business, and reach out to more people. Data analytics helps companies use the information they collect from their digital transformations and integrations with data sources. They then use them to gain the kind of sustainable competitiveness, where price, peace of mind, and ease of doing business make a difference.

2.     Creates Personalized Experiences

Big data technology helps companies personalize some services for their clients. Unstructured data analytics can help companies track different facets of a customer’s life, such as their medical history or habits. They can also find out what would the ideal budget for the client be. That would help them create unique packages for each client, which would make them feel special. We know that families and businesses value that extra mile you go to know them. Agencies have traditionally trusted deep relationships between their agents and customers to get this level of personalization. It remains to be seen how close purely tech-led solutions can travel that road.

3.     Aids in Customer Acquisition and Retention

Businesses obtain customers by generating revenue, right? Data analytics makes this process more efficient by using unstructured data to create targeted marketing campaigns for potential customers. That streamlines the customer acquisition process significantly and generates excellent, high-quality leads. After that, they use algorithms to predict when a customer is feeling dissatisfied. Companies use insights to react to this in time, improve their services, reach out to these customers, and find a way to solve the grievances of their customers.

4.     Improves Risk Assessment Techniques

Insurers use data analytics to diversify their risk by using predictive modeling to discover certain possible issues based on a client’s data. That would help put them in a suitable risk class more efficiently. Simultaneously, insurers can compare a customer’s data against previous fraudulent profiles and identify cases that require more investigation. That would help decrease premiums for every stakeholder involved.

5.     Optimizes Internal Processes

Big data algorithms help decrease the time and effort required for many processes, such as working on a customer’s profile, deciding a suitable risk class, creating a pricing model, automating claims processing, and delivering the best services. A study shows that automation saves 43% of the time of insurance employees. That’s a lot of time, effort, and ultimately resources, that’s saved, with little investment involved.

6.     Satisfies the Customer’s Desire for Digitalization

The modern consumer demands digital experiences. If a company provides digital ways of doing business, they may be able to stand head and shoulders above the rest of the competition in the eyes of those consumers. It makes them appear modern, up-to-date, and more convenient to do business with. It’s also easier to keep a track of all the conversations, documents, and other important information. You’re essentially giving the customers what they want when you’re using digital means to improve your business.

7.     Improves Your Brand Value by Improving Customer Satisfaction

Using data analytics, you can predict the needs of prospective customers by using data trends to guide you. These have the potential to make more sales for your company than you would by just conventional methods of selling. Analyzing existing customer data also offers prescriptive insights to improving customer satisfaction. Therefore, it’s a powerful tool in serving your customers by truly understanding their needs and wants. That automatically increases your brand value in the market – by giving you the image of an insurance carrier that cares.

That said, it’s still important to put in that personal touch whenever it’s possible. While collected data can say a lot about a company’s clients, it’s simply not enough to gain insights from that. Many times, people put in inaccurate information. It can also be outdated information, in case the person in question doesn’t frequently update their information digitally. Then there are so many intangibles that impact the specific moment beyond what the historical data says. That’s why it’s important to maintain personal lines of communication with your clients. Just a technologically powered link can end up in your relationships having a short shelf life. Relationships tend to be more long-lasting when that personal communication route is established. While data can help make businesses more efficient, grow your business, and help you understand your customers better, it can’t replace the sense of humanity, of caring, that establishing a personal rapport does. For best effect, the approaches must align and work together.