How Data Analytics Implementation Helps Insurers Become Future-Ready


In the digital world, every commercial industry must leverage the potential of untapped business data. One such sector that possesses a treasure trove of business data is insurance. Business data includes product details, customer information, underwriting practices, pricing information, and others.

Hence, insurers can implement Data Analytics tools within their infrastructure to convert all these raw business data into useful insights. With these insights, insurers can identify new growth opportunities, influence more customers, and protect their businesses from potential risks. In addition, insurance firms can remain competitive by not just focusing on data management but also making data-driven decisions. Overall, Data Analytics tools help insurers become resilient and digitized quickly.

What is a Data Analytics Tool?

A Data Analytics tool is a software solution that incorporates the best of analytics and data management capabilities. These capabilities allow enterprises to collect and analyze huge volumes of data about their business, competition, and customers in order to make data-driven decisions and optimize processes. A robust Data Analytics tool enables end-to-end analytical processes from gathering, preparing, and analyzing data to applying analytics and observing results. Enterprises can team up with the right Data Analytics consulting services provider to implement an ideal tool within their infrastructure.

Why Insurers Should Use Data Analytics Tools

Many traditional insurance firms have long been dependent on manual processes. Manual processing or the use of basic spreadsheets and computer programs enables insurers to process and analyze only smaller amounts of confined data. Accordingly, calculating premiums and underwriting becomes relatively slow due to human evaluation. Since the process depends on human action, the problems related to inaccurate risk calculations and predictions increases. This impacts the cash flow and productivity of insurers at large.

In contrast, implementing Data Analytics tools by insurers automates most of the calculation process. Thus, the process becomes more accurate and requires less human input since Data Analytics solutions make calculations based on the programmed formulas inputted into the system. As per a recent study, 55% of insurance companies stated that using Data Analytics tools help them make accurate calculations and predictions.

Benefits of Implementing Data Analytics Tools by Insurers

There are several benefits that Data Analytics tools give to insurance enterprises.

  • Effective Customer Acquisition

Customer acquisition has become increasingly tougher when insurers use Excel and spreadsheets for tracking different lead information. This makes it challenging for insurers to capture the prospect and customer attention. In such a situation, insurers need to centralize information and databases. Data Analytics solution helps insurers centralize both structured and unstructured data from multiple sources. Consequently, insurers can research customer behavior patterns, common characteristics, and demographics, and target the right customer segments. This way, insurers can create more market opportunities to cross-sell and up-sell insurance products.

Moreover, integrating Data Analytics tools with CRM systems enable insurers to extract valuable insights from reports that display the customer journey, starting from search to conversion. It helps insurers understand customer behavior and allows the marketing department to target the right audience, run personalized campaigns, and convert leads into customers.

  • Accurate Underwriting

As stated before, underwriting is a complex and imperative task for insurance companies. It can be streamlined effectively through the implementation of Data Analytics tools. For instance, the Data Analytics tool would accurately predict a higher auto insurance premium for a client who drives the vehicle for a longer distance than that for a client who drives a lesser distance. Such data can also be valuable during insurance claims. Similarly, insurers can automate a policyholder’s underwriting journey, starting from FNOL to recovery.

The implementation of the Data Analytics solution supports underwriters to focus on subjective tasks that require judgment and intuitive decision-making while allowing systems to organize back-office work. Experts from the right Data & Analytics service providers can effectively program underwriting rules within Data analytics solutions. This, in turn, delivers uniform underwriting and eliminates risks for insurers.

  • Custom Insurance Pricing

In general, insurance product pricing is set by insurers based on reviewing a specific customer’s profile. The profile of every customer is scrutinized to evaluate the risk factors based on health records, biometric data, lab testing, and others. When the factors are evaluated, the insurer sets a custom policy price for the consumer. This manual assessment and product pricing determination is often time-consuming and usually results in indiscretions during claims processing.

By implementing Data Analytics tools, Insurers can easily determine how much to charge for a policy from customers. Data analytics tools help insurers include a range of factors into their pricing model such as customer perceptions, insurance product life cycle, and competition. Hence, insurers can automate customers’ risk factors evaluation process. Also, insurers can feed crucial premium parameters as inputs to pricing models. By considering both risk factors and premium parameters such as the type of coverage, insuree age, location, and solvency, Analytics-embedded pricing models can offer personalized product prices to policyholders.

When the risk and premium factors are inputted correctly, the pricing model can follow the regulations with better compliance and determine the policy price on its own. This method results in fast, and reliable custom pricing for insurance customers.

Summing Up

Every industry including insurance constantly keeps trying hard to compete with its competitors. Insurers can implement Data Analytics tools within their infrastructure to make data-driven decisions, automate processes and enhance efficiency. Implementing Data Analytics solutions is a major step for insurers toward attaining digitization while remaining competitive.

Written by elenamia

Elena Mia is a Technical Consultant, avid writer, and blogger. She has vast knowledge and expertise in Software/Mobile/Web products and frameworks and works with organizations to achieve their business goals.

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