Big Data uses in Insurance Industry.

by Sonali Mishra Human Resource Executive

The insurance industry has always been quite conservative; however, the adoption of new technologies is not just a modern trend but a necessity to maintain a competitive pace. In the modern digital era, Big Data technologies help to process vast amounts of information, increase workflow efficiency, and reduce operational costs. Learn more about the benefits of Big Data for insurance from our material.

Let’s take a look at several Big Data solutions for insurance.

Customer Acquisition

Every person generates massive amounts of data via social networks, emails, and feedback, which gives much more precise information about their preferences than any questionnaire or survey. Analyzing such unstructured data, insurance companies can increase their efficiency by creating targeted marketing companies that will help to acquire new customers.

Customer Retention

Based on customer activity, algorithms can identify early signs of customers’ dissatisfaction so you can quickly react and improve your services. Using gathered insights, insurers can focus on solving client’s issues, offer discounts, and even change the pricing model to increase the loyalty of each particular customer.

Risk Assessment

Insurers were always focused on the verification of customers' information while assessing the risks, and Big Data technologies can increase the efficiency of this process. Before the final decision, an insurance company can use predictive modeling to estimate possible issues based on the client's data and precisely determine their risk class.

Fraud Prevention and Detection

According to Coalition Against Insurance Fraud, each year US insurance companies lose more than $80 billion due to fraud, and this results in increased premiums for every stakeholder. Using predictive modeling, insurers can compare a person's data against past fraudulent profiles and identify cases that require more investigation.

Cost Reductions

Big Data technology can automate many manual processes, making them more efficient and reducing the costs spent on handling claims and administration. In a competitive environment, this will result in lower premiums, which will attract new clients.

Personalized Services and Pricing

The analysis of unstructured data can help to offer services that will meet the customer's needs. For example, life insurance based on Big Data can become more personalized by taking into account not only the customer’s medical history but also habits detected by activity trackers. It can be also used for determining pricing models that will both ensure profit for companies and fit customers’ budgets.

Effects on Internal Processes

The implementation of big data algorithms can enhance the efficiency of most processes that require a lot of analyzation. Technology can help insurers quickly check the policyholder’s history, automate claims processing, and deliver better services to customers. According to McKinsey, automation can save 43% of the time for insurance employees, so they can focus on money-generating tasks.