How to Put Insurer’s Data to Use

Learn what type of analysis can help insurers make good business decisions with their data.

Tunde PanakiMarch 2, 2017

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There is a massive amount of data available to insurers today. As Property & Casualty 360 points out, “Insurance companies have significantly more data than some think. But the industry has been unwilling or unable to use the data to its fullest extent. However, by ignoring this data, companies are missing opportunities to better service customers and to improve business.”

It’s no surprise to carriers that they have, and continue to collect, large amounts of data. Every insurer knows that about their business. But what should insurers do with all of this data? The low hanging fruit is to enhance the customer experience.

Enhancing the Customer Experience

Insurers can analyze customer data for information that can be used to ensure the customer gets the most optimal coverage they need while also protecting themselves from any underwriting risk or fraud. This allows insurers to provide highly personalized quotes for each individual customer instead of simply having standard rate cards. For example, if a student’s car insurance coverage was under her parent’s plan, the insurer could offer that student a discount on renter’s insurance after she graduates college. In addition, by applying predictive analytics, the insurer may be able to provide home owners insurance for the student when she buys her first home. The insurer already has the data required for these analyses and conducting these analyses helps to preempt churn long before it happens.

Reducing Customer Churn

We’re all well aware of the research that shows it is much more expensive to acquire a new customer than it is to retain current customers. With the use of data analytics, insurers can use algorithms to predict if a customer is likely to churn. If a customer is identified as “likely to churn,” they can then send that customer tailored information that is specifically designed to retain them. From specific types of coverage to lowered rates, there are ways to keep the policyholder engaged.

It is important to note that all of this is dependent on data quality. If the data quality has not been tracked and confirmed, it is useless. But fear not; there is a simple solution to ensure data quality.


An Enterprise Data Analysis platform can analyze 100 percent of data in real-time and derive valuable insights from it. An Enterprise Data Analysis platform automatically monitors data flow as it continuously moves throughout an enterprise to ensure data integrity and data quality. By ensuring data integrity and data quality, insurance organizations can ensure trustworthy results from all of their data and can put all of their data to good use.

To learn more about ensuring data quality, download this white paper:

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