Date of Award

Spring 5-19-2017

Degree Type

Thesis (Restricted access)

Degree Name

Master of Science in Information Technology Leadership (MS ITL)


Computer Science

First Advisor

Michael Redmond


To remain competitive in the personal auto insurance industry, an insurance company requires understanding the churn of policies and which group of customers should be targeted for renewal of business and new business. Customer churn takes place when policyholders discontinue their relationship with their insurance carrier. This is the result of either non-renewal or cancellations of policies. Technological changes are affecting the insurance industry every day. NJ Insurance Company (*NJIC) has built new databases to capture new policy and billing systems’ data. With these new databases established, additional customer data will need to be collected. Data analytics can transform this data into valuable information. Data analytics is needed to understand why and when customer churn takes place which affects NJIC’s book of business and revenue. The book of business for NJIC entails all the insurance policies that NJIC has written. The book of business enables NJIC to keep track of all its policyholders and customer data.

Data analytics will uncover and identify patterns within the customer database. A data analytic tool is needed that will transfer the data collected into meaningful information. Data mining tools, techniques and algorithms can be used to uncover and identify patterns and targeted groups. Once these targeted groups are identified, potential technological enhancements and improvements to business processes can be discussed. Applying optimal data analytic techniques will uncover customer behaviors and help to identify the model behavior and customer risk profiles. This research is intended to lead to a project plan for NJIC that focuses on improving the company’s competitive edge using a digital strategy approach through data analytic results.