Predicting likelihood of payment of renewal premium of an insurance plan for a client

Abstract

Insurance companies provide various insurance plans which are characterized by the maturity of the plan, premium payment frequency, type of the risk which must be insured and assured sum. The insured must pay the premium to the insurance company on a regular basis based on his plan. In the life insurance industry, each policy has a potential risk accompanied with them. This project focuses on one of these risks, the risk related to the termination of policies by the policyholders, known as “lapse” risk. Even if the insured fails to pay within the due date he/ she would be given a grace period post which the insured’s policy would be lapsed, and the insured must pay a penalty to renew his policy. Since the lapse rate is dependent on various factors such as the insured’s income, type of job, marital status, modal premium etc., it is necessary to understand and segment the customers and target customers who pose lesser chances of premium payment default. These customers will warrant regular reminders of policy payment and hence, company can target their resources to these customers rather than spending them on good customers. Also, it is important for insurance companies to maximize the retention of their existing customers as cost of acquiring new customer is higher than cost of retaining the existing clients. Companies at the time of expiry of a customer’s plan tend to circulate reminders of renewal in the form of mails, calls, etc. This process is time and resource consuming as well as is a significant cost driver to the company because they tend to call every customer without knowing likeliness of renewal of a customer. It is more beneficial in terms of improving its bottom-line if they target only customers who are less likely to renew and convince them to continue with the plan or suggest a suitable plan.