Logistic Regression Analysis of Demographic and Vehicle Condition for Purchasing Vehicle Insurance

Abstract

Insurance is a contract, represented by a policy, in which an individual or entity receives financial protection or reimbursement against losses from an insurance company. Insurance policies are used to hedge against the risk of financial losses, both big and small, that may result from damage to the insured or her property, or from liability for damage or injury caused to a third party. Building a model to predict whether a customer would be interested in Vehicle Insurance is extremely helpful for the company because it can then accordingly plan its communication strategy to reach out to those customers and optimize its business model and revenue. In this research, we use the secondary data that collected in India in 2020, which analyzes vehicle condition, demographics, and owning a driver’s license on vehicle insurance buying interest. The method used in this research is the Logistic Regression, the response variable is the Response (of buying vehicle insurance interest), and the independent variables are Gender, Driving License, Previously Insured, Vehicle Age, and Vehicle Damage. The result of this research showed that the Previously Insured, Vehicle Age, and Vehicle Damage have a correlation to the Response.