Customer segmentation is a tool that enables marketers to
customize their efforts based on the behaviors of their
customers. Customer Segmentation is the practice of
classifying your customers into distinct groups based on the
similarities in their behavior.
The main aim of this project was to create customer
behavioral clusters/segments based on demographics,
purchase behavior, and promotion response ad also to
minimize response time to resolve customer’s claim which in
turn improves the customer's Net Promoter Score (NPS).

The aim was to develop a Risk Predictive Model based on
statistical and historical customer details to calculate a predictive
score which could give a better criterion at time of resolution of
customer’s claim. Secondly, to minimize response time to resolve
customer’s claim which in turn improved the customer's Net
Promoter Score (NPS).

The aim was to develop a risk predict model based on the
demographic information and pre-existing diseases given by the
customer to decide the premium and design policies accordingly

Development of PD and LGD Models for Residential Mortgage
Loan Portfolio for DFAST submission and which could be
leveraged further for CECL requirements at future point in time.