Client background: Third-largest bank in Southeast Asia, headquartered in Singapore
Industry: Fintech
Products/Services: R (Advanced Analytics)

Propensity Model for a Bank

Business Challenge

  • Identify customers who have high propensity to buy a specific product

  • Understand factors influencing customer decisions

  • Facilitate promotional campaigns for the right customers

  • Increase positive response rates and customer loyalty

Business Solution

  • Exploratory data analysis to perform initial data investigation

  • Create inventory list of variables and identify variables which helps for predict high propensity customers

  • Propensity model using Random Forest, Logistic Regression, Neural Networks and predictive modelling techniques

  • Model comparison based on performance measures

  • Recommendations based on models, course of action based on variable importance

Business Benefits

  • Unearthed factors influencing customer decisions

  • Devised a roadmap for increased as well as qualified lead generation

  • Targeted high propensity customers for specific products

  • Used recommendations to run campaigns at the right time

  • Improved quality of conversions, increased the count of loyal customers

Environment

  • R

  • ANN

  • Random Forest and Logistic Regression