88%

Accuracy in prediction of income

~2k

Affluent Customers worth $ 1 Mn

~38k

Affluent Customers worth $ 500k

Overview

Our client, one of the leading consumer bank, wanted to increase its revenue from its existing customer base. Client wanted to identify the affluent customer segment and target it for upsell and cross-sell opportunities.

Approach

TransOrg developed a customer 360° view using customer’s personal, transactional and account data, assets and different types of liabilities and income sources listed with credit bureaus, Equifax, credit cards and bank accounts.

TransOrg used various machine learning techniques to build income estimation models that can serve as appropriate baseline for wealth imputations and determine actual customer income as target-variable with 89% accuracy.

Output

  • Identified prospective base of 2k very affluent customers worth more than $1 Mn.
  • Identified nearly 38k high net worth customers (HNIs) worth > $ 500k.
  • Customer tiering on the basis of wallet share and wealth.
  • Personalized campaigns for right product to right customer.
Learn more about TransOrg’s value proposition, solution methodology and implementation approach