Case Study 2 : Propensity modeling

For a large bank

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01

Client

The client is a large private sector bank in India with a significant savings and current account holders base. The Client has various products in Assets and liabilities with a mix of vintaged and new clients.

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02

Problem

Client had a set of third party wallet customers to whom they wanted to sell the core banking products. The problem statement was to identify the high propensity customers who can buy core banking products starting with a savings account.

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03

Solution

  • G-Square analysed the demographics and buying pattern of customers in the wallet & looked at the bureau scores.
  • Using these factors, G-Square developed a robust propensity Model using various predictive modelling techniques and machine learning algorithms.

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    04

    Outcome

    G-Square’s productified solution is now implemented and is being used to target high propensity customers for cross selling the core banking products.

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