Overview

The client, a financial services corporation specializing in payment cards, aims to enhance the calculation of Card Member Values (CMVs) and Return on Investment (ROI) to optimize investments. This involves assessing customer value not just on a transactional basis but throughout the entire customer relationship.

Solution

  • Acquired data from internal sources, including the customer360 database, and utilized forecasted data generated by the decision science team.
  • Analyzed card member data to identify user behavior patterns, creating a logical framework for estimating two key metrics: Write-off and Finance charges.
  • Implemented the logic in a Big Data environment to construct a dataset estimating write-off and finance charges based on card member details spanning up to 5 years for each tenure.
  • Continuously expanded the logic to cover different products and portfolios, focusing on enhancing efficiency and performance of the estimator.
  • Automated scripts were developed to reduce manual processing time.

Output

  • Granular CMV and ROI calculations are now enabled, with CMV calculated at the card level as opposed to the previous card member level.
  • Automation of the logic implementation ensures the use of the most recent values, providing accurate insights with minimal manual intervention and increasing the frequency of CMV calculations.
  • The project has resulted in improved acquisitions and retention through targeted marketing campaigns, ultimately leading to enhanced ROI for the company.
Learn more about TransOrg’s value proposition, solution methodology and implementation approach

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