Case study

Enhanced Customer Experience: SG Analytics Empowers Clients in Understanding Customer Behaviour and Formulating Business Strategy

SG Analytics Fraud Case Study Enabled a Credit Card Company in Addressing and Mitigating Fraudulent Transactions


  • Our client, a major credit card issuer in the US, was facing issues with payment holds, and consequently, sales declines were increasing without a corresponding reduction in fraud.
  • A complex set of strategies, a legacy to the company, was not up to the mark to manage fraud.


  • Analytics Engagement
  • Preliminary segmentation used to build key segments of customers based on spend patterns
  • Features for analysis created from multiple data sources:
  • ML techniques like XGBoost and LightGBM were used to identify top predictors of transaction fraud
  • Simulation analysis used to optimize cut-offs for predicted positives using data on the sales decline rate


SGA’s engagement comprised two data scientists and one data engineer working in an Agile framework.


  • A complex set of 50+ segments of strategies replaced by clearly delineated sets
  • Easy to comprehend, resulting in quicker buy-in from stakeholders
  • Less complexity helped with faster deployment


  • Build and implement robust ML supervised and unsupervised models and strategies to improve fraud capture
  • Enhance customer experience by reducing false positives
  • Reduce sales declines from good customers affected by fraud rules
  • Build detailed tracking mechanisms for the implemented strategies

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