Basel II Credit Risk Modeling

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A diversified global financial services company

Problem Statement

  • Compliance with Basel II regulations for Global Credit Card portfolio
  • Need consolidated exposure at the parent level for the segments–wholesale and retail
  • Existence of several versions of single model with virtually no documentation

Analytics Led Approach

  • Relevant data elements merged to create single version of truth for customer’s credit exposure
  • Multiple validation across different sources and different data granularity
  • Scenario analysis to finalize segments for model build
  • Developed probability of default models (PD) to score the entire institutional customer base in accordance with Basel 2 norms

Business Impact

  • 40% jump in ability of PD models to accurately capture ‘at risk’ customers
  • Effective credit portfolio management using the principle of risk adjusted return on capital
  • Timely compliance with the capital adequacy guidelines outlined by the Basel committee
  • Reduction in the overall regulatory capital charges due to better risk management

Critical Success Factors

  • Understanding of Basel II norms
  • Expertise in predictive modeling techniques (logistic regression, IV analysis, missing imputation, etc.)
  • Expertise in modeling tools and languages (SAS, SQL etc.)
  • Ability to embed compliance requirements into modeling parameters

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