An individual bank will use a multitude of statistical models for each business segments and division to support annual, quarterly and monthly projections for income, loss, balance sheet and RWA. Since all the models are inter-linked it is very important for modelers to understand the inter-dependency among the models.

Also, the Federal Reserve wants banks to have complete control and visibility on inter model dependencies across various CCAR models, business portfolio and risk metrics.

The Challenge:

Today, banks use manual efforts to perform the below actions which is a highly labor intensive, time consuming and prone to error:

  • Dependency tracing across models, assumptions and outcomes
  • Wallet sizing exercises, sensitivity analysis across model inventory

In addition to statistical analysis, SME’s use qualitative judgment to identify those parameters with the highest priority. This qualitative judgment (knowledge) is never institutionalized and hence remains subject to local decision making, which, in turn, creates inconsistency in the decision-making process.

How we can help:

Parabole’s Impact Analyzer allows modelers to have real time visualization of inter-model dependencies and these dependencies impact on portfolio and risk metrics in near real time. It further enhances decision-making ability by:

  • Instant discovery of inter-model dependencies (across Credit, Capital, Revenue, Loss projection) and their relationships.

  • Instant discovery of correlation between data elements, model variables, FR Y14 ( A, Q, M) reports and qualitative judgments made by analyst.

  • Real time ability to simulate changing macro-economic events and discover their potential impacts on portfolio metrics.

Model Risk Management and Impact Analysis