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FRM Part II · FRM Exam Part II · Case Study: Model Risk and Model Validation

A bank's VaR model is validated by comparing its output with a simpler benchmark model built independently on the same portfolio. The two produce 99% one-day VaR figures that diverge materially. What is the most appropriate interpretation?

A material gap between a model and an independent benchmark signals potential model risk and calls for investigation of assumptions, data and implementation. Neither model is automatically right: complexity does not prove accuracy, and simplicity does not prove error. Concluding the data is flawed is also unsupported.

  1. AThe divergence signals possible model risk and should be investigated, since neither model can be assumed to be correctCorrect
  2. BThe more complex model is proven correct because complexity captures more risk factors
  3. CThe benchmark must be wrong because it is simpler, so the discrepancy can be ignored
  4. DThe divergence proves the data is flawed and no further model analysis is needed

Explanation

Benchmarking is used to highlight model uncertainty. A material gap means assumptions, data or implementation differ, and the cause must be explored. Complexity does not guarantee accuracy, and the divergence does not by itself prove a data problem.

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