Validating operational risk models

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Many banks are tempted to settle for a minimalist approach focused on merely meeting regulatory requirements; as a result, the banks fail to achieve the benefits of robust enterprise-wide risk management, and they do not recognize the growing business value of predictive models.

To that end, outlined below are the six best practices for envisioning the ideal model validation group.

The team must also have a broad understanding of the business context ranging from regulatory requirements to the enterprises’ strategic objectives.

Strong leadership and collaboration pull these individual competencies together to deliver outstanding team results in diverse business settings.

4) Comprehensiveness The ideal model validation approach encompasses the full range of KPIs relevant to the business.

In other words, the model should not only meet its established technical requirements but also contribute to continuous improvement of the business as a whole.

2) Competencies The MVG must possess knowledge and competencies that provide a balance of technical expertise, organizational awareness, and business judgment.

Success in managing model risk depends on how the MVG is empowered and the extent to which the model is embedded in the corporate culture.Experience has shown that a well-designed model validation function can not only facilitate compliance but also contribute broader value to the business.The idea behind recent regulatory initiatives is to promote a more risk-sensitive capital framework by providing banks with incentives for implementing good risk management practices.3) Framework The MVG operates within a structured analytical and policy framework so that every aspect of each model is covered, from design to implementation and ongoing use.The framework establishes an evaluation cycle (typically annual) and directs team efforts toward the central question of whether models are performing within their established performance thresholds.

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