Diving Deeper

Building an Efficient and Compliant CCAR Modeling System

Robust coding practices and streamlining the process and reduces delays and errors in model development and implementation for critical CCAR stress testing execution.

Case Study: Robust coding practices and streamlining the process reduced delays and errors in model development and implementation for critical CCAR stress testing execution. Complex and unreliable code, manual processes, and extensive back-and-forth with development teams made it difficult for a Top 20 bank to implement models required for the Comprehensive Capital Analysis and Review (CCAR), a federal stress-testing exercise. The existing environment resulted in delays, data issues and model revisions that put the bank at risk for non-compliance in submitting on time. Facing multiple pain points with that process, the bank tapped into our expertise and experience to develop a...

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The Process Behind Process Automation

From EUCs to structured, automated data, we walk you through the process, best practices and change management to ensure you’re leveraging analysts’ skillsets to the fullest.

Since its introduction in September 1987, Excel has been the go-to resource in an analyst’s toolkit due to its versatility and capacity to quickly translate complex formulas into illustrative tables and charts. Over the ensuing years, a typical financial services analyst would build elaborate, interwoven spreadsheets, simple models, assumptions and calculations, all in Excel, creating end-user computing (EUC) applications. And while these EUCs built the foundation for modern automation, generally speaking, they lacked traceability or documentation, making model adjustments challenging and presenting serious challenges for governance, risk and regulatory compliance functions.