Case Study

Successful Data Mart Design and Implementation for Midsize Bank

A bank engaged Oakleaf in response to its having been identified as a Large Institution Supervision Coordinating Committee (LISCC) Firm. The bank needed assistance in designing and implementing a data aggregation data mart containing CCAR Stress test results. The data mart’s purpose was to aggregate, reconcile, transform, and consolidate stress testing results across business lines and categorize results into reporting (FR Y14) asset categories. The data mart would feed downstream systems which would submit regulatory reports.

Approach

Over the span of approximately seven months, Oakleaf’s seven-person team designed and developed a consolidated CCAR results aggregation capability and aided in operating the aggregation facility during the annual year-end execution cycle. To assist the bank with their needs, Oakleaf provided business and data requirements analysis, as well as asset taxonomy analysis to support mapping and de-duplication. Our team designed, implemented, and tested CCAR results aggregation in the data mart. Finally, we provided operational support to our Client for stress testing execution. This collective approach ensured the success of the project and exceeded the Client’s expectations and needs, which factored into the client’s decision to re-engage Oakleaf for further development of a complete end-to-end CCAR and PPNR execution capability.

Result

  • Multiple books of business were sourced from systems of record.
  • Data-readiness was ensured for use as actuals and as model inputs for stress projections.
  • Mapping from internal asset categorization to Y14 line items was developed, ensuring that no duplication in assets would be reported.
  • Business overlays were incorporated into the end-to-end process.
  • Execution times were reduced by 60%-80%, and additional time was provided to review and analyze results during execution.
  • The utility served as a foundation for expanded end-to-end execution and the addition of model execution in subsequent years.

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