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Historical Data Gathering

Historical Data Gathering


The ECB has regulated the definition of default for all banks across Europe. CubeMatch’s client, one of the major banks in Amsterdam, had to deliver at very short notice a quantitative estimation of the impact on RWA (Risk-Weighted Asset) and adjust its financial credit risk PD (Probability of Default) models. The CubeMatch team provided the client with a solution to gather and measure the required historical data for the estimation and model adjustments.

CubeMatch Deliverables

  • A Data Gathering plan that anticipated the need for data collection to support the delivery of the quantitative impact study within 3 months and to subsequently gather extended data from all locations globally for the model adjustment initiatives
  • A Data Quality Framework to measure each system of record for completeness, correctness, accuracy, lineage, processability and usability of the data and to align it with the central model development teams for acceptance
  • A Calculation Engine to recalculate the default thresholds

CubeMatch Approach

  • A dedicated CubeMatch managed team of experienced project and analysis professionals
  • Based on previous experiences we have plugged in a SAS based tool to provide us with the speed that was required from day one onwards
  • Standardise the way to collect data and create a factory to measure the quality of the data
  • Subsequently report the data quality to the data consumers

Benefits Delivered

  • Historical and remediated data gathered from both central and local data sources
  • Data to enable the Bank to estimate the impact of the implementation of the new Definition of Default, according to ECB guidelines and timelines
  • DQ (Data Quality) stamped data for the credit risk model department
  • Capability to produce the target data gathering solution