Abstract

The European Central Bank performs a targeted review of internal models with the objective of reducing the variability in risk-weighted assets (RWAs). This will be accomplished by harmonising practices and checking the compliance of Pillar 1 internal models of credit risk (CR), market risk (MR) and counterparty credit risk (CCR) with regular requirements. The paper will help assessment teams with guidance on which situations should trigger findings, covering a selection of mandatory key variables and allowing for additional tests to be performed. Specific attention will be paid to the different core banking systems and data sources that are used through to the (historical) risk database identified in the inspection. Although the fact that the information technology architecture and infrastructure for the credit rating systems are mode-specific, a simplified process will be outlined throughout the paper to illustrate the main process steps, systems and datasets. Targets are the retail and corporate small medium enterprises (SMEs) portfolios, including information based on personal experiences of the author. For the future, more sophisticated methods like artificial intelligence and machine learning, as described in literature, need to be found and applied.

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