ECB introduces plausibility checks on AnaCredit reporting

The ECB has published a document detailing new plausibility checks[1] on top of the existing validation checks[2].

The plausibility checks are intended to complement the existing validation checks. The validation checks mainly focus on the technical accuracy of the reported data. The introduction of plausibility checks ensures that AnaCredit data are of sufficient quality to serve the purposes for which the data have been collected.

The ECB distinguishes 6 types of checks depending on whether the checks:

  • are performed purely based on AnaCredit data (“internal” checks) or against other data (“external data”);
  • relate to a single observed agent or across observed agents; or
  • relate to a single reference date (structure category) or multiple dates (stability category)

Internal plausibility checks

Internal plausibility checks are self-contained within the AnaCredit dataset and are mainly aimed at time-series analysis or consistency checks across observed agents for shared instruments (e.g. syndicated loans).

External plausibility checks

Benchmark value and equivalent value

The external plausibility checks aims at comparing the data submitted in the context of AnaCredit submissions against data reported under other statistical or supervisory reporting frameworks such as the BSI regulation reporting (e.g. Schema A in Belgium). In order to do so both the BSI measure and the AnaCredit measure need to be altered in order to for the amounts to be comparable. This is done by calculating a benchmark value and an AnaCredit equivalent value which are the data from respectively the BSI reporting and the AnaCredit reporting after certain modifications.

These modifications could be filtering and aggregations (e.g. excluding loans to households from BSI items) or corrections for conceptual differences (e.g. corrections on intra-companies, settlement date differences, fiduciary status…).

The figure below highlights the alterations required from the AnaCredit dataset in order to arrive to the AnaCredit equivalent value.

Data quality index

The benchmark value and the AnaCredit value are then compared in order to derive a Data Quality Index (DQI). The DQI measures to what extent the benchmark value and the AnaCredit value are in proportion to each other indicating the likelihood of an issue. This DQI can then also be monitored through time.

At b.fine, our experts assist customers in their regulatory reporting and follow the updates and new requirements from the EBA and ECB meticulously. Do you have any questions on AnaCredit and the new plausibility checks? Don’t hesitate to reach out to our team.


[2] https://www.ecb.europa.eu/pub/pdf/other/ecb.AnaCreditValidationChecks1120~3de2aa121c.en.pdf

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