ESMA DQR Report Highlights Issues with EMIR and SFTR Data Quality

April 15, 2021

Data Quality Review (DQR) report published by ESMA is first of its kind.

 

ESMA monitors and assesses data quality of regulatory reports provided by TRs. Areas of focus are: completeness, timeliness, availability, adherence to format, and content, and reconciliation.

In the new report ESMA summarises the trends they’ve observed and outline an action plan to improve data quality in the future.

 

EMIR are noting some improvements to data quality, although some issues still persist. Data trends identified by ESMA include:

  • a steady level of late reports;
  • persisting high percentage of non-reported derivatives;
  • slight increase in rejection rates since Brexit;
  • failures to duly terminate trades;
  • improved, although still unsatisfactory reconciliation rates;
  • data quality issues remain

In September 2014 NCAs and ESMA launched a joint Data Quality Action Plan. In 2020 it included 3 areas for review and required NCAs to analyse at least 5 of worst performing counterparties in each category:

  • pairing and matching;
  • completeness, accuracy, timeliness, and rejections;
  • thematic review continued from 2019: valuation and collateral data.

In 2021 NCAs and ESMA will continue their supervisory efforts under the DQAP project, focusing
on those areas where deficiencies have been identified so far.

 

ESMA findings in regards to EMIR data include:

  • Significant number of derivatives that are being reported late:
    • 7% of daily submissions are being reported late;
    • 11 million of open derivatives did not receive daily valuation updates;
    • there tend to be between 3,2 and 3,7 million of open non-reported derivatives on a given reference date during 2020;
  • reporting not in line with the EMIR format and content rules;
  • reported trades do not reconcile or are not reported altogether:
    • Around 47% of open derivatives (totalling circa 20 million open derivatives) are unpaired.

ESMA highlights need for increased efforts on EMIR and SFTR data quality

 

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