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19th April 2023

2022 Report on Quality and Use of Transaction Data

Press Release: ESMA finds data quality significantly improves under new monitoring approach

  •  3rd annual edition

    • New approach to data monitoring:

      • More data-driven and outcome-focused approach to data monitoring

      • Collaborating with the NCAs on data quality issues

      • Centralised data quality dashboard

        • EU-wide indicators covering the most fundamental data quality aspects under EMIR

        • Data sharing framework that enables relevant authorities to follow up with counterparties when potentially significant data quality issues are detected

      • Significant quality improvements

      • Increased use of transaction data by EU financial regulatory authorities

    • New: analysis of MiFiR transaction data

  Report: 2022 Report on Quality and Use of Transaction Data 19/04/2023

  1. How is the reported data used?

    • NCAs, ECB and ESRB

      • Monitoring of;

        • Key trends in EU derivatives markets (2.2.1)

        • Derivatives exposures (2.2.2)

          • E.g. tools to monitor financial exposures of funds, CCPs, financial intermediaries and other financial market participants

        • Market abuse behaviour (2.2.3)

        • Risk of specific segments and asset types (2.2.4)

          • E.g. assess the impact of the 2020 short selling bans jointly by the AFM and AMF

        • Reporting obligation (2.2.5)

          • e.g. timeliness and completeness of reporting.

          • Performed through the implementation of dashboards with indicators automatically flagging any issues

    • ESMA

      • Macro-level research, support of policymaking and supervision/supervisory mandates. E,g,

        • Reports

          • Trends, Risk and Vulnerabilities report (TRV) (2.3.1)

            • semi-annual report on market-level risks to consumers, market integrity and financial stability risks

          • Archegos (2.3.2)

            • Report on default of Archegos (US family office) and affects on EU cptys

          • Markets reports (2.3.3)

            • Previously “statistical” reports

        • Policymaking

          • Carbon markets and Derivatives Trading Obligation (DTO) (2.3.4)

          • Reporting of  CDS prices (2.3.5)

        • Supervision (2.3.6)

          • Direct supervisory mandates: e.g. TRs, ARMs and APAs

          • support NCAs supervisory mandates of reporting participants

        • Monitoring

          • Transparency data monitoring (from APAs)  (2.3.7)

          • Retail risk monitoring (2.3.8)

  2. ESMA’s new approach to monitoring data quality

    • Data quality dashboards (3.2)

      • EMIR started in May 2022

      • SFTR to be implemented in 2023

      • Compares data quality for a country against EU benchmark

      • Contains 19 Data Quality Indicators (DQIs) e.g.

        • under-reporting

        • over-reporting

        • inconsistent reporting vis-à-vis the other counterparty

        • incomplete information in the key fields of the reports

        • late reporting

        • abnormal values

        • incorrect identifiers of the counterparties

      • Results are presented to and discussed with the NCAs experts

    • NCAs data sharing and follow-up on significant data quality issues (3.3)

      • Goal: ensure resolution of the most critical data quality problems

      • Criteria has been set to determine which reporting issues should be considered significant

      • Follow-up is focused on a limited # of entities with the highest volume of incorrect reports at EU level

      • Individual entities may be approached, e.g. when they report abnormal/incorrect values on such a scale that it may materially impact the analysis of EMIR data

      • Framework used 4 times since 2022;

        • Implausible notional/quantity and incorrect margins under EMIR

        • Abnormal number of reports submitted by a single entity under EMIR

        • Implausible loan values under SFTR

        • EMIR DQIs indicating issues for 67 entities in 18 Member States

          • # of trades vs # of positions

          • empty/abnormal maturity date

          • 0 valuation

  3. Key developments affecting data quality

    • EMIR

      • EMIR Refit (4.1.1)

        • Guidelines, xml schema, validations all publish Dec 22 – to give market time to prepare for data quality before go live.

        • Guidelines: facilitate ensuring compliance with the revised rules

      • EMIR DQIs (4.1.2)

        • DQI 1: discrepancies # of level T records between two counterparties

          • Worst = 25% in Sep-21. Dec-22 = 15%

        • DQI 2: discrepancies # of level P records between two counterparties

          • Worst = 27.6% in Mar-20, Dec-22 = 7.8%

        • DQI 8 – late valuations

          • Worst = 38.3% in Mar-20, Dec-22 = 13.2%

        • DQI 9 – missing or abnormal maturity

          • Fluctuates between 10% and 16% of data

        • DQI 10 – missing valuations

          • Worst = 23.8% in 2019, 2022= 14.3%

      • Misreporting of notional/quantity (4.1.2.2)

        • Implausible values identified from 1 entity in fields ‘Notional’ and ‘Quantity’ for CO FU records

        • Affecting a large percentage of EU CO FU flow

        • Inconsistencies in use of collateral update records also identified

        • ESMA spoke with NCA who spoke with entity directly

      • EMIR Remediation (from supervisory reviews) (4.1.3)

        • Incorrect data in TSR reports from TRs (4.1.3.1)

        • TR filtering data before sending to ESMA (4.1.3.2)

        • TR data ingestion issues (4.1.3.3)

    • SFTR

      • Closing of Unavista SFTR (4.1.4)

      • ESMA revalidation of SFTR format (4.1.5)

    • MiFIR

      • Supervisor of significant DRSPs (4.2.1)

        • ESMA now responsible for supervision of DRSPs (previously was NCAs)

        • ARMs = 50%+ of flow of MiFIR TR in EU. The remaining reported directly by investment firms or trading venues.

      • Timeliness of publication (APA) (4.2.2)

        • Minimal delay in the dissemination of trade information to the public.

      • Analysis of MiFIR data affecting policy making

        • Insights from the analysis of CDS prices (4.2.3)

        • Publication of transparency data by Systematic Internalisers (SIs) (4.2.4)

        • Lessons learnt from the analysis of MiFIR transaction data for the carbon markets report (4.2.5)

      • Consistency of transaction and transparency data (4.2.6)

        • Project underway – results expected in Q1 2023

      • APAs Transparency data outliers (4.2.7)

        • ESMA test bonds: avg volume is in line with similar products in the same market

        • Outliers excluded from transparency calcs

  4. Conclusion and next steps

    • “ESMA plans to further intensify and industrialise the use of transaction data and to explore innovative ways to obtain greater intelligence from the reported data”

    • Expand use of EMIR DQIs in 2023

    • SFTR DQIs in 2023

    • Prepare dashboard for REFIT

    • Monitor TRs reports