ISO 20022 XML standards are taking over transaction reporting
20 Jan 2021
Cappitech reviews the move to the ISO 20022 XML standards occurring within transaction reporting regulation
Image: spainter_vfx/stock.adobe.com
The Securities Financing Transactions Regulation (SFTR) go live date in July last year marked the first time an EU transaction reporting regulation went live with only the format available for submissions. This followed the 2018 introduction of the Markets in Financial Instruments Regulation (MiFIR) post-transaction reporting of which submissions to national competent authorities (NCAs) are required to be in XML. In contrast to SFTR, alternative formats such as CSV are available when submitting through licensed approved reporting mechanisms. In addition, existing reporting regimes have in place or may see migrations to XML in the future. Already, the European Markets Infrastructure Regulation (EMIR) REFIT (Level 3) and updates to the Commodity Futures Trading Commission (CFTC) Part 43 and 45 — set to go into effect in 2022 and 2023 — are adding XML requirements for submissions. For EMIR, the addition of ISO 20022 expands existing repository to repository data sharing requirements that are in XML.
Big data, standardisation and report quality
What is leading this move to the ISO 20022 format? The simple answer is standardisation.
Regulatory reporting, especially regimes governing derivatives which came out of the 2009 Pittsburgh G20 Summit, was created to allow sharing of data between submitting firms and regulators. NCAs then use this information to help them analyse trading markets for systemic risk and market abuse. But getting this data is easier said than done.
Complicated reports are the vast arrays of data required for each trade, often well over 100 fields of information. For derivative reporting, this data is submitted to a trade repository (TR) or swap data repository (SDR). Repositories then share the submissions between themselves to create pairing and matching reports.
The pairing reports check for breaks of unique transaction identifiers (UTIs) where only one counterparty has submitted a report. While the matching data reviews for paired UTIs where there are differences in the underlying fields being reported. The repositories then make this information available to be accessed by local NCAs and national regulators. (The chart below illustrates the data flow used for EMIR).
Due to the need for data sharing, regulators have found that data quality of reports is improved through standardising file formats. In the case of EMIR, the European Securities and Markets Authority (ESMA) found deficiencies in matching and pairing reports due to inconsistencies between data formats between TRs which have improved under ISO 20022. ESMA specifically mentioned the reduction of data cleaning and normalisation improving the quality of information.
Global standards
Beyond the ISO 20022 format assisting regulators to monitor transaction reporting data within their jurisdictions, there is also a trend among regulators to harmonise collected information to global standards. In the CFTC Part 43 and 45 updates, many of the new fields being added relate to using global identifiers for identifying products (UPI), counterparties (LEI) and UTIs. While many of these fields exist globally, they are new for the US.
As data fields being used for transaction reporting around the world harmonises, the adoption of the ISO 20022 XML format is expected to make it easier for firms to report across different regimes. Also, as datasets harmonise, regulators will have an easier time sharing top level data between themselves to analyse risks in the greater financial markets.
Big data, standardisation and report quality
What is leading this move to the ISO 20022 format? The simple answer is standardisation.
Regulatory reporting, especially regimes governing derivatives which came out of the 2009 Pittsburgh G20 Summit, was created to allow sharing of data between submitting firms and regulators. NCAs then use this information to help them analyse trading markets for systemic risk and market abuse. But getting this data is easier said than done.
Complicated reports are the vast arrays of data required for each trade, often well over 100 fields of information. For derivative reporting, this data is submitted to a trade repository (TR) or swap data repository (SDR). Repositories then share the submissions between themselves to create pairing and matching reports.
The pairing reports check for breaks of unique transaction identifiers (UTIs) where only one counterparty has submitted a report. While the matching data reviews for paired UTIs where there are differences in the underlying fields being reported. The repositories then make this information available to be accessed by local NCAs and national regulators. (The chart below illustrates the data flow used for EMIR).
Due to the need for data sharing, regulators have found that data quality of reports is improved through standardising file formats. In the case of EMIR, the European Securities and Markets Authority (ESMA) found deficiencies in matching and pairing reports due to inconsistencies between data formats between TRs which have improved under ISO 20022. ESMA specifically mentioned the reduction of data cleaning and normalisation improving the quality of information.
Global standards
Beyond the ISO 20022 format assisting regulators to monitor transaction reporting data within their jurisdictions, there is also a trend among regulators to harmonise collected information to global standards. In the CFTC Part 43 and 45 updates, many of the new fields being added relate to using global identifiers for identifying products (UPI), counterparties (LEI) and UTIs. While many of these fields exist globally, they are new for the US.
As data fields being used for transaction reporting around the world harmonises, the adoption of the ISO 20022 XML format is expected to make it easier for firms to report across different regimes. Also, as datasets harmonise, regulators will have an easier time sharing top level data between themselves to analyse risks in the greater financial markets.
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