To rewrite or not to rewrite is no longer the question
July 2023
Big changes are afoot in the European compliance space — they will come from the west and sweep their way east. All will change, affirms Paul Rennison, director of product management at deltaconX
Image: elnur/stock.adobe.com
Dramatic license aside, the coming years will bring enormous changes for those involved in compliance and regulatory reporting. The programme of global regulatory rewrites aims to create a more stable and sustainable global financial system, while promoting economic growth and increasing transparency to protect consumers and investors. At the start of the wave is the Commodity Futures Trading Commission Rewrite, from the US. From Europe, the EMIR REFIT will follow, and we’ll end with MAS, HKMA and ASIC from Asia.
What will the new reporting landscape look like when the waters subside? What could be swept away?
As the Chinese proverb says: ‘May you live in interesting times’ — that we certainly do.
The methods behind how firms report and how they are assessed will completely change, from regulator to firm and back to regulator. We’ll also witness an increase in the use of modern technologies, especially AI.
However, like a trip to the doctors, there is often pain before the medicine is prescribed, and a cure is seldom instant.
Similarly, in the financial markets, while firms may face short-term challenges in an effort to adapt to these changes, the long-term benefits can outweigh the costs.
These changes have been influenced by several key drivers including:
Technological advancements: Rapid technological progress has significantly disrupted traditional industries and created new ones. Technologies like AI, blockchain and big data analytics have changed the way businesses operate — necessitating updated regulations to address potential risks and opportunities.
Globalisation: The increasing interconnectivity of economies has resulted in a higher degree of cross-border trade and investment. This demands more harmonised and efficient regulatory frameworks to ensure global financial stability while minimising the risk of regulatory arbitrage.
Lessons from past crises: The 2008 Financial Crisis exposed weaknesses in existing regulatory systems, leading to a renewed focus on enhancing financial stability, tightening the oversight of financial institutions and strengthening investor protections.
Evolving societal values: The growing focus on ESG issues, such as climate change and income inequality, has led regulators to integrate these concerns into their rule-making processes.
Cost: It is very expensive for global firms to meet their regulatory obligations, as they have to maintain multiple separate data sets collected from multiple source systems. It has become a high risk and high cost to monitor, manage and maintain these ecosystems.
Lack of efficiency: The current reporting architecture is inefficient and doesn’t support its primary goal, which is to ensure that the regulators have a clear line of sight across the trading positions of their members and are able to take quick action if alarms are triggered.
These changes have been influenced by several key drivers including:
Technological advancements: Rapid technological progress has significantly disrupted traditional industries and created new ones. Technologies like AI, blockchain and big data analytics have changed the way businesses operate — necessitating updated regulations to address potential risks and opportunities.
Globalisation: The increasing interconnectivity of economies has resulted in a higher degree of cross-border trade and investment. This demands more harmonised and efficient regulatory frameworks to ensure global financial stability while minimising the risk of regulatory arbitrage.
Lessons from past crises: The 2008 Financial Crisis exposed weaknesses in existing regulatory systems, leading to a renewed focus on enhancing financial stability, tightening the oversight of financial institutions and strengthening investor protections.
Evolving societal values: The growing focus on ESG issues, such as climate change and income inequality, has led regulators to integrate these concerns into their rule-making processes.
Cost: It is very expensive for global firms to meet their regulatory obligations, as they have to maintain multiple separate data sets collected from multiple source systems. It has become a high risk and high cost to monitor, manage and maintain these ecosystems.
Lack of efficiency: The current reporting architecture is inefficient and doesn’t support its primary goal, which is to ensure that the regulators have a clear line of sight across the trading positions of their members and are able to take quick action if alarms are triggered.
Standardisation and harmonisation
The industry drive toward standardisation has been led by the Committee on Payments and Market Infrastructures (CPMI) and the International Organization of Securities Commissions (IOSCO).
They have been working together to standardise regulatory reporting to increase the efficiency, transparency and stability of financial markets.
Their aim has been to standardise and harmonise the framework for reporting, with the express goal of removing the inefficiencies and isolation of each reporting regime.
The key areas intended to be enhanced are:
Harmonisation: Creating a globally consistent framework for reporting, therefore reducing the differences between jurisdictions and making it easier for market participants to comply with regulations.
Data quality: The standardisation process aims to improve the quality of reported data by providing clear guidance on reporting requirements and data definitions. This would enable regulators to better monitor and analyse the risks associated with financial market activities.
Timeliness: With standardised reporting, regulators can access data quickly and efficiently, enabling them to respond to emerging risks and challenges in a timely manner.
Risk reduction: By having a clear and standardised reporting framework, financial market participants can better understand and manage their risks, leading to greater overall stability in the financial system.
It’s all about the data
The introduction of standardised data definitions, or common data elements (CDEs), is a central tenet of the route to standardisation which the industry should laud. The macro intentions are sound and will lead to a more sensible regime, in time.
However, while the introduction of CDEs into global regulatory transaction reporting can offer several benefits to firms, there are some potential negatives that need to be considered.
These include:
Implementation costs: Adopting CDEs may require firms to invest in new systems, tools or technologies to ensure their data is consistent with the standardised definitions and formats. This can lead to substantial upfront costs, particularly for smaller firms with limited resources.
Staff training and expertise: Firms may need to invest in staff training and development to ensure employees are knowledgeable about the new data standards and reporting requirements. This can be time consuming and may divert resources from other strategic initiatives.
Data integration and transformation: Firms may face challenges in integrating CDEs into their existing data systems, particularly if they have multiple legacy systems or data silos. This will require significant effort to ensure data consistency and accuracy while avoiding duplication and errors.
Ongoing maintenance and updates: Regulatory reporting requirements and data standards are subject to change. Firms will need to stay up-to-date with any revisions to CDEs and adapt their systems and processes accordingly, which can be resource-intensive.
Loss of proprietary information: In some cases, the adoption of CDEs may require firms to share proprietary information or unique data elements with regulators, which could raise concerns about competitive advantages or intellectual property protection.
Privacy and data security concerns: The increased standardisation and sharing of data through the use of CDEs may raise concerns about data privacy and security. Firms will need to ensure that they have robust data protection measures in place to comply with relevant regulations and safeguard sensitive information.
Limited flexibility: While CDEs aim to simplify and harmonise reporting requirements, they may not adequately address the unique needs or circumstances of individual firms or industries. This could lead to a one-size-fits-all approach that does not fully capture the specific risks or nuances of certain market participants.
Short-term impacts of implementation include:
Increased compliance costs: Firms may face higher compliance costs as they adapt to new regulatory requirements. This could involve investing in new technology, updating internal processes or hiring additional staff.
Enhanced stability and resilience: New regulations aimed at promoting financial stability and reducing systemic risk can help create a more resilient business environment.
Improved market access: Harmonised regulations can facilitate cross-border trade and investment, creating new opportunities for firms to expand their global footprint.
Shift in business models: Firms may need to re-evaluate their business models and strategies in response to new regulations. This could lead to new market opportunities or the need to pivot to different industries or sectors.
The role of AI
Rewrites have been introduced to drive ambiguity out of reporting by increasing the number of fields being reported. They have also been introduced to standardise how fields are described. This will increase the amount of data that regulators are going to have to monitor and analyse — this is where timing and advances in technology can combine their strengths. Regulators, like all firms, are utilising AI technology to improve both the amount of data they can survey, but also to increase their options for the speed and depth of their analysis.
AI has driven harmonisation and standardisation globally. It has also underpinned a move toward more prescriptive models. Its presence has already helped regulators to analyse data at a greater speed, enabling patterns to be detected earlier. This will only continue.
Regulators are also leveraging AI to reduce systemic risk. By employing AI techniques, they can identify potential risks or compliance issues and make more informed decisions.
The key areas intended to be enhanced are:
Anomaly detection: AI algorithms can automatically detect unusual patterns or outliers in transaction data that may indicate potential market abuse, fraud or other irregular activities. This allows regulators to identify potential risks and take corrective action at a faster rate than previously possible.
Network analysis: Regulators can use AI-powered network analysis tools to map out relationships and connections among various market participants. This helps them understand the interconnectedness of the financial system and identify potential sources of systemic risk.
Risk modelling and prediction: AI techniques can help regulators build more sophisticated risk models to predict potential risks and vulnerabilities in the financial system. By incorporating advanced analytics and machine learning, these models can provide more accurate and timely insights for regulatory decision-making.
Supervisory automation: AI-powered tools can automate certain aspects of regulatory supervision, such as monitoring compliance with reporting requirements or analysing financial statements, enabling regulators to focus their resources on more complex or high-risk activities.
Regulatory reporting: AI can help regulators streamline their own reporting processes, making it easier for firms to submit accurate and complete data. By improving data quality, regulators can enhance their ability to analyse transactions and identify potential risks.
Cross-border data sharing and collaboration: AI can facilitate data sharing and collaboration among regulators in different jurisdictions, enabling them to identify and address global systemic risks.
We are just at the start of AI’s journey, and no one can be sure where it will lead. In the short term it will add strings to the regulators’ bow, ensuring a clearer view of the systemic risks in our market.
This phase of rewrites has just started, and there is much work to be done. In the long run our goals are sound — we should all benefit from the changes. However, there are always some pain points after any major operation.
What will the new reporting landscape look like when the waters subside? What could be swept away?
As the Chinese proverb says: ‘May you live in interesting times’ — that we certainly do.
The methods behind how firms report and how they are assessed will completely change, from regulator to firm and back to regulator. We’ll also witness an increase in the use of modern technologies, especially AI.
However, like a trip to the doctors, there is often pain before the medicine is prescribed, and a cure is seldom instant.
Similarly, in the financial markets, while firms may face short-term challenges in an effort to adapt to these changes, the long-term benefits can outweigh the costs.
These changes have been influenced by several key drivers including:
Technological advancements: Rapid technological progress has significantly disrupted traditional industries and created new ones. Technologies like AI, blockchain and big data analytics have changed the way businesses operate — necessitating updated regulations to address potential risks and opportunities.
Globalisation: The increasing interconnectivity of economies has resulted in a higher degree of cross-border trade and investment. This demands more harmonised and efficient regulatory frameworks to ensure global financial stability while minimising the risk of regulatory arbitrage.
Lessons from past crises: The 2008 Financial Crisis exposed weaknesses in existing regulatory systems, leading to a renewed focus on enhancing financial stability, tightening the oversight of financial institutions and strengthening investor protections.
Evolving societal values: The growing focus on ESG issues, such as climate change and income inequality, has led regulators to integrate these concerns into their rule-making processes.
Cost: It is very expensive for global firms to meet their regulatory obligations, as they have to maintain multiple separate data sets collected from multiple source systems. It has become a high risk and high cost to monitor, manage and maintain these ecosystems.
Lack of efficiency: The current reporting architecture is inefficient and doesn’t support its primary goal, which is to ensure that the regulators have a clear line of sight across the trading positions of their members and are able to take quick action if alarms are triggered.
These changes have been influenced by several key drivers including:
Technological advancements: Rapid technological progress has significantly disrupted traditional industries and created new ones. Technologies like AI, blockchain and big data analytics have changed the way businesses operate — necessitating updated regulations to address potential risks and opportunities.
Globalisation: The increasing interconnectivity of economies has resulted in a higher degree of cross-border trade and investment. This demands more harmonised and efficient regulatory frameworks to ensure global financial stability while minimising the risk of regulatory arbitrage.
Lessons from past crises: The 2008 Financial Crisis exposed weaknesses in existing regulatory systems, leading to a renewed focus on enhancing financial stability, tightening the oversight of financial institutions and strengthening investor protections.
Evolving societal values: The growing focus on ESG issues, such as climate change and income inequality, has led regulators to integrate these concerns into their rule-making processes.
Cost: It is very expensive for global firms to meet their regulatory obligations, as they have to maintain multiple separate data sets collected from multiple source systems. It has become a high risk and high cost to monitor, manage and maintain these ecosystems.
Lack of efficiency: The current reporting architecture is inefficient and doesn’t support its primary goal, which is to ensure that the regulators have a clear line of sight across the trading positions of their members and are able to take quick action if alarms are triggered.
Standardisation and harmonisation
The industry drive toward standardisation has been led by the Committee on Payments and Market Infrastructures (CPMI) and the International Organization of Securities Commissions (IOSCO).
They have been working together to standardise regulatory reporting to increase the efficiency, transparency and stability of financial markets.
Their aim has been to standardise and harmonise the framework for reporting, with the express goal of removing the inefficiencies and isolation of each reporting regime.
The key areas intended to be enhanced are:
Harmonisation: Creating a globally consistent framework for reporting, therefore reducing the differences between jurisdictions and making it easier for market participants to comply with regulations.
Data quality: The standardisation process aims to improve the quality of reported data by providing clear guidance on reporting requirements and data definitions. This would enable regulators to better monitor and analyse the risks associated with financial market activities.
Timeliness: With standardised reporting, regulators can access data quickly and efficiently, enabling them to respond to emerging risks and challenges in a timely manner.
Risk reduction: By having a clear and standardised reporting framework, financial market participants can better understand and manage their risks, leading to greater overall stability in the financial system.
It’s all about the data
The introduction of standardised data definitions, or common data elements (CDEs), is a central tenet of the route to standardisation which the industry should laud. The macro intentions are sound and will lead to a more sensible regime, in time.
However, while the introduction of CDEs into global regulatory transaction reporting can offer several benefits to firms, there are some potential negatives that need to be considered.
These include:
Implementation costs: Adopting CDEs may require firms to invest in new systems, tools or technologies to ensure their data is consistent with the standardised definitions and formats. This can lead to substantial upfront costs, particularly for smaller firms with limited resources.
Staff training and expertise: Firms may need to invest in staff training and development to ensure employees are knowledgeable about the new data standards and reporting requirements. This can be time consuming and may divert resources from other strategic initiatives.
Data integration and transformation: Firms may face challenges in integrating CDEs into their existing data systems, particularly if they have multiple legacy systems or data silos. This will require significant effort to ensure data consistency and accuracy while avoiding duplication and errors.
Ongoing maintenance and updates: Regulatory reporting requirements and data standards are subject to change. Firms will need to stay up-to-date with any revisions to CDEs and adapt their systems and processes accordingly, which can be resource-intensive.
Loss of proprietary information: In some cases, the adoption of CDEs may require firms to share proprietary information or unique data elements with regulators, which could raise concerns about competitive advantages or intellectual property protection.
Privacy and data security concerns: The increased standardisation and sharing of data through the use of CDEs may raise concerns about data privacy and security. Firms will need to ensure that they have robust data protection measures in place to comply with relevant regulations and safeguard sensitive information.
Limited flexibility: While CDEs aim to simplify and harmonise reporting requirements, they may not adequately address the unique needs or circumstances of individual firms or industries. This could lead to a one-size-fits-all approach that does not fully capture the specific risks or nuances of certain market participants.
Short-term impacts of implementation include:
Increased compliance costs: Firms may face higher compliance costs as they adapt to new regulatory requirements. This could involve investing in new technology, updating internal processes or hiring additional staff.
Enhanced stability and resilience: New regulations aimed at promoting financial stability and reducing systemic risk can help create a more resilient business environment.
Improved market access: Harmonised regulations can facilitate cross-border trade and investment, creating new opportunities for firms to expand their global footprint.
Shift in business models: Firms may need to re-evaluate their business models and strategies in response to new regulations. This could lead to new market opportunities or the need to pivot to different industries or sectors.
The role of AI
Rewrites have been introduced to drive ambiguity out of reporting by increasing the number of fields being reported. They have also been introduced to standardise how fields are described. This will increase the amount of data that regulators are going to have to monitor and analyse — this is where timing and advances in technology can combine their strengths. Regulators, like all firms, are utilising AI technology to improve both the amount of data they can survey, but also to increase their options for the speed and depth of their analysis.
AI has driven harmonisation and standardisation globally. It has also underpinned a move toward more prescriptive models. Its presence has already helped regulators to analyse data at a greater speed, enabling patterns to be detected earlier. This will only continue.
Regulators are also leveraging AI to reduce systemic risk. By employing AI techniques, they can identify potential risks or compliance issues and make more informed decisions.
The key areas intended to be enhanced are:
Anomaly detection: AI algorithms can automatically detect unusual patterns or outliers in transaction data that may indicate potential market abuse, fraud or other irregular activities. This allows regulators to identify potential risks and take corrective action at a faster rate than previously possible.
Network analysis: Regulators can use AI-powered network analysis tools to map out relationships and connections among various market participants. This helps them understand the interconnectedness of the financial system and identify potential sources of systemic risk.
Risk modelling and prediction: AI techniques can help regulators build more sophisticated risk models to predict potential risks and vulnerabilities in the financial system. By incorporating advanced analytics and machine learning, these models can provide more accurate and timely insights for regulatory decision-making.
Supervisory automation: AI-powered tools can automate certain aspects of regulatory supervision, such as monitoring compliance with reporting requirements or analysing financial statements, enabling regulators to focus their resources on more complex or high-risk activities.
Regulatory reporting: AI can help regulators streamline their own reporting processes, making it easier for firms to submit accurate and complete data. By improving data quality, regulators can enhance their ability to analyse transactions and identify potential risks.
Cross-border data sharing and collaboration: AI can facilitate data sharing and collaboration among regulators in different jurisdictions, enabling them to identify and address global systemic risks.
We are just at the start of AI’s journey, and no one can be sure where it will lead. In the short term it will add strings to the regulators’ bow, ensuring a clearer view of the systemic risks in our market.
This phase of rewrites has just started, and there is much work to be done. In the long run our goals are sound — we should all benefit from the changes. However, there are always some pain points after any major operation.
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