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Preparing for Data Readiness in Regulatory Compliance: Navigating EMIR, AI Act, and Emerging AI Regulations

By Matt Flenley, Head of Marketing, Datactics

Amid a backdrop of evolving regulatory requirements, and pressure on enterprises to reduce costs associated with manual work, the need for automating data readiness has never been more pressing.

Regulations such as EMIR (European Market Infrastructure Regulation), SFDR (Sustainable Finance Disclosure Regulation) and the EU AI Act rely on data as a key enabler to deliver satisfactory evidence of compliance. Enterprises must balance ensuring that their data management practices are robust and accurate, with automations and efficiencies to minimise the overhead on business operation.

This article digs deep into the challenges, strategies and approaches for regulatory data readiness, highlighting the importance of technological solutions to deliver effective and efficient compliance.

Understanding the key regulations

The European Market Infrastructure Regulation was established to increase transparency and reduce risks in the derivatives market. It mandates the reporting of derivative contracts to trade repositories and the implementation of risk management standards. Non-compliance with EMIR can result in significant penalties, making it essential for organisations to maintain accurate and timely data.

The AI Act, proposed by the European Commission, aims to ensure the safe and ethical use of artificial intelligence. It outlines requirements for high-risk AI systems, including stringent data management practices. As AI technologies become more prevalent, the forthcoming AI regulations will likely introduce additional compliance requirements, emphasising the need for robust data governance.

The Sustainable Finance Disclosure Regulation sets out how financial market participants must disclose sustainability information. It is designed to help investors seeking to put their money into companies and projects supporting sustainability objectives to make informed choices.  The SFDR is also designed to allow investors to properly assess how sustainability risks are integrated in the investment decision process, and ultimately contribute to the EU’s goal of moving the region to a net zero economy.

Challenges in achieving data readiness

Organisations face several challenges in preparing their data for regulatory compliance:

  • Data accuracy and quality: Ensuring data is accurate, complete, and up to date is critical. Inaccurate data can lead to compliance breaches and financial penalties; incomplete or insufficient data can equally lead to penalties often running into tens or even hundreds of millions of dollars.
  • Data integration: Integrating data from various sources, including old or legacy systems, is often complex. Disparate and distributed data silos hinder the ability to provide a single, unified view of compliance-related information.
  • Real-time data processing and reporting: Many regulations require real-time or near-real-time data reporting. Achieving this level of responsiveness necessitates advanced data processing capabilities.
  • Data security and privacy: Protecting sensitive data from breaches and ensuring compliance with data privacy laws is paramount. Organisations must implement stringent security measures to safeguard their data.

Strategic approaches to data readiness

Among the vast array of activities that organisations could engage in, some key recommendations stand out when it comes to adopting certain strategies. These include:

  • Implementing a robust data governance framework:

Establishing clear policies and procedures for data management, including data classification, data quality standards, and roles and responsibilities for data stewardship will help greatly in aligning data readiness activities.

  • Using advanced data management technologies

Technologies such as data lakes, data warehouses, and ETL/ELT (Extract, Transform, Load) tools will help to streamline data integration and management processes. These tools are often a combination of bought (off-the-shelf) and built (internally developed) depending on the need of the enterprise.

  • Setting up continuous data monitoring and auditing

Configure tools and systems for ongoing monitoring of data quality and compliance. Regular audits help identify and address potential issues before they escalate. Some of these can be pre-built internally, others can be through external services or consultancy, or some vendors offer pre-built rules built to specific regulatory requirements and standards to aid such audit processes.

  • Conducting training and awareness programmes

When your people understand that all employees are, in fact, data people, it will help greatly to overcome barriers to adoption. Through careful and considered education, training and assessment of compliance teams and employees on the importance of data readiness, it will help ensure everyone is aware of their roles in maintaining compliance.

What role does technology play in data readiness for regulatory compliance?

The role is pivotal, central and should be complementary to human processes, augmenting and improving regulatory and compliance reporting.

  • AI and Machine Learning

Such technologies can help to automate data quality checks, identify and detect anomalies and outliers, and streamline reporting processes, making compliance more efficient.

  • Cloud-based data management systems

Cloud solutions offer scalability, flexibility, and advanced security features, making them ideal for managing large volumes of compliance data.

What lies in store in the future?

As has been shown in the past, regulatory requirements will continue to evolve. What can enterprises do to best set themselves up for the future? Some ideas are outlined below:

  • Anticipate regulatory changes

Conduct ‘horizon scanning’ to regularly review and update compliance practices to align with new regulations. Early engagement with regulatory bodies will help to understand upcoming changes.

  • Integrate new technologies:

Not everything has to be built from scratch. There are many firms offering some part, or the end-to-end capability to support one or more parts of the data readiness journey for regulatory compliance.

Conclusion
Achieving data readiness for regulatory compliance is a complex but essential task for organisations. At present, much of the work is often manual, delivered on demand and at risk of human error. However, through early engagement, understanding the key regulations, addressing data management challenges, and leveraging advanced technologies, companies can navigate the regulatory landscape with confidence. As regulations and technologies continue to evolve, a proactive approach to data readiness will be crucial for maintaining compliance and ensuring long-term success.

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