How Has the Deprioritization of RTS 28 Affected Strategic Data Capture Initiatives?

Concept

The operational calculus of institutional trading has been fundamentally altered by the effective sunsetting of the Regulatory Technical Standard 28, commonly known as RTS 28. This regulation, born from the ambitious transparency objectives of MiFID II, mandated a specific, public-facing reporting protocol. Investment firms were required to annually publish detailed information on their top five execution venues for each class of financial instrument, alongside a qualitative assessment of the execution quality obtained.

The design principle was one of external accountability, theoretically empowering clients and regulators to scrutinize and compare execution performance across the market. It established a uniform data format, a common language for venue disclosure, intended to bring a new level of clarity to the often opaque world of order routing.

This system, however, exhibited significant friction in practice. The reports, while comprehensive in their mandate, were found to be cumbersome and of limited utility. A key finding, echoed by both European and UK regulators, was that the intended audience rarely engaged with the data. The sheer volume and complexity of the information, coupled with the inherent delays in its publication, rendered it difficult to use for making timely, meaningful comparisons of execution quality.

For many firms, the process of generating RTS 28 reports devolved into a resource-intensive compliance exercise, a fulfillment of a regulatory requirement rather than a valuable strategic undertaking. The data was being structured for the regulator, not for the firm’s own intelligence apparatus. This created a systemic inertia, where the focus was on meeting the letter of the law, potentially at the expense of innovating in the spirit of best execution.

The deprioritization of RTS 28 marks a pivotal shift from mandated, standardized reporting to a framework demanding self-directed, strategic data intelligence.

Recognizing these shortcomings, the European Securities and Markets Authority (ESMA) issued a public statement in early 2024 advising national competent authorities (NCAs) to deprioritize supervisory actions related to the enforcement of RTS 28 reporting obligations. This move was a direct precursor to the formal removal of the requirement within the broader MiFID II/MiFIR review. It is critical to understand that this action does not dismantle the bedrock principle of best execution. On the contrary, ESMA has been emphatic that the overarching duty for firms to achieve the best possible result for their clients remains fully intact and subject to supervision.

The change is one of mechanism, not of principle. The system is moving away from a prescribed, public disclosure model to one that places the onus of proof and analysis squarely back onto the investment firms themselves.

This deprioritization creates a new operational paradigm. The removal of the mandatory reporting framework clears the path for firms to re-architect their data strategies around internal value creation. Strategic data capture is no longer about populating a standardized template for external consumption. It is now about building a proprietary intelligence engine designed to enhance decision-making, optimize execution pathways, and ultimately, generate alpha.

The core challenge has transformed from “How do we comply with RTS 28?” to “How do we design a data system that provides a persistent, verifiable, and competitive edge in our execution quality?” This is a far more demanding, yet strategically rewarding, undertaking. It requires a move from a static, compliance-oriented mindset to a dynamic, performance-oriented one, where data is the central component of a firm’s trading infrastructure, not a peripheral reporting artifact.

Strategy

The cessation of mandatory RTS 28 reporting necessitates a fundamental strategic recalibration for investment firms. The previous environment fostered a data strategy that was, by its nature, defensive and compliance-centric. The primary objective was the production of a report that would satisfy regulatory scrutiny. In the new landscape, the objective of a data capture initiative becomes offensive and performance-oriented.

The goal is to build a proprietary system of insight that directly informs and enhances every stage of the trading lifecycle. This represents a move from data as a liability to be managed to data as an asset to be exploited.

From Compliance Checkbox to Intelligence Engine

A modern data strategy must now be designed around the core tenets of Transaction Cost Analysis (TCA), venue optimization, and the systematic capture of execution-derived alpha. The focus shifts from merely listing the top five venues to understanding the microscopic dynamics of why certain venues deliver superior results under specific market conditions. This requires a far more granular and high-frequency approach to data collection.

Firms must now architect systems capable of capturing not just the basic execution data required by the old standard, but a rich tapestry of contextual information, including:

• Order Characteristics ▴ Full details of the order at the time of routing, including size, type, limit price, and any specific instructions or constraints.
• Market Conditions ▴ High-frequency snapshots of the order book depth, bid-ask spread, and volatility for the specific instrument at the moment of execution.
• Venue-Specific Data ▴ Latency measurements for order submission and confirmation, fill rates, and the frequency of price improvement versus slippage at each execution venue.
• Post-Trade Analytics ▴ Detailed analysis of price reversion, implementation shortfall, and performance against various benchmarks (e.g. VWAP, TWAP, Arrival Price).

In the absence of a public reporting mandate, the new competitive differentiator becomes the sophistication of a firm’s private data analytics framework.

Architecting a Post-RTS 28 Data Framework

Developing a robust data capture initiative in this new era involves several key strategic pillars. The first is a commitment to technological infrastructure. This means investing in systems that can ingest, normalize, and store vast quantities of time-series data from multiple sources, including market data feeds, order management systems (OMS), and execution management systems (EMS).

The second pillar is a sophisticated analytics layer. This involves deploying advanced statistical tools and, increasingly, machine learning models to identify patterns and anomalies in execution data that would be invisible to the naked eye.

The table below outlines the conceptual shift in data strategy driven by the deprioritization of RTS 28.

The New Role of Governance and Oversight

A third, critical pillar is data governance. With the onus of proof now entirely internal, firms must be able to demonstrate to regulators, auditors, and clients that their best execution process is robust, systematic, and data-driven. This requires a clear and auditable framework for how data is collected, stored, validated, and used in decision-making.

The firm’s Best Execution Committee, once potentially focused on signing off on the annual RTS 28 report, must now evolve into a dynamic, data-centric body that actively uses the firm’s internal analytics to challenge and refine execution policies on an ongoing basis. This strategic shift transforms the best execution obligation from a periodic reporting task into a continuous, integrated, and value-adding operational function.

Execution

Executing a strategic data capture initiative in a post-RTS 28 world is an exercise in system architecture. It requires the deliberate construction of a data pipeline and analytical framework that serves the dual purpose of satisfying the enduring best execution obligation while simultaneously creating a source of competitive intelligence. The focus moves from report generation to the creation of a dynamic feedback loop that continuously informs and improves the trading process.

Building the Data Capture Infrastructure

The foundation of any such initiative is the technological stack. This is a multi-layered system designed to handle the velocity, volume, and variety of modern market and trading data. A successful execution requires careful planning across several domains.

1. Data Ingestion and Normalization ▴ The first step is to establish a robust mechanism for capturing data from all relevant sources. This includes direct market data feeds, FIX protocol messages from the firm’s OMS and EMS, and data from third-party providers. A critical component here is a normalization engine that can translate these disparate data formats into a single, consistent internal schema. Without this, any subsequent analysis will be built on a flawed foundation.
2. Time-Series Database ▴ The heart of the infrastructure is a high-performance time-series database. This technology is specifically designed to store and query the massive datasets generated by financial markets, where every data point is indexed by a nanosecond-precision timestamp. The ability to rapidly query data across specific time windows is essential for effective TCA and venue analysis.
3. The Analytics and Visualization Layer ▴ This is where raw data is transformed into actionable intelligence. This layer should consist of a suite of tools ranging from interactive dashboards for traders to sophisticated statistical modeling environments for quantitative analysts. Visualization tools allow for the intuitive exploration of execution performance, while modeling tools can be used to build predictive models for routing logic or to conduct deep-dive forensic analysis of specific orders.

A Practical Framework for Analysis

With the infrastructure in place, the focus turns to the analytical methodologies. The goal is to create a hierarchy of analysis that serves different functions within the firm, from real-time decision support for traders to periodic strategic reviews by the Best Execution Committee. The following table provides a sample of key analytical modules that a firm should aim to build.

The ultimate execution of a modern data strategy is an integrated system where pre-trade analytics, in-flight monitoring, and post-trade forensics operate as a single, coherent intelligence loop.

The true power of this approach is realized when these modules are integrated. For instance, the findings from post-trade venue analysis can be used to refine the parameters of the pre-trade smart order router. The insights from TCA can inform the development of new algorithmic trading strategies. This creates a virtuous cycle of continuous improvement, driven by data.

This is the ultimate fulfillment of the best execution mandate ▴ a system designed not just to prove that the firm is meeting its obligations, but to ensure that it is constantly striving to exceed them. It transforms the data capture initiative from a cost center into a core component of the firm’s performance-generation machinery.

Reflection

The Intelligence Mandate beyond Compliance

The retreat of the RTS 28 reporting mandate does not create a vacuum; it establishes a new proving ground. Where a standardized report once stood, there is now an imperative for a proprietary, dynamic, and far more potent form of intelligence. The fundamental question for every institutional trading desk has evolved.

It is no longer about demonstrating compliance through a static, annual artifact. The new mandate is to construct an internal system of record and analysis that is so robust, so insightful, and so deeply integrated into the fabric of the trading process that best execution becomes an emergent property of the system itself.

This requires a profound shift in perspective. Data capture ceases to be a task delegated to the compliance or operations department. It becomes a core competency of the front office, as essential as risk management or strategy development. The quality of a firm’s data architecture is now a direct reflection of its commitment to its clients and a primary determinant of its competitive standing.

In this environment, firms that view the removal of RTS 28 as a simple cost-saving measure will find themselves at a significant and growing disadvantage. Those that seize the opportunity to re-architect their data infrastructure around the principles of performance and intelligence will define the next generation of execution excellence. The system has changed, and with it, the definition of what it means to truly master the art of execution.