How Has the Deprioritization of RTS 27 and 28 Affected Best Execution in Europe?

Concept

The deprioritization of Regulatory Technical Standards (RTS) 27 and 28 marks a pivotal recalibration in the European framework for best execution. It signals a move away from a prescriptive, report-centric model of transparency toward a more principles-based system that places greater emphasis on the internal capabilities and analytical rigor of investment firms. This transition acknowledges a fundamental reality experienced by market participants ▴ the immense operational cost and complexity of producing these reports often outweighed their practical utility for investors or for the enhancement of execution quality. The original intent was to create a common data language for execution performance, yet the result was frequently a deluge of non-standardized, context-poor data that was difficult to compare and rarely consumed.

The Original Blueprint for Transparency

Under the Markets in Financial Instruments Directive II (MiFID II), RTS 27 and 28 were conceived as foundational pillars of a new, transparent European market structure. The objective was to arm investors with detailed information, enabling them to assess how and where their orders were being executed and to hold firms accountable to their best execution obligations. This was a systemic attempt to codify and standardize the measurement of execution quality across a fragmented landscape of trading venues and investment firms.

RTS 27 the Venue’s Diagnostic Report

RTS 27 required execution venues ▴ such as stock exchanges, multilateral trading facilities (MTFs), and systematic internalisers (SIs) ▴ to publish quarterly reports detailing a vast array of execution quality metrics. These reports were designed to be the raw material for analysis, containing granular data on prices, costs, speed, and likelihood of execution for individual financial instruments. The vision was for this data to allow firms and their clients to conduct objective, data-driven comparisons of venue performance, forming a quantitative basis for venue selection and execution routing decisions.

RTS 28 the Firm’s Execution Footprint

Complementing the venue-specific data of RTS 27, RTS 28 mandated that investment firms publish annual reports summarizing their execution practices. These reports identified the top five execution venues used for each class of financial instrument and included a qualitative summary of the execution quality obtained. The goal was to provide clients with a clear picture of their broker’s execution policies in practice, fostering competition based on demonstrated execution performance. It was a mechanism for accountability, forcing firms to disclose their routing decisions and justify them with an analysis of the results achieved.

The suspension of these reporting mandates reflects a regulatory acknowledgment that true execution quality is a dynamic process, not a static report, demanding a shift in focus from public disclosure to internal analytical mastery.

Systemic Flaws in the Data Protocol

Despite their laudable goals, the RTS 27 and 28 frameworks exhibited significant operational and conceptual flaws from the outset. The immense volume and granularity of RTS 27 data made it exceptionally costly for venues to produce and for firms to ingest and analyze. More critically, a lack of strict standardization in data formatting and content meant that comparing reports from different venues was often an exercise in reconciling disparate datasets, a task that required significant resources and expertise.

Stakeholder feedback, cited by both the UK’s Financial Conduct Authority (FCA) and the European Securities and Markets Authority (ESMA), consistently highlighted that these reports were rarely downloaded or used by end-investors. The information was often perceived as too complex, outdated by the time of publication, and lacking the necessary context to draw meaningful conclusions about execution quality. For many firms, the process became a compliance exercise ▴ a fulfillment of a regulatory obligation ▴ rather than a meaningful tool for improving client outcomes. This divergence between regulatory intent and practical reality ultimately led to the consensus that the system required a fundamental rethink.

Strategy

The removal of the mandatory RTS 27 and 28 reporting obligations instigates a significant strategic re-evaluation for investment firms. The operational focus transitions from a compliance-driven task of external reporting to the strategic imperative of building and maintaining a robust internal best execution monitoring framework. This change elevates the importance of a firm’s proprietary data and analytical capabilities, transforming best execution from a periodic disclosure exercise into a continuous, data-driven process of internal scrutiny and optimization. The responsibility for proving best execution has not diminished; rather, the methodology for demonstrating it has become more internalized and sophisticated.

The Shift from Public Mandate to Proprietary Intelligence

With the disappearance of the standardized, albeit flawed, public datasets, the strategic high ground now belongs to firms that can cultivate superior internal intelligence. The core of this strategy involves treating execution data not as a resource for regulatory reports, but as a critical input for a dynamic feedback loop. This loop consists of capturing high-quality trade data, analyzing it to measure performance, and using the resulting insights to refine execution policies, algorithms, and venue choices. The emphasis is on creating a self-improving system, where every trade contributes to a deeper understanding of market dynamics and execution pathways.

Recalibrating the Analytical Engine Transaction Cost Analysis

Transaction Cost Analysis (TCA) moves from being a supplementary tool to the central analytical engine for best execution. While previously TCA could be benchmarked against or supplemented by RTS 27 data, it now stands as the primary quantitative methodology for evaluating execution performance. A modern TCA framework must go beyond simple price metrics. It involves a multi-dimensional analysis that considers:

• Implicit Costs ▴ Measuring market impact and slippage against relevant benchmarks (e.g. arrival price, interval VWAP). This quantifies the hidden costs of executing a trade.
• Explicit Costs ▴ Tracking commissions, fees, and taxes associated with each execution to provide a complete picture of total cost.
• Execution Speed and Certainty ▴ Analyzing the time taken to execute an order and the fill rates achieved, which are critical factors for certain trading strategies.
• Venue Performance ▴ Using TCA data to conduct rigorous, like-for-like comparisons of execution quality across different venues, moving beyond the high-level summary that RTS 28 provided.

The Emerging Data Ecosystem

The void left by RTS 27 and 28 is being filled by a growing ecosystem of third-party data and analytics providers. These vendors aggregate and normalize vast amounts of market data, offering sophisticated TCA and peer-to-peer benchmarking services. The strategic decision for firms is no longer just about internal analysis but also about how to leverage these external resources effectively.

Engaging with these providers can offer a broader market context, allowing a firm to compare its execution performance against an anonymized peer group. This provides a powerful tool for identifying areas of underperformance and validating the effectiveness of its execution strategies in a way that the old reporting regime never could.

Firms must now architect their own systems of proof, relying on sophisticated internal analytics and curated external data to demonstrate their commitment to client outcomes.

Qualitative Factors a Renewed Emphasis

The deprioritization of quantitative reports paradoxically increases the importance of qualitative assessment. Without a universal, albeit imperfect, quantitative benchmark, regulators and clients will place greater weight on a firm’s documented policies and the rationale behind its execution decisions. The strategic response requires a comprehensive and well-articulated execution policy that details not just what factors are considered, but how they are weighted and balanced.

This includes assessing venue resilience, technological capabilities, risk controls, and the quality of their customer service. The ability to articulate and document this qualitative diligence becomes a key component of the overall best execution strategy.

This strategic realignment is summarized in the table below, contrasting the old and new paradigms.

Execution

In the post-RTS 27/28 environment, the execution of a best execution policy is an exercise in systemic integrity. It requires the deliberate construction of an internal framework that is both robust in its data handling and sophisticated in its analytical output. The focus shifts from producing a static, public-facing artifact to maintaining a dynamic, internal system of record and analysis that can withstand regulatory scrutiny and, more importantly, drive continuous performance improvements for clients. The obligation to achieve the best possible result remains unchanged; what has evolved is the toolkit and the methodology for proving it.

Reinforcing the Internal Execution Framework

The practical implementation of a modern best execution framework rests on several key pillars. This is an architectural challenge, requiring firms to integrate data capture, analytics, and governance into a cohesive operational process. The objective is to create a closed-loop system where execution data is systematically collected, rigorously analyzed, and the resulting intelligence is fed back into the decision-making process for venue and algorithm selection.

Upgrading Internal Data Capture and Storage

The foundation of any credible best execution framework is high-quality, granular data. Firms must ensure their systems capture a complete lifecycle of every order. This is a far more demanding task than simply compiling data for an annual report. Key data points to capture include:

1. Order Timestamps ▴ Millisecond or even microsecond precision for order receipt, routing to venue, execution, and final confirmation.
2. Benchmark Prices ▴ The prevailing market price at the moment the order is received (the arrival price) and at various points during its execution.
3. Routing Information ▴ A detailed log of where the order was sent, including any re-routes, and the specific execution algorithm used.
4. Fill Details ▴ The price, size, and venue of each partial and final fill.

This data must be stored in an accessible and queryable format, allowing for both real-time monitoring and historical analysis.

Advanced Analytics and Peer Benchmarking

With a robust dataset, the next step is to deploy advanced analytics. This means moving beyond simple average price comparisons. A sophisticated TCA platform should be capable of “apples-to-apples” comparisons by normalizing for different market conditions, order sizes, and stock volatilities. This allows for a much fairer and more insightful assessment of venue and algorithm performance.

Furthermore, integrating data from external vendors allows for powerful peer group analysis. Seeing how a firm’s execution costs for a specific type of trade compare to an anonymized industry average provides invaluable context and helps to identify systemic strengths and weaknesses in the firm’s execution strategy.

The deprioritization of RTS 27 and 28 does not lower the bar for best execution; it raises the bar for how firms must internally measure, validate, and govern it.

The Governance Overlay Documenting the Rationale

The final and most critical layer of execution is governance. The data and analysis are only valuable if they are used to inform decisions within a structured oversight process. Best Execution Committees or similar governance bodies must meet regularly to review the outputs of the TCA system. Their role is to interpret the data, challenge underperformance, and make documented decisions about the firm’s execution policy.

The documentation of this process is paramount. Regulators will expect to see a clear audit trail showing not just the quantitative analysis but the qualitative judgments made based on that analysis. This includes the rationale for using certain venues, the calibration of trading algorithms, and the overall strategy for achieving best execution for different types of clients and instruments.

The table below provides a granular look at the factors that a modern, data-driven governance process should consider.

Reflection

The phasing out of the RTS 27 and 28 reporting mandates represents more than a mere reduction in administrative tasks. It is a fundamental re-architecting of the philosophy behind best execution oversight in Europe. The system is moving from a state of enforced, standardized public disclosure to one that champions internal, proprietary, and continuous self-assessment.

This evolution presents a profound challenge and a significant opportunity. The challenge lies in cultivating the internal discipline, technological infrastructure, and analytical expertise to build a monitoring framework that is demonstrably superior to the one it replaces.

The opportunity is for firms to reclaim the narrative of best execution. It allows them to move beyond a check-the-box compliance mentality and forge a genuine competitive advantage through superior execution quality. The ultimate measure of success in this new landscape will not be the ability to produce a report, but the ability to answer a simple, yet profound question from a client or a regulator ▴ “How do you know you achieved the best possible result?” The quality of that answer will depend entirely on the integrity of the internal system a firm has chosen to build.