How Has the Removal of RTS 27 Reports in the UK Impacted Execution Venue Selection Processes? ▴ Question

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Concept

The operational challenge of achieving and demonstrating superior execution quality has been fundamentally recalibrated within the UK’s financial markets. The removal of Regulatory Technical Standard 27 (RTS 27) reports represents a decisive architectural shift. These reports were conceived as a core data protocol within the MiFID II framework, a standardized mechanism intended to transmit execution quality metrics from venues to the broader market. The design principle was one of transparency through uniformity; by mandating that all execution venues ▴ from lit exchanges to dark pools and systematic internalisers ▴ publish quarterly data sets in a common format, regulators aimed to create a comparable landscape for investment firms to assess venue performance.

This system was designed to solve a genuine problem ▴ information asymmetry in a fragmented market. An investment firm’s best execution obligation is a constant, yet the means of satisfying it are variable and complex. RTS 27 was engineered to provide a public utility of raw data points, covering price, costs, speed, and likelihood of execution for a vast array of financial instruments.

The underlying logic was that with this data, an investment firm could mechanistically compare Venue A against Venue B, optimizing its order routing logic based on empirical evidence and thereby fulfilling its fiduciary duty to clients. The reports were, in essence, a regulatory attempt to build a universal translation layer for venue performance.

The discontinuation of RTS 27 reports signals a move away from mandated, standardized data towards a more principles-based and firm-specific approach to verifying execution quality.

The system’s failure in practice was a lesson in the dynamics of information value. The sheer volume and complexity of the RTS 27 data created a significant signal-to-noise problem. The reports were immensely resource-intensive for venues to produce and equally burdensome for investment firms to ingest and analyze. The data, being quarterly, was often stale on arrival, reflecting market conditions that had long since passed and offering little predictive power for future execution outcomes.

Consequently, the intended consumers of this information ▴ the buy-side firms tasked with venue selection ▴ found the utility of the reports to be exceptionally low. The Financial Conduct Authority (FCA) confirmed that the reports were rarely downloaded or used, making the cost of their production disproportionate to their benefit.

The UK’s decision to abolish this requirement, effective December 1, 2021, was an acknowledgment of this architectural flaw. It was a pragmatic dismantling of a data protocol that failed to deliver actionable intelligence. This act has forced a systemic re-evaluation of how execution quality is measured, monitored, and proven.

The market has transitioned from a state of mandated, low-quality public data to an environment where the onus is placed squarely on the investment firm to construct its own, more sophisticated analytical framework. This requires a fundamental shift in thinking, from passive consumption of standardized reports to the active sourcing and synthesis of diverse, high-frequency data streams to build a proprietary, dynamic view of the execution landscape.

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Strategy

The strategic void left by the abolition of RTS 27 reports necessitates a more robust and intellectually rigorous approach to fulfilling the best execution mandate. Firms can no longer point to a standardized, albeit flawed, public data set as a foundational component of their venue analysis. The new strategic imperative is to build an internal system of intelligence that is both more dynamic and more defensible. This system must be architected around two core principles ▴ the acquisition of superior data and the application of more sophisticated analytical models.

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From Compliance to Competitive Advantage

The previous regime inadvertently fostered a compliance-oriented mindset. The existence of RTS 27 provided a procedural checklist item for venue selection committees. The new environment demands a performance-oriented approach. The goal is to construct a proprietary view of execution quality that yields a competitive edge.

This means moving beyond the static, aggregated metrics of RTS 27 and embracing a more granular, real-time analysis of execution pathways. The focus shifts from what a venue reported it did last quarter to what it is actually doing with a firm’s orders now.

This strategic realignment involves several key shifts:

Data Sovereignty ▴ Firms must take ownership of their data strategy. This involves sourcing execution data directly from brokers and venues, leveraging third-party Transaction Cost Analysis (TCA) providers, and integrating this information into a cohesive internal database. The lack of a standardized format, a direct consequence of RTS 27’s removal, makes data normalization and management a critical new competency.
Qualitative Overlay ▴ The quantitative analysis must be augmented with a structured qualitative assessment. While RTS 27 focused purely on numbers, a modern venue selection framework must systematically evaluate factors like a venue’s participant demographics, its protocols for handling large orders, its resilience during periods of market stress, and the sophistication of its anti-gaming logic.
Dynamic Calibration ▴ Venue selection can no longer be a static, periodic review. It must become a continuous process of monitoring and recalibration. Smart order routers (SORs) and algorithmic trading strategies need to be fed with dynamic, high-frequency data to optimize their routing decisions intra-day.

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How Does the Venue Selection Framework Evolve?

The evolution from a pre- to post-RTS 27 world can be systematized. The table below outlines the strategic transformation in the core components of the venue selection process. It illustrates the move from a passive, report-based methodology to an active, data-driven system.

Table 1 ▴ Strategic Shift in Venue Selection Frameworks
Framework Component	Pre-RTS 27 Approach (Reliance on Standardized Reports)	Post-RTS 27 Approach (Proprietary Intelligence System)
Primary Data Source	Quarterly RTS 27 reports published by venues.	High-frequency, proprietary data from brokers, direct venue feeds, and third-party TCA providers.
Analytical Focus	Historical analysis of standardized, aggregated metrics (e.g. average spread, execution speed).	Real-time analysis of granular metrics, including fill rates, price reversion, and information leakage.
Decision Frequency	Periodic (quarterly or annual) review of venue performance.	Continuous, dynamic monitoring and automated recalibration of order routing logic.
Qualitative Assessment	Ad-hoc and unstructured, often secondary to the quantitative report data.	Systematic and formalized, integrated into the overall venue scoring model.
Regulatory Proof	Demonstrating that RTS 27 reports were reviewed as part of the process.	Maintaining a detailed audit trail of data, analysis, and decision-making within the firm’s internal governance structure.
Technological Requirement	Ability to download and perform basic analysis on large, standardized CSV files.	Sophisticated data infrastructure for ingesting, normalizing, and analyzing diverse data streams in near real-time.

The removal of RTS 27 compels firms to build their own analytical engines, transforming the best execution process from a regulatory burden into a source of alpha.

This strategic pivot places a significant demand on a firm’s technological and quantitative resources. It requires investment in data engineering, analytics platforms, and the human expertise to interpret the results. The ultimate goal is to create a closed-loop system where execution data informs routing strategy, the results of that strategy are measured, and the data from those measurements is used to refine the strategy further. This is the architecture of a modern, intelligent execution framework, one that thrives in the absence of mandated, simplistic reporting.

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Execution

Executing a robust venue selection process in a post-RTS 27 environment is an exercise in system design. It requires the construction of a durable, evidence-based framework that can withstand regulatory scrutiny and deliver superior execution outcomes. This framework is built upon a foundation of deep data analysis and disciplined governance. The process moves from a simple review of public reports to the active management of a firm-specific intelligence platform.

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The Operational Playbook for Venue Analysis

A firm must establish a clear, repeatable process for evaluating execution venues. This process forms the core of the firm’s ability to demonstrate its commitment to the principles of best execution. The following steps provide an operational blueprint:

Data Architecture Assembly ▴ The initial phase is to construct a data pipeline. This involves establishing feeds from all relevant sources.
- Broker Execution Reports ▴ Mandate that all brokers provide detailed, post-trade reports, ideally using a standardized protocol like FIX Tag 851 to identify the ultimate execution venue.
- Direct Venue Feeds ▴ For high-volume relationships, establish direct data feeds from exchanges and other venues to capture market data and execution metrics.
- Third-Party TCA Integration ▴ Contract with specialized Transaction Cost Analysis (TCA) providers who can supply benchmarked data and sophisticated analytics, offering an independent validation of internal findings.
Quantitative Modeling and Analysis ▴ With the data infrastructure in place, the next step is analysis. This moves far beyond the simplistic metrics offered by RTS 27. The goal is to build a multi-factor model for scoring each venue based on the specific characteristics of the orders being routed. A key output is a comparative analytics dashboard.
Qualitative Due Diligence ▴ Numbers alone are insufficient. A formal qualitative review must be conducted for each primary execution venue. This involves assessing operational resilience, counterparty risk, market impact models, and the protocols in place to protect client orders from adverse selection or information leakage. This assessment should be documented and scored.
Governance and Decision Documentation ▴ The outputs of the quantitative and qualitative analyses must be presented to a formal governance body, such as a Best Execution Committee. This committee is responsible for making the final decisions on venue inclusion and tiering. All analysis, meeting minutes, and decisions must be meticulously documented to create a defensible audit trail.

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Quantitative Modeling and Data Analysis

The heart of the new execution framework is a sophisticated, data-rich analytical model. This model must assess venues across multiple dimensions of execution quality. The table below provides an example of a comparative analysis that a firm might produce internally. It uses more advanced metrics than were available in RTS 27 to create a more nuanced picture of venue performance for a specific asset class, such as FTSE 100 stocks.

Table 2 ▴ Multi-Factor Venue Performance Analysis (FTSE 100 Equities, Q3 2025)
Metric	Venue A (Lit Exchange)	Venue B (Dark Pool)	Venue C (Systematic Internaliser)	Definition & Strategic Implication
Price Improvement (%)	0.05%	0.15%	0.12%	Percentage of trades executed at a better price than the prevailing European Best Bid/Offer (EBBO). A higher value indicates better pricing.
Midpoint Fill Rate (%)	N/A	65%	80%	For dark venues, the percentage of orders filled at the midpoint. A higher rate indicates greater access to non-toxic liquidity.
30-Second Reversion (bps)	-0.2 bps	+1.5 bps	+0.5 bps	The average price movement after a trade. A positive value (adverse reversion) may indicate information leakage. A negative or neutral value is preferred.
Average Fill Size (€)	€15,000	€75,000	€50,000	The average size of an individual fill. A larger size is beneficial for executing large orders with minimal market impact.
Information Leakage Score (1-10)	2	7	4	A proprietary score based on pre-trade price movements and post-trade reversion. A lower score is better, indicating less market impact.

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What Is the True Cost of Execution?

This deeper analysis reveals a more complex reality. Venue A offers minimal price improvement but has very low information leakage, making it suitable for the initial stages of a large order. Venue B provides the best price improvement and large fill sizes but suffers from significant adverse reversion, suggesting it is being used by informed traders and poses a high risk of information leakage. Venue C offers a strong balance of midpoint liquidity and controlled market impact.

A sophisticated SOR would use this analysis to dynamically route order slices to the optimal venue based on the parent order’s size, urgency, and market conditions. This level of granular, multi-factor analysis is the operational reality of best execution in the absence of RTS 27.

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References

Financial Conduct Authority. “PS21/20 ▴ Changes to UK MiFID’s conduct and organisational requirements.” 30 November 2021.
Decuyper, Charlotte. “Best execution post-RTS 27 ▴ Building consensus in the industry.” FIXimate, FIX Trading Community, 23 December 2021.
Smith, Victoria. “FCA changes to MiFID II research rules and an end to RTS 27 and RTS 28 best execution reporting.” Cleveland & Co, 21 April 2022.
Global Compliance News. “UK ▴ FCA makes changes to MiFID II research rules and removes RTS 27 and RTS 28 best execution reporting.” Baker McKenzie, 5 January 2022.
DLA Piper. “ESMA publishes statement on reporting requirements under RTS 28 of MiFID II.” 20 February 2024.

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Reflection

The dismantling of the RTS 27 regime in the UK was not an abdication of regulatory oversight. It was a transfer of responsibility. The mandate for transparency remains, but the methodology has been privatized. Each firm is now compelled to become its own data scientist, its own market structure analyst, and the ultimate architect of its execution quality framework.

The question you must now ask of your own operational system is this ▴ is your data architecture robust enough to turn this new responsibility into a source of durable, defensible alpha? The absence of a public standard creates the opportunity to build a superior private one. The quality of that construction will define your execution performance in the years to come.