Concept
The dissolution of the Regulatory Technical Standard (RTS) 28 reporting mandate has been misinterpreted by some as a relaxation of a firm’s duty to its clients. This perspective is fundamentally incorrect. The core, unshakeable obligation to deliver best execution persists, with regulatory bodies in both the United Kingdom and the European Union affirming its central importance. The change is not one of substance but of method.
The era of performative, public reporting via standardized templates has ended. It is superseded by a new paradigm demanding a more sophisticated, internalized, and continuous demonstration of execution quality. Firms are no longer judged on their ability to complete a form, but on their capacity to build and maintain a dynamic, evidence-based execution framework.
This evolution requires a profound shift in thinking. Best execution is a continuous process, woven into the fabric of a firm’s trading and investment lifecycle. It is the demonstrable outcome of a series of sufficient steps taken to secure the best possible result for a client, considering a spectrum of factors. While price and cost are primary considerations, particularly for retail clients where total consideration is the paramount metric, the institutional calculus is more complex.
The nature of the order, its size, the prevailing market liquidity, the speed of execution, and the certainty of settlement all constitute critical variables in the best execution equation. The removal of RTS 28 elevates the importance of a firm’s own Order Execution Policy (OEP), transforming it from a static disclosure document into the central pillar of its compliance and strategic execution architecture. The onus is now squarely on the firm to prove, at any given moment, that its systems, choices, and outcomes are calibrated to achieve this superior result for its clients.
The fundamental duty to secure the best possible outcome for clients remains, shifting the focus from public reporting to a robust, internal evidence-based framework.
This new environment compels firms to look inward, to rigorously interrogate their own processes. The key question has changed from “What must we report?” to “How can we prove our value and diligence?” Answering this requires a system of verifiable evidence. It demands a culture where execution quality is not an afterthought reviewed annually, but a live, monitored variable. Every decision, from the selection of a counterparty to the choice of an execution algorithm, must be justifiable within the context of the firm’s OEP and supported by a robust audit trail.
This is a higher bar to clear. It requires investment in technology, data analysis, and governance, moving the proof of best execution from a public relations exercise to a core operational discipline.
Strategy
The Primacy of the Order Execution Policy
In the post-RTS 28 landscape, the Order Execution Policy (OEP) is elevated from a compliance document to the central strategic charter for all execution activities. It is the constitution upon which the entire framework for demonstrating best execution is built. A modern OEP must be a living document that provides a granular, defensible rationale for the firm’s execution strategy. It must explicitly detail, for each class of financial instrument, the relative importance assigned to the various execution factors ▴ price, costs, speed, likelihood of execution, settlement finality, and any other pertinent considerations.
The policy must also provide clear justification for the selection of execution venues, counterparties, and any third-party brokers. A generic statement about seeking the best outcome is no longer sufficient. The policy must articulate the how ▴ the specific processes, criteria, and monitoring systems in place to consistently deliver on the best execution promise. This includes a clear methodology for handling potential conflicts of interest and a robust process for periodic review to ensure the policy remains effective amid changing market conditions.
A Multi-Layered Monitoring Framework
Demonstrating best execution requires a continuous, multi-layered monitoring framework that spans the entire lifecycle of a trade. This is a significant departure from the static, backward-looking nature of RTS 28 reporting. The strategy involves three distinct temporal layers:
- Pre-Trade Analysis ▴ This is the forward-looking component. Before an order is placed, firms must leverage analytical tools to estimate potential transaction costs, market impact, and risks associated with different execution strategies. This involves analyzing historical data, current market liquidity, and volatility to select the most appropriate execution algorithm and venue. The ability to document this pre-trade decision-making process is a critical piece of evidence.
- Real-Time Monitoring ▴ During the execution of an order, particularly for large or complex trades, firms must have systems in place to monitor progress against pre-defined benchmarks in real time. This allows for intra-flight adjustments to the execution strategy if market conditions change or if the order is not being filled as expected. Alerts and dashboards that track slippage against a benchmark like Volume-Weighted Average Price (VWAP) are essential components of this layer.
- Post-Trade Analysis ▴ This is the most data-intensive layer, where Transaction Cost Analysis (TCA) comes to the forefront. Post-trade analysis provides the definitive quantitative evidence of execution quality. It involves comparing the execution price against a variety of benchmarks to measure performance. Crucially, this analysis must feed back into the pre-trade layer, creating a virtuous circle where insights from past trades inform future execution strategies.
The Evolution of Transaction Cost Analysis
Transaction Cost Analysis (TCA) has evolved from a simple reporting tool into a core strategic component of the best execution framework. Its role is to provide objective, quantitative proof of performance. A sophisticated TCA strategy goes far beyond a single benchmark.
It employs a suite of metrics to build a complete picture of execution quality. The choice of benchmark is critical and must be appropriate for the order type and the client’s instructions.
Firms must now implement a continuous, multi-layered monitoring system that integrates pre-trade analytics, real-time oversight, and comprehensive post-trade Transaction Cost Analysis.
The table below illustrates some common TCA benchmarks and their strategic applications, highlighting how a multi-benchmark approach provides a more nuanced view of performance than a single metric ever could.
| Benchmark | Description | Strategic Application | Best Suited For |
|---|---|---|---|
| Arrival Price / Implementation Shortfall | Measures the difference between the decision price (when the order was generated) and the final execution price, including all commissions and fees. | Provides the most complete picture of total trading cost and captures the full market impact of an order. It is the gold standard for measuring the performance of a portfolio manager’s decision. | Assessing the overall cost of implementing an investment decision. |
| Volume-Weighted Average Price (VWAP) | The average price of a security over a specific time period, weighted by volume. The goal is to execute at or better than the market’s average price. | Used for orders that are a small percentage of the day’s expected volume and where minimizing market impact is a key objective. | Passive, less urgent orders where the goal is to participate with the market. |
| Time-Weighted Average Price (TWAP) | The average price of a security over a specific time period, calculated by breaking the order into smaller, equal chunks executed over the period. | Useful in markets with lower liquidity or when a VWAP profile is unpredictable. It aims to reduce market impact by spreading trades out over time. | Orders in less liquid securities or when seeking to avoid a volume-driven execution pattern. |
| Market on Close (MOC) | Measures performance against the official closing price of the security. | Essential for index funds and other strategies that need to track a closing benchmark price as closely as possible. | Trades that are benchmarked to the closing price. |
Integrating Qualitative Factors
While quantitative analysis is critical, a purely numbers-driven approach is insufficient. The best execution obligation requires firms to consider a range of qualitative factors that are not easily captured by TCA. These factors are often just as important in achieving the best overall outcome for a client. A robust strategy involves systematically assessing and documenting these qualitative aspects of execution.
This documentation serves as crucial evidence that the firm considered the full context of the trade, not just the final price. The governance process must ensure that these qualitative assessments are performed consistently and are given appropriate weight in the overall evaluation of execution quality.
| Qualitative Factor | Description | Method of Assessment and Documentation |
|---|---|---|
| Likelihood of Execution | The probability that an order of a certain size and type can be completed without adversely affecting the market. | Documenting the choice of venue or counterparty based on their historical fill rates and demonstrated ability to handle large block orders in the specific instrument. |
| Speed of Execution | The time taken from order routing to execution confirmation. This is particularly important in fast-moving markets. | System logs tracking order latency. Comparison of execution speeds across different venues and brokers for similar order types. |
| Settlement and Counterparty Risk | The risk that a trade fails to settle or that the counterparty defaults on its obligations. | Maintaining a rigorous counterparty due diligence process. Monitoring settlement failure rates and the creditworthiness of counterparties. Documenting the rationale for using specific counterparties. |
| Information Leakage | The risk that information about a large order leaks to the market before it is fully executed, leading to adverse price movements. | Analysis of post-trade price reversion. Preferential use of execution methods designed to minimize information leakage, such as dark pools or specific algorithmic strategies. |
Execution
The Operational Playbook for Demonstrating Compliance
With the onus of proof now fully internalized, firms require a clear, repeatable operational playbook to demonstrate best execution compliance. This is not a theoretical exercise; it is a set of concrete actions and systems that create a defensible, evidence-based framework. The following steps represent a robust model for implementation.
- Codify the Execution Philosophy in the OEP ▴ The Order Execution Policy must be treated as the foundational document. It needs to be reviewed and enhanced to move beyond generic statements. For each asset class, it must explicitly define the criteria for venue and counterparty selection, detail the hierarchy of execution factors, and describe the governance process for its oversight. This document becomes the reference against which all execution outcomes are measured.
- Establish a Data-Driven Monitoring System ▴ Firms must invest in the technological infrastructure to capture, store, and analyze execution data. This system should integrate data from the Order Management System (OMS), Execution Management System (EMS), and any third-party TCA providers. The goal is to create a single source of truth for all trading activity, enabling comprehensive post-trade analysis.
- Define Execution Quality Thresholds ▴ It is essential to move from subjective assessment to objective measurement. The firm must define specific, quantifiable thresholds for acceptable execution quality. For example, a threshold might be set for the maximum acceptable slippage against a VWAP benchmark for a certain type of order. When these thresholds are breached, an automated alert should trigger a formal review process.
- Implement a Robust Governance and Committee Structure ▴ Best execution cannot be the sole responsibility of the trading desk. A formal governance structure, typically involving a Best Execution Committee, is required. This committee should be composed of senior members from trading, compliance, risk, and technology. It is responsible for reviewing the output of the monitoring systems, investigating any breaches of the quality thresholds, and approving any changes to the OEP or execution strategies. The minutes of these committee meetings form a critical part of the audit trail.
- Create a Demonstrable Audit Trail ▴ Every step of the process, from the pre-trade analysis to the post-trade review, must be documented and auditable. This includes storing the rationale for specific execution strategy choices, the real-time monitoring logs, the full TCA reports, and the minutes and decisions of the governance committee. In the event of a regulatory inquiry, this audit trail is the firm’s primary evidence of its commitment to the best execution obligation.
Quantitative Modeling and Data Analysis
The core of the new best execution paradigm is deep quantitative analysis. This requires moving beyond high-level summary statistics to granular, order-by-order examination. The tables below provide a glimpse into the level of detail required for a robust quantitative framework. They are designed to work together to build a multi-dimensional view of execution performance, from the individual trade level up to the strategic assessment of venues and algorithms.
A rigorous, evidence-based approach requires the implementation of a formal governance structure, including a Best Execution Committee, to oversee the entire process.
Table 1 ▴ Granular TCA Benchmark Analysis
This table demonstrates a detailed post-trade analysis for a single, large institutional order to buy 500,000 shares of a hypothetical stock, XYZ Corp. It breaks down the execution into multiple fills and compares the performance against several key benchmarks, providing a rich, multi-faceted view of the execution quality.
| Fill ID | Time | Quantity | Execution Price | Arrival Price Slippage (bps) | Interval VWAP Slippage (bps) | Commissions (£) |
|---|---|---|---|---|---|---|
| F-001 | 09:35:12 | 50,000 | £10.015 | -15.0 | -2.5 | £25.00 |
| F-002 | 10:15:45 | 100,000 | £10.020 | -20.0 | +1.0 | £50.00 |
| F-003 | 11:05:22 | 150,000 | £10.025 | -25.0 | +1.5 | £75.00 |
| F-004 | 14:30:18 | 100,000 | £10.030 | -30.0 | -0.5 | £50.00 |
| F-005 | 16:00:05 | 100,000 | £10.035 | -35.0 | +2.0 | £50.00 |
| Total/Avg | N/A | 500,000 | £10.027 (Avg) | -27.0 (Avg) | +0.3 (Avg) | £250.00 |
| Analysis Summary ▴ Arrival Price (Decision Time 09:30:00) ▴ £10.000. Total Implementation Shortfall ▴ 27 bps + Commissions. The positive slippage against interval VWAP suggests the algorithm successfully captured liquidity at favorable prices within each trading period, even as the overall market drifted upwards. | ||||||
Table 2 ▴ Venue Performance Scorecard
Firms must continuously evaluate the performance of the execution venues they use. This scorecard provides a model for a quarterly review, combining quantitative TCA data with qualitative factors to create a holistic performance rating. This evidence is crucial for justifying the venue choices outlined in the OEP.
| Execution Venue | Price Improvement (%) | Avg. Speed (ms) | Fill Rate (%) | Settlement Fail Rate (%) | Qualitative Score (1-5) | Weighted Overall Score |
|---|---|---|---|---|---|---|
| Venue A (Lit Market) | 0.05% | 50 | 98.5% | 0.1% | 4.0 | 4.10 |
| Venue B (MTF) | 0.15% | 75 | 95.2% | 0.2% | 4.5 | 4.35 |
| Venue C (Dark Pool) | 0.25% | 150 | 85.0% | 0.1% | 3.5 | 3.95 |
| Venue D (Systematic Internaliser) | 0.10% | 25 | 99.8% | 0.05% | 4.8 | 4.55 |
| Note ▴ Weighted score based on firm-defined priorities (e.g. Price 40%, Speed 20%, Fill Rate 20%, Settlement 10%, Qualitative 10%). Venue D is the top performer this quarter due to its high speed, reliability, and strong qualitative assessment, despite not offering the highest price improvement. | ||||||
Predictive Scenario Analysis ▴ A Case Study
Consider a portfolio manager at a large institutional asset manager who needs to sell a 1.5 million share position in a mid-cap technology stock, “Innovate PLC,” which has an average daily volume of 5 million shares. The manager’s directive is to minimize market impact while ensuring the position is liquidated by the end of the trading day. The decision to sell is made at 8:45 AM, with the market opening at 9:00 AM. The arrival price is noted at £25.50.
The execution team immediately begins its pre-trade analysis. Using their TCA platform, they run simulations for various execution strategies. A simple TWAP strategy is projected to have a market impact of 15 basis points, while a more aggressive, front-loaded VWAP strategy is estimated to have an impact of 25 basis points but with a higher probability of completion. Given the significant size of the order relative to the daily volume (30%), the team is concerned about information leakage.
They decide on a hybrid strategy. The core of the order will be executed using a sophisticated “adaptive shortfall” algorithm that balances participation with the market’s volume profile against opportunistic liquidity seeking. This algorithm will be programmed to be more aggressive in the morning when liquidity is typically higher and more passive in the afternoon. To further minimize impact, the team will route 20% of the order to a selection of dark pools, accessed via a smart order router that pings multiple venues simultaneously for non-displayed liquidity.
As the market opens, the execution begins. The real-time monitoring dashboard comes to life. The adaptive algorithm begins working the order, participating in the opening auction and then scaling back its participation rate as initial volatility subsides. By 11:00 AM, approximately 40% of the order has been executed at an average price of £25.45, slightly underperforming the VWAP benchmark for that period but with minimal market impact.
The dashboard shows that the stock’s price has remained stable, indicating low information leakage. However, at 11:30 AM, unexpected positive news about a competitor hits the market, and the entire tech sector begins to rally. Innovate PLC’s price jumps to £25.70. The real-time alert system flags a significant deviation from the execution schedule.
The head of the execution desk confers with the portfolio manager. The original goal was to minimize impact, but the changing market dynamics present an opportunity. They decide to adjust the algorithm’s parameters to be more aggressive, increasing its participation rate to take advantage of the rising price and the influx of new buyers. The smart order router also finds a significant block of liquidity in a dark pool, executing 200,000 shares at £25.72, a price that would have been impossible to achieve on the lit market without causing a significant price disturbance.
The execution continues throughout the afternoon, with the algorithm dynamically adjusting to liquidity and price movements. The final portion of the order is completed just before the closing auction. The post-trade TCA report is generated the next morning. The volume-weighted average sale price for the entire order was £25.65.
The implementation shortfall against the original arrival price of £25.50 was a positive 59 basis points, a testament to the successful adaptation to changing market conditions. The report details every fill, the venues used, and the performance against multiple benchmarks. It shows that the dark pool fills contributed significantly to the positive result. This entire process, from the initial pre-trade simulation to the final TCA report and the documented decision to change strategy mid-flight, is compiled into a single execution file. This file is the definitive proof that the firm not only sought but actively managed the execution process to achieve a superior result for the client, far exceeding what a simple, static execution plan could have delivered.
System Integration and Technological Architecture
Delivering and proving best execution in the modern era is a technological challenge. It requires a seamless, integrated architecture where data flows efficiently between systems. At the heart of this architecture is the interplay between the Order Management System (OMS) and the Execution Management System (EMS). The OMS is the system of record for the portfolio manager’s investment decisions, while the EMS is the trader’s tool for working the order in the market.
For best execution purposes, these systems must be tightly integrated. When an order is passed from the OMS to the EMS, it must carry with it a rich set of data, including the decision time and arrival price, which are critical inputs for TCA.
The Financial Information eXchange (FIX) protocol is the lingua franca of this communication. Specific FIX tags are used to pass this critical data. For instance, Tag 60 (TransactTime) is used to record the precise moment an order is sent to the market, which is essential for calculating arrival price slippage. The EMS, in turn, must be connected to a wide range of liquidity sources, including lit exchanges, MTFs, dark pools, and systematic internalisers.
It also needs to house a suite of sophisticated execution algorithms. The data from every execution fill, including venue, price, quantity, and time, is captured by the EMS and must be fed back into a central data warehouse. This data warehouse is the engine for the TCA platform. It normalizes data from various sources and provides the foundation for the quantitative analysis.
APIs (Application Programming Interfaces) play a crucial role in this ecosystem, allowing the firm’s proprietary systems to connect with third-party TCA providers, market data vendors, and risk management tools. This integrated technological stack is the operational backbone that makes a robust, evidence-based best execution framework possible.
References
- European Securities and Markets Authority. (2025). “ESMA publishes Final Report and Final Draft RTS on investment firms’ order execution policies”.
- European Securities and Markets Authority. (2024). “ESMA clarifies certain best execution reporting requirements under MiFID II”.
- Macfarlanes LLP. (2021). “The UK’s post-Brexit balancing act begins with MiFID II”.
- M&G plc. (2019). “MiFID II Best Execution RTS28 Disclosures”.
- TRAction Fintech. (2024). “RTS 27 and 28 ▴ The 2024 Status of These Reports in UK and EU”.
- Cleveland & Co. (2022). “FCA changes to MiFID II research rules and an end to RTS 27 and RTS 28 best execution reporting”.
- Financial Conduct Authority. (2021). “PS21/20 ▴ Changes to UK MiFID’s conduct and organisational requirements”.
- eflow Global. (2021). “Best execution and beyond – What’s happening to RTS 27 & 28 post-Brexit?”.
Reflection
From Mandate to Mandate
The removal of a prescriptive reporting standard does not diminish the underlying mandate; it elevates it. The obligation has transformed from a task of disclosure to a mission of demonstration. This requires a fundamental re-evaluation of a firm’s internal capabilities. Is your Order Execution Policy a document of intent or a detailed, defensible blueprint for every trading decision?
Does your governance structure merely review past performance, or does it actively shape future execution strategy based on empirical evidence? The data and tools necessary to navigate this new landscape exist. The defining question is whether firms possess the operational framework and the institutional will to integrate them into a coherent system. The ultimate proof of best execution is found not in a historical report, but in the quality and integrity of the living, breathing system that produces the client’s outcome.
Glossary
Best Execution
Execution Quality
Order Execution Policy
Compliance
Audit Trail
Governance
Execution Strategy
Execution Policy
Execution Strategies
Market Impact
Average Price
Transaction Cost Analysis
Post-Trade Analysis
Transaction Cost
Quantitative Analysis
Order Execution
Management System
Arrival Price
