How Can a Firm Quantitatively Prove Best Execution When Using a Systematic Internaliser?

Concept

The challenge of quantitatively proving best execution when utilizing a Systematic Internaliser (SI) is fundamentally a question of data architecture and analytical integrity. A firm’s decision to route an order to an SI is a decision to engage in a bilateral execution, moving the trade away from the multilateral price discovery of a lit exchange. The core task, therefore, is to construct an evidentiary framework that demonstrates this choice consistently yields a superior, or at minimum equivalent, outcome for the client compared to all other viable alternatives. This requires a system capable of capturing not just the execution data itself, but a high-fidelity snapshot of the entire market landscape at the precise moment of the trade.

An SI is an investment firm that deals on its own account by executing client orders outside a regulated market, MTF, or OTF. It operates as a principal, offering liquidity from its own book. This structure presents both an opportunity and a challenge. The opportunity lies in the potential for price improvement, access to liquidity that may not be present on lit venues, and reduced market impact for large orders.

The challenge is one of transparency and proof. Unlike a central limit order book where the prevailing best bid and offer are publicly visible, an SI’s quotes are provided directly to the client, often through a Request for Quote (RFQ) process. Proving best execution in this environment moves beyond simply recording the transaction price. It requires a dynamic, counterfactual analysis ▴ comparing the price achieved through the SI against the prices that were simultaneously available on the consolidated European tape.

A firm must systematically prove that its bilateral executions are superior to the publicly available alternatives at the moment of trade.

The regulatory framework, specifically MiFID II, mandates that firms take “all sufficient steps” to obtain the best possible result for their clients. This obligation is not waived when using an SI. In fact, the burden of proof becomes more acute. The firm must demonstrate that its selection of an SI as an execution venue is part of a deliberate and effective order execution policy.

This involves a continuous process of monitoring, analysis, and justification. The quantitative proof is derived from a meticulous comparison of the SI execution against a set of predefined benchmarks, primarily the European Best Bid and Offer (EBBO), at the time of execution. The quality of this proof is entirely dependent on the quality of the data captured and the rigor of the analytical models applied.

Strategy

A robust strategy for proving best execution with a Systematic Internaliser is built upon three pillars ▴ a comprehensive data collection protocol, intelligent benchmark selection, and a rigorous counterfactual comparison framework. This strategy must be codified within the firm’s formal Order Execution Policy, providing a clear and defensible methodology for why and when SI liquidity is accessed. The objective is to transform the best execution process from a compliance formality into a system for continuous execution quality improvement.

The Data Collection Protocol

The foundation of any quantitative proof is the underlying data. The strategy must ensure the capture of a complete and time-stamped record of every stage of the order lifecycle. This is a non-trivial data engineering challenge, requiring the integration of information from multiple internal and external systems. The goal is to create a single, unified record for each trade that contains all the necessary data points for a complete post-trade analysis.

Key data points to be captured include:

• Order Inception ▴ The precise timestamp (to the millisecond or finer) when the parent order is created or received by the firm’s Order Management System (OMS).
• Pre-Trade Market State ▴ A snapshot of the consolidated European order book (EBBO) at the moment the decision to route to an SI is made. This includes the best bid and offer, depths, and the venues displaying them.
• RFQ Process ▴ For RFQ-based SIs, all relevant timestamps must be logged, including when the RFQ is sent, when quotes are received, and the full content of each quote from the SI.
• Execution Timestamp ▴ The exact time the trade was executed with the SI.
• Post-Trade Market State ▴ A snapshot of the EBBO immediately following the execution to assess for any potential market impact.

What Are the Most Effective Benchmarks for SI Execution Analysis?

Selecting the right benchmarks is critical for a meaningful analysis. While standard benchmarks like Volume-Weighted Average Price (VWAP) or Arrival Price have their place, they are insufficient on their own for SI analysis. The most critical benchmark is the prevailing market price on lit venues at the moment of execution. This allows for a direct, “apples-to-apples” comparison.

The core of the analysis hinges on comparing the SI’s execution price against the best available prices on public exchanges at the same instant.

The primary benchmarks for SI execution quality are:

1. European Best Bid and Offer (EBBO) ▴ This is the most important benchmark. A buy order executed via an SI should be compared against the best offer available on any European trading venue at the time of the trade. The difference represents the quantifiable price improvement (or detriment).
2. EBBO Midpoint ▴ Comparing the execution price to the midpoint of the EBBO spread provides a measure of how much of the spread the firm was able to capture for the client.
3. Arrival Price ▴ The midpoint of the EBBO at the time the order was first received by the trading desk. Slippage against this benchmark measures the cost of delay and the market movement during the order handling process.

A Comparative View of Execution Venues

To justify the use of an SI, a firm must understand its characteristics relative to other liquidity sources. The decision to use an SI is a strategic choice based on a trade-off between factors like price discovery, potential for price improvement, and information leakage.

Execution

The execution of a quantitative best execution framework for Systematic Internalisers is an operational discipline. It involves translating the firm’s strategic policy into a concrete, repeatable, and auditable process of data analysis and reporting. This process must be systematic, leveraging technology to automate data capture and analysis while enabling human oversight to interpret the results and refine the execution strategy. The ultimate goal is to create a closed-loop system where post-trade analysis directly informs pre-trade decisions.

The Operational Playbook for SI Trade Analysis

A firm must establish a clear, step-by-step procedure for analyzing every trade executed with an SI. This process should be integrated into the firm’s daily operational workflow and form the basis of its periodic regulatory reporting.

1. Data Ingestion and Normalization ▴ The first step is to automatically pull together all the required data points for each SI execution. This involves consolidating trade records from the EMS/OMS, quote data from the SI (often via FIX messages), and market data from a consolidated feed provider. All timestamps must be synchronized to a common clock, typically GPS or PTP, as required by MiFID II.
2. Benchmark Calculation ▴ For each trade, the system must calculate the relevant benchmarks. This means querying the historical market data to retrieve the exact state of the EBBO at the precise millisecond of execution.
3. Quantitative Metric Computation ▴ With the trade data and benchmarks in place, the system computes the core performance metrics. This includes Price Improvement (PI) versus the relevant side of the EBBO, slippage versus Arrival Price, and spread capture versus the EBBO midpoint.
4. Exception Reporting ▴ The system should automatically flag any trades that fail to meet predefined quality thresholds. For example, any trade executed at a price worse than the EBBO, or with significant negative slippage, should be flagged for immediate review by the trading desk and compliance function.
5. Aggregation and Reporting ▴ On a periodic basis (e.g. monthly or quarterly), the individual trade data is aggregated to produce summary reports. These reports, which mirror the logic of RTS 28, provide a high-level view of the execution quality provided by each SI and allow for comparison against other execution venues.

How Should a Firm Structure Its Quantitative Analysis?

The quantitative analysis must be structured to answer the fundamental question ▴ did this SI provide the best possible result for the client? This is achieved through detailed Transaction Cost Analysis (TCA) that focuses on direct, measurable comparisons.

A granular TCA dashboard provides the definitive evidence of execution quality, comparing every SI trade against the available market alternative.

The following table illustrates a simplified TCA dashboard for analyzing a series of trades routed to an SI. This level of detail provides the raw data for proving best execution.

This analysis provides the tangible evidence required. For trades A123, B456, and C789, the firm can clearly demonstrate that the SI provided a better price than was publicly available. For trade D012, while there was no price improvement, the firm can demonstrate that the execution was no worse than the public market and may have been justified by other factors like size and low market impact, which must be documented in the qualitative assessment.

System Integration and Technological Architecture

Delivering this level of quantitative proof requires a sophisticated technological architecture. It is insufficient to rely on manual spreadsheets or disparate data sources. A truly robust system involves the seamless integration of several key components:

• Execution Management System (EMS) ▴ The EMS must be configured to log every child order and execution with high-precision timestamps. It should also be capable of routing RFQs to SIs and capturing the quote responses electronically.
• Market Data Infrastructure ▴ The firm needs access to a high-quality, consolidated European market data feed. This data must be stored in a tick database that can be queried efficiently to reconstruct the state of the market at any point in time.
• TCA Engine ▴ A dedicated Transaction Cost Analysis engine is required to automate the process of fetching trade and market data, performing the calculations, and generating the reports and dashboards illustrated above.
• Compliance and Reporting Tools ▴ The output of the TCA engine should feed directly into the firm’s compliance systems to support the generation of regulatory reports (like the RTS 28 summary) and to provide an auditable trail for regulators.

This integrated system forms the operational backbone of the best execution process. It ensures that the proof is not an occasional, manual exercise but a continuous, automated, and integral part of the firm’s trading workflow.

Reflection

Is Your Data Architecture a Source of Proof or a Source of Liability?

The framework detailed here provides a methodology for constructing quantitative proof of best execution. The exercise of building this capability, however, reveals a deeper truth about a firm’s operational readiness. The ability to perform this analysis is a direct reflection of the sophistication of its underlying data and technology infrastructure. A firm that struggles to gather and synchronize the necessary data is not merely facing a reporting challenge; it is operating with a significant blind spot in its execution strategy.

Consider the systems currently in place within your own organization. Can you, with certainty, reconstruct the full European order book for any given millisecond in the past quarter? Can you automatically link every child execution from an SI back to its parent order and the precise market state at the time of the routing decision?

The answers to these questions determine whether your firm’s best execution policy is a living, data-driven process or a static document. The capacity for rigorous, quantitative proof is the ultimate measure of a firm’s command over its own execution process.