How Should a Buy-Side Firm’s Best Execution Policy Evolve to Account for Systematic Internalisers?

Concept

The formalization of the Systematic Internaliser (SI) regime under MiFID II represents a fundamental alteration of the European market structure, compelling a buy-side firm’s best execution policy to evolve from a static document into a dynamic, data-driven operational framework. The mandate is to recalibrate the very logic of execution, moving beyond a simple hierarchy of venues to a sophisticated system of contingent decision-making. This is an environment where principal liquidity from SIs coexists with lit markets, multilateral trading facilities (MTFs), and dark pools, each with distinct characteristics.

An execution policy confined to a pre-MiFID II worldview fails to harness the potential of this fragmented landscape and, more critically, fails to adequately defend its execution outcomes. The core of the issue is that SIs introduce a bilateral, quote-driven liquidity source that operates outside the continuous central limit order book paradigm, demanding a new analytical lens and a more granular approach to proving best execution.

The Systematic Internaliser as a Structural Reality

A Systematic Internaliser is an investment firm that, on an organised, frequent, systematic, and substantial basis, deals on its own account when executing client orders outside a regulated market, an MTF, or an organised trading facility (OTF). This definition is not merely regulatory jargon; it describes a specific market function. An SI acts as a principal, taking the other side of a client’s trade. This liquidity is proprietary.

The firm is putting its own capital at risk. This structural distinction is paramount. Unlike an agency broker who finds a counterparty in the market, the SI is the counterparty. The evolution of a best execution policy begins with the full assimilation of this fact. The policy must codify the firm’s approach to interacting with principal liquidity, acknowledging both the opportunities, such as potential price improvement and size discovery, and the inherent complexities, like the potential for information leakage and the challenge of comparing a bilateral quote to a multilateral, anonymous order book.

From Venue Checklist to Liquidity Ecosystem

Historically, many execution policies were constructed as a checklist of approved venues, often with a static preference for lit markets. The modern, SI-aware policy must instead be framed as a guide to navigating a complex liquidity ecosystem. It must recognize that the “best” execution outcome is a function of the order’s specific characteristics (size, instrument, urgency) mapped against the available liquidity sources at a precise moment in time. The policy’s role shifts from dictating a fixed path to defining the principles and data inputs that a firm’s execution systems, particularly its Smart Order Router (SOR), will use to find the optimal path in real-time.

This requires the policy to articulate the firm’s philosophy on accessing different liquidity types. For instance, it must specify the conditions under which the SOR should query SIs, how it should evaluate their quotes against the European Best Bid and Offer (EBBO), and what constitutes a meaningful price improvement that justifies routing to an SI over a lit exchange.

A firm’s execution policy must transition from a static venue list to a dynamic framework that governs real-time interaction with a diverse liquidity ecosystem.

This transition necessitates a deep integration of pre-trade and post-trade analytics. The policy can no longer be a high-level statement of intent. It must be a living document, directly informing the configuration of trading systems and continuously refined by the outputs of Transaction Cost Analysis (TCA). It must answer difficult questions ▴ How do we measure the performance of an SI?

What are the key metrics? How do we account for the implicit costs of information leakage when dealing with a principal? Answering these questions transforms the policy from a compliance document into the central nervous system of the firm’s trading function, ensuring that the fiduciary duty to achieve the best possible result for clients is met with demonstrable rigor in a market defined by its complexity.

Strategy

Integrating Systematic Internalisers into a best execution framework is a strategic imperative that extends far beyond mere compliance. It requires a fundamental recalibration of a buy-side firm’s entire approach to order execution, transforming the policy from a static document into the strategic blueprint for a dynamic, data-centric trading operation. The objective is to construct a system that can intelligently and verifiably navigate a fragmented liquidity landscape to consistently deliver optimal outcomes. This involves a deliberate evolution in three core areas ▴ the definition of execution objectives, the analytical tools used to measure success, and the logic embedded within the firm’s execution technology.

From Static Rules to Dynamic Routing Logic

A legacy best execution policy often relies on a rigid, hierarchical set of rules for routing orders. For example, it might dictate that all orders below a certain size must first be routed to a specific lit market. The inclusion of SIs renders this approach obsolete. The strategic shift is toward a policy that defines principles and objectives, which then empower a Smart Order Router (SOR) to make dynamic, context-aware decisions.

The policy itself becomes a higher-level governance layer, setting the parameters within which the execution algorithm operates, rather than prescribing its every move. This requires the policy to be rewritten to accommodate conditional logic, specifying the “if-then” scenarios for engaging SIs. For instance, the policy might state that for a liquid equity, the SOR should query available SIs, but only route to an SI if its quote represents a price improvement over the EBBO that exceeds a specified threshold, and only for a portion of the order to mitigate signaling risk.

A New Mandate for Pre-Trade and Post-Trade Analytics

A robust SI strategy is built upon a foundation of comprehensive data analysis. The policy must mandate the systematic collection and evaluation of execution data that goes far beyond simple price comparisons. It necessitates a new generation of Transaction Cost Analysis (TCA) that can meaningfully compare execution quality across fundamentally different venue types. This means moving from measuring simple arrival price slippage to incorporating SI-specific metrics.

The policy must explicitly require the monitoring of these factors to create a feedback loop that constantly refines the SOR’s logic and the firm’s overall execution strategy. The table below illustrates the evolution of data requirements for a modern execution policy.

Codifying the SI Engagement Protocol

A critical component of the evolved strategy is the formal codification of an SI engagement protocol within the best execution policy. This protocol acts as the firm’s rulebook for interacting with these principal liquidity sources. It removes ambiguity and ensures a consistent, defensible approach. Such a protocol would be structured as a set of clear directives.

• Selection Criteria ▴ The policy must define the quantitative and qualitative criteria for selecting which SIs the firm will connect to. This includes factors like the breadth of instruments covered, historical performance on price improvement, and the robustness of their technology and reporting.
• Quoting Requirements ▴ The protocol should specify that SIs must be able to provide quotes that are firm, executable, and adhere to the MiFID II quote obligations for price, size, and speed.
• Tiering of SIs ▴ Based on ongoing TCA, the policy should allow for the dynamic tiering of SIs. High-performing SIs might receive a greater share of order flow, while underperformers could be downgraded or removed from the SOR’s routing table.
• Information Leakage Mitigation ▴ The protocol must outline the firm’s strategy for minimizing signaling risk. This could involve rules on minimum order size, limiting the number of SIs queried simultaneously, or using randomized routing patterns.

The strategic integration of SIs demands that the best execution policy evolves into a governance document for a dynamic, data-driven system of execution.

This strategic evolution ensures that the firm is not merely “using” SIs, but is integrating them into a coherent and optimized execution process. The policy becomes the central document that links the firm’s fiduciary duty to its technological capabilities and analytical rigor, creating a framework where every execution decision is part of a deliberate, evidence-based strategy. The ultimate goal is a system where the choice to execute via an SI is a conscious, justifiable decision that can be proven to be in the client’s best interest, supported by a wealth of empirical data.

Execution

The operational execution of an SI-aware best execution policy represents the translation of strategic principles into concrete, auditable workflows and technological configurations. This is where the theoretical framework is subjected to the realities of market mechanics, data processing, and regulatory scrutiny. A firm’s ability to demonstrate compliance and achieve superior execution hinges on the granular details of this implementation. It requires a tripartite focus on the pre-trade decision architecture, the post-trade analytical engine, and the overarching governance structure that binds them together.

The Pre-Trade Decision Matrix a Smart Order Router’s Logic

The core of the execution framework is the firm’s Smart Order Router (SOR). The best execution policy must directly inform the logic of the SOR, transforming it from a simple liquidity seeker into a sophisticated decision engine. The SOR’s process for handling an order in this environment is a multi-stage analytical cascade.

The very structure of the SI regime, designed to enhance competition, presents a paradox ▴ does concentrating flow to a select number of high-volume SIs ultimately recreate the very liquidity fragmentation it sought to mend, albeit in a more opaque, bilateral form? The data from RTS 28 reports, while extensive, often lacks the contextual richness to definitively answer this, forcing firms into a continuous, iterative process of analysis and adaptation where the ‘best’ venue is a probabilistic target, not a fixed point.

1. Order Decomposition ▴ Upon receiving a parent order (e.g. buy 200,000 shares of a FTSE 250 stock), the SOR first analyzes its characteristics. Is it a high-touch or low-touch order? What is the order size relative to the average daily volume (ADV)? What is the client-specified urgency? This initial assessment determines the overall execution strategy (e.g. aggressive, passive, scheduled).
2. Pre-Trade Liquidity Mapping ▴ The SOR conducts a comprehensive sweep of all potential liquidity sources. This includes polling the lit market order books for depth and price, checking for available volume in registered MTFs and dark pools, and, critically, sending a request for quote (RFQ) to the firm’s chosen roster of SIs. This is a simultaneous data gathering exercise.
3. Application of Policy Filters ▴ The SOR then applies the rules codified in the best execution policy. It compares the SI quotes to the current EBBO. Let’s say the EBBO is 100.0p / 100.2p. An SI might return a quote to buy at 100.05p. The policy filter checks if this 0.05p improvement meets the firm’s minimum threshold for what constitutes “meaningful” price improvement. It also checks the quoted size against the order’s requirements.
4. Optimal Pathway Construction ▴ Based on the filtered data, the SOR constructs an execution plan. It will not simply send the entire order to the venue with the best price. To manage market impact and information leakage, it will slice the parent order into multiple child orders. For our 200,000 share order, the SOR might decide:
   • Send a 50,000 share child order to the SI that offered price improvement for immediate execution.
   • Place a 75,000 share child order into a dark pool, resting passively to capture liquidity without signaling.
   • Work the remaining 75,000 shares on the lit market using a VWAP algorithm over the next hour.
5. Continuous Re-evaluation ▴ This is not a one-time decision. The SOR continuously monitors market conditions and the execution of the child orders. If the dark pool fills are slow, it may re-route that portion to the lit market. If a new, better SI quote becomes available, it may dynamically adjust the plan. This iterative process is the hallmark of a truly smart execution system.

Transaction Cost Analysis the SI Performance Ledger

Post-trade analysis provides the empirical evidence to justify the SOR’s decisions and to refine its logic over time. A generic TCA report is insufficient. The execution framework must mandate a specific suite of analytics designed to evaluate SI performance with precision. The goal is to build a detailed performance ledger for each SI the firm interacts with, allowing for objective, data-driven comparisons.

The Governance and Oversight Framework

The final pillar of execution is a robust governance structure, typically centered around a Best Execution Committee. This committee is responsible for the ongoing oversight of the firm’s execution arrangements and policy. Its role is to interpret the data provided by TCA and make strategic decisions. The execution policy must empower this committee and define its operational mandate.

• Regular Performance Reviews ▴ The committee must meet on a scheduled basis (e.g. quarterly) to review aggregated TCA reports. This review should compare the performance of all execution venues, including a direct comparison of SIs against lit markets and MTFs on a like-for-like basis.
• Deep-Dive Analysis ▴ If an SI consistently underperforms on key metrics like reversion or fill rates, the committee must commission a deep-dive investigation. This could lead to the SI being placed on a “watchlist” or having its share of order flow reduced.
• SOR Logic Calibration ▴ The committee provides the strategic direction for calibrating the SOR. For example, based on TCA data, they might decide to increase the minimum price improvement threshold required to route to SIs, or to adjust the maximum order size that can be sent to a single SI.
• Policy Attestation ▴ The committee is ultimately responsible for reviewing and attesting to the effectiveness of the best execution policy annually. This process must be documented, providing a clear audit trail that demonstrates the firm is actively monitoring and correcting any deficiencies in its execution arrangements.

This comprehensive execution framework ensures that the firm’s engagement with Systematic Internalisers is not a leap of faith, but a calculated, measured, and continuously optimized process. It creates a defensible system where technology, data, and human oversight converge to meet the fundamental obligation of best execution in a complex and evolving market. The system is designed for proof.

Reflection

The Policy as a System of Intelligence

Ultimately, the evolution of a best execution policy in the age of Systematic Internalisers is a reflection of the firm’s own evolution. It marks a transition from viewing compliance as a static obligation to embracing it as a dynamic system of intelligence. The document itself is merely the output, the written artifact of a much deeper institutional capability. The real asset is the underlying framework of data analysis, technological integration, and critical oversight that produces it.

This framework does not provide simple answers; it provides a superior way of asking questions. It institutionalizes a process of continuous inquiry into the firm’s own execution quality, transforming every trade into a data point that refines the system. The challenge is to see the policy not as a set of rules to be followed, but as the source code for the firm’s execution philosophy, one that must be constantly compiled, tested, and improved in the live environment of the market.