How Has the Rise of Systematic Internalisers Affected the Definition of Best Execution?

Concept

The introduction of the Systematic Internaliser (SI) regime under MiFID II represents a fundamental re-architecting of the European liquidity landscape. It compels market participants to move beyond a simplistic, price-centric view of execution quality. The core of the matter is that best execution is now a multi-variable equation, where the SI acts as a distinct and powerful variable.

An SI is an investment firm that executes client orders on its own account, creating a private liquidity pool that exists outside the traditional lit order books of a public exchange. This structure introduces a controlled environment where a firm can offer execution to its clients without exposing those orders to the broader market, a critical capability for managing market impact.

This evolution forces a sophisticated re-evaluation of what it means to achieve an optimal outcome for a client. The definition of best execution has expanded to formally include not just price, but also costs, speed, likelihood of execution and settlement, and the specific characteristics of the client’s order. The rise of SIs directly addresses these factors.

By internalizing flow, a firm can potentially offer price improvement relative to the public bid-offer spread, reduce explicit transaction costs, and, most critically, minimize the information leakage that often precedes adverse price movements when a large order is shown to the market. The SI regime was designed to bring activity that was previously occurring in opaque over-the-counter (OTC) markets into a more regulated framework, increasing transparency through post-trade reporting while allowing for pre-trade discretion.

The proliferation of Systematic Internalisers has transformed best execution from a quest for the best price into a complex, multi-factor optimization problem.

From a systems perspective, an SI is a new protocol for accessing liquidity. It is a bilateral communication channel, distinct from the multilateral free-for-all of a central limit order book. This bilateral nature carries both immense advantages and inherent complexities. The primary advantage is control over information.

For a large institutional order, signaling intent to the entire market can be prohibitively expensive. An SI provides a mechanism to execute that trade with a single, known counterparty, mitigating the risk of being front-run by high-frequency participants. However, this also introduces a new dynamic ▴ the firm operating the SI is the direct counterparty to the trade. This creates a potential conflict of interest that must be managed through rigorous data analysis and a robust compliance framework. The challenge for institutional traders is to architect an execution strategy that intelligently leverages this new protocol, integrating it alongside lit markets, dark pools, and other alternative trading systems to create a holistic liquidity-sourcing framework.

Strategy

The strategic imperative for any institutional trading desk is to navigate the increasingly fragmented liquidity landscape created by the SI regime. The existence of SIs, alongside traditional exchanges and other off-venue pools, means that a significant portion of market liquidity is no longer accessible through a single point of entry. A successful execution strategy, therefore, must be built upon a sophisticated understanding of when and why to route an order to a specific type of venue. This is not a static decision; it is a dynamic process of calibration based on the specific characteristics of each order and the real-time state of the market.

Calibrating the Execution Factors for Venue Selection

The MiFID II framework provides the core set of factors that must be considered to demonstrate best execution ▴ price, costs, speed, likelihood of execution, and order size/nature. The strategy lies in how these factors are weighted and analyzed in the context of SI liquidity.

• Price and Costs ▴ An SI can offer price improvement by quoting a price inside the spread available on the lit market. This is a primary attraction. The strategic consideration is whether this offered price improvement is substantial enough to outweigh other factors, and to verify that the SI is not widening its own spreads to capture more than a fair share of the economic benefit. Costs are also a factor, as executing with an SI can sometimes mean lower explicit exchange and clearing fees.
• Likelihood of Execution ▴ For large or illiquid orders, the probability of a complete fill is a dominant concern. A lit market may not have sufficient depth at a single price level, forcing an order to “walk the book” and incur significant slippage. An SI, dealing as principal, can commit capital and guarantee a full execution at a single price for a large block, offering a high degree of certainty.
• Speed and Market Impact ▴ These two factors are intrinsically linked. While the raw execution speed on an SI might be measured in milliseconds, its true value is in minimizing market impact, which is a function of time and information leakage. The strategic decision to route to an SI is often a deliberate choice to trade certainty for the potential of a slightly better price in the lit market, precisely to avoid the cost of signaling trading intent.

How Should a Firm Approach SI Counterparty Selection?

Choosing which SIs to connect with is a critical strategic decision. A firm’s best execution policy must justify its selection of execution venues. This involves a due diligence process to assess the quality of liquidity provided by different SIs.

Key performance indicators (KPIs) should be tracked for each SI, including the frequency and magnitude of price improvement, rejection rates for quote requests, and post-trade performance measured by robust Transaction Cost Analysis (TCA). This data-driven approach allows a firm to build a ranked and rationalized list of SI counterparties, ensuring they are systematically directing flow to the venues that provide the best outcomes across the spectrum of execution factors.

An effective strategy treats venue selection not as a choice, but as an optimization algorithm, constantly solving for the best possible outcome based on order-specific constraints.

The table below illustrates a simplified comparison of potential outcomes for a hypothetical 100,000-share order in a liquid stock, highlighting the trade-offs that an execution strategy must balance.

The Central Role of the Smart Order Router

The practical implementation of this strategy is embodied in the firm’s Smart Order Router (SOR). An SOR is the automated system responsible for dissecting an order and routing its components to the optimal venues. In a post-MiFID II world, the logic governing the SOR must be incredibly sophisticated. It must be configured to recognize the unique attributes of SI liquidity.

The SOR’s decision-making process should incorporate a “waterfall” logic:

1. Check for SI Price Improvement ▴ For a given order, the SOR should first ping its selected SI counterparties for a quote. If an SI offers a firm quote at a price better than the European Best Bid and Offer (EBBO), and the size is sufficient, this may be the optimal route.
2. Assess Market Impact Sensitivity ▴ If the order is large or in a sensitive name, the SOR’s logic may prioritize routing to an SI even without significant price improvement, purely to control information leakage.
3. Evaluate Lit Market Depth ▴ If SIs do not offer a compelling quote, the SOR must then analyze the depth and liquidity on the lit order books, calculating the likely slippage of placing the order there.
4. Consider Dark Pool Liquidity ▴ As a parallel step, the SOR can seek passive fills in dark pools at the midpoint, blending this execution with other venues.

This systematic, data-driven approach to routing is the only viable strategy for navigating the complexities of the modern market structure and demonstrably fulfilling the mandate of best execution.

Execution

Executing a trading strategy that effectively incorporates Systematic Internalisers requires a robust operational framework grounded in technology, data analysis, and rigorous post-trade review. The theoretical advantages of SI liquidity can only be realized through meticulous implementation, ensuring that every decision is justifiable, measurable, and compliant. The focus shifts from simply finding liquidity to architecting a process that proves the quality of that liquidity on an ongoing basis.

The Operational Playbook for SI Engagement

A disciplined, procedural approach is required to integrate SIs into a firm’s execution workflow. This playbook outlines the critical steps for translating strategy into concrete action.

• Step 1 Counterparty Onboarding and Due Diligence ▴ This initial phase involves a quantitative and qualitative assessment of potential SI partners. Quantitatively, firms must analyze historical market data to evaluate the SI’s typical quote quality, response times, and fill rates across different market conditions. Qualitatively, the operational due diligence should review the SI’s stated commercial policy to ensure it is non-discriminatory and aligns with the firm’s execution philosophy.
• Step 2 Pre-Trade Venue Analysis ▴ Before an order is routed, the execution system must perform a real-time analysis of the available options. This involves the OMS/EMS fetching quotes from connected SIs while simultaneously evaluating the state of the lit order book. The system’s logic must be able to instantly calculate the implicit cost of crossing the spread on a lit market versus the price improvement offered by an SI.
• Step 3 Intelligent Order Routing and Execution ▴ This is the domain of the Smart Order Router (SOR). The SOR must be programmed with rules that govern how it interacts with SIs. For example, for orders below the Large-in-Scale (LIS) threshold, the SOR might be configured to always prioritize an SI that is offering a price at the midpoint or better. For LIS orders, the SOR may be programmed to request quotes from multiple SIs simultaneously to create competitive tension and secure the best possible block price.
• Step 4 Post-Trade Reconciliation and Reporting ▴ Once a trade is executed with an SI, the operational process is not complete. The SI has the obligation to make the trade public via an Approved Publication Arrangement (APA). The firm’s middle-office systems must have a workflow to reconcile their execution records with the public tape to ensure accuracy and timeliness. This provides a critical audit trail for compliance and regulatory review.

Quantitative Modeling and Transaction Cost Analysis

The burden of proof for best execution lies with the investment firm. When using SIs, this burden is magnified due to the inherent conflict of interest. Rigorous, quantitative Transaction Cost Analysis (TCA) is the primary tool for meeting this obligation. TCA moves beyond simple price metrics to provide a multi-dimensional view of execution quality.

The following table provides an example of a TCA report designed to compare executions across different venue types, including SIs. This level of granularity is essential for refining the SOR’s routing logic and demonstrating to regulators that the firm is systematically achieving optimal outcomes.

Analysis of this data allows the firm to answer critical questions. Is a particular SI consistently providing price improvement? Does routing to SIs for large orders demonstrably reduce negative market impact compared to algorithmic execution on lit venues? The answers, derived from this quantitative analysis, form the backbone of the best execution defense.

What Is the Required Technological Architecture?

Effective execution requires a technology stack capable of handling the complexity of a fragmented market. Key components include:

1. Aggregated Market Data Feeds ▴ The system must consume and normalize data from numerous sources in real-time, including direct exchange feeds and the proprietary quote streams from each SI counterparty. Latency must be minimized to ensure pre-trade analysis is based on the most current market picture.
2. Configurable Smart Order Router (SOR) ▴ A generic, “out-of-the-box” SOR is insufficient. The firm must have the ability to customize the routing logic, weighting the best execution factors according to its specific policies and the characteristics of different order flows.
3. Integrated Execution and Order Management (EMS/OMS) ▴ The trading platform must provide a unified view of all liquidity sources. A trader should be able to see SI quotes alongside the lit market book within their primary execution screen. The system must seamlessly handle order placement, execution confirmation, and post-trade allocation for trades occurring across all venue types.
4. Robust TCA and Analytics Engine ▴ The TCA system must be able to ingest execution data from all venues and attribute costs and performance metrics correctly. It should be capable of generating the detailed reports necessary for both internal strategy refinement and external regulatory inquiry.

Reflection

The integration of Systematic Internalisers into the market’s architecture is a permanent evolution. It presents a structural challenge to legacy definitions of execution quality and demands a more sophisticated operational response. The framework of price, cost, speed, and likelihood of execution is the beginning of the analysis. The truly differentiating factor is a firm’s ability to measure and control for the unseen variable ▴ information.

Is Your Data Architecture a True Asset?

Consider your firm’s data infrastructure. Does it merely record executions, or does it provide the analytical power to model the counterfactual? Can you quantify the market impact that was avoided by routing a large order to an SI? A reactive TCA process that simply reports slippage against a benchmark is no longer sufficient.

A proactive analytics framework is required, one that informs routing logic in real-time and provides a defensible, evidence-based narrative for every execution decision. The quality of your execution is now a direct reflection of the quality of your data architecture.