How Do the SI Regimes for Bonds and Equities Affect Best Execution Obligations?

Concept

The Systemic Re-Calibration of Principal Liquidity

The introduction of the Systematic Internaliser (SI) regime under MiFID II represents a fundamental recalibration of how principal liquidity interacts with broader market structures. It formalizes a specific type of over-the-counter (OTC) dealing, moving it into a framework with defined transparency and reporting obligations. An SI is an investment firm that deals on its own account by executing client orders outside of a regulated market or trading facility on an organized, frequent, systematic, and substantial basis.

This framework compels firms that internalize significant order flow to operate under a specific set of rules, directly impacting how they provide liquidity and, consequently, how their clients achieve and demonstrate best execution. The regime’s application is not uniform across asset classes; its effects on equity and bond markets are distinct, driven by the inherent structural differences between these two financial landscapes.

Understanding the impact on best execution requires a precise definition of the obligation itself. Best execution is a multi-faceted duty that requires firms to take all sufficient steps to obtain the best possible result for their clients. This assessment is based on a range of factors including price, costs, speed, likelihood of execution and settlement, size, and nature of the order. It is a process, not a single outcome.

The inclusion of SIs as a formal execution venue type adds a new dimension to this process. A firm’s best execution policy must now account for the liquidity offered by SIs, evaluating their quotes alongside those from traditional exchanges and other trading venues. This evaluation is complex because the nature of SI liquidity and the transparency obligations attached to it differ profoundly between the high-velocity, standardized world of equities and the fragmented, relationship-driven domain of fixed income.

Divergent Pathways for Equities and Bonds

The core distinction in how the SI regime affects equities versus bonds stems from their pre-existing market structures. Equity markets are predominantly centralized, characterized by lit order books, continuous trading, and a high degree of pre-trade transparency. The SI regime for equities, therefore, was designed to regulate internalization that might otherwise draw liquidity away from these transparent public venues.

It imposes strict pre-trade quoting obligations on SIs for liquid instruments, forcing them to publish firm quotes that contribute to the overall price discovery process. These quotes must be competitive, as buy-side firms are obligated to consider them within their smart order routing (SOR) logic to satisfy best execution.

Bond markets, in contrast, are fundamentally decentralized, operating primarily OTC. Liquidity is fragmented across numerous dealers, and price discovery has traditionally occurred through bilateral request-for-quote (RFQ) protocols. Applying the SI framework to this environment was a significant structural intervention. For bonds, the SI regime aims to introduce a degree of pre-trade transparency into a historically opaque market.

However, the obligations are tailored to the market’s nature. For liquid bonds, SIs must provide quotes upon request, but the definition of “liquid” is far narrower than in equities. For the vast majority of bonds, which are illiquid, the pre-trade transparency obligations are less stringent, reflecting the reality that continuous, firm quoting is often impractical and detrimental to risk management for dealers. This divergence creates two very different sets of considerations for firms when integrating SIs into their best execution framework.

Strategy

Integrating Equity SIs into the Execution Calculus

For equities, the strategic integration of Systematic Internalisers into a best execution framework is primarily a technological and quantitative challenge. The availability of firm, public quotes from SIs for liquid stocks provides a valuable new source of potential price improvement and liquidity. Investment firms must adapt their execution systems, particularly their Smart Order Routers (SORs), to intelligently access this liquidity. An effective SOR can no longer simply sweep lit exchange order books; it must be programmed to poll SIs for quotes and compare them against the prevailing market price, factoring in all associated costs of execution.

The strategic challenge in equities is to treat SI liquidity not as an alternative, but as an integral component of the addressable market, requiring sophisticated routing logic to optimize execution outcomes.

The execution policy must clearly articulate the circumstances under which routing to an SI is beneficial. This involves a continuous analysis of execution quality data, as mandated by RTS 28 reporting. Firms must analyze metrics such as price improvement versus the European Best Bid and Offer (EBBO), speed of execution, and the likelihood of execution for different order sizes. This data-driven approach allows firms to dynamically adjust their routing tables, favoring SIs that consistently provide superior results for specific types of order flow.

Furthermore, the strategy must account for the nuances of the MiFID II double volume cap (DVC), which limits the amount of dark trading. Since SI trades (that are not large-in-scale) can count towards these caps, a firm’s strategy might involve using SIs for mid-point execution to minimize market impact while managing their exposure to DVC restrictions.

Navigating the Relational Dynamics of Bond SIs

In the fixed-income space, the strategy for engaging with SIs is less about high-frequency routing logic and more about managing relationships and accessing fragmented liquidity. The bond market’s OTC nature means that even with the SI regime, securing the best outcome often depends on a firm’s ability to source quotes from the right counterparties. The SI designation helps identify key liquidity providers in specific instruments, acting as a “marketing tool” for dealers who specialize in certain bonds. A buy-side firm’s best execution strategy, therefore, involves identifying which dealers are SIs for their target securities and ensuring their RFQ processes systematically include these firms.

The strategic imperative is to build a robust counterparty management system. This system should track not only which firms have opted into the SI regime for which bonds but also their responsiveness and quality of pricing. Unlike the equity market’s firm and public quotes, bond SI quotes are often provided only upon request. The best execution policy must define a process for ensuring a sufficient number of dealers, including relevant SIs, are solicited for quotes to evidence that the market has been adequately surveyed.

This process must be auditable and systematic. The table below outlines the key strategic differences in approaching SIs for best execution across the two asset classes.

Table of Strategic Differentiation in SI Engagement

The Governance Framework for SI Oversight

A comprehensive strategy requires a robust governance framework to oversee the use of SIs and ensure ongoing compliance with best execution obligations. This framework must be data-centric, relying on the post-trade transparency and execution quality reports generated by SIs (RTS 27) and the firm’s own summary of execution venues used (RTS 28). The firm’s governance committee should regularly review this data to assess whether the SIs included in the execution policy are consistently delivering high-quality outcomes.

• For Equities ▴ The review process should scrutinize whether the firm’s SOR logic is performing as expected. Questions to address include ▴ Are we achieving meaningful price improvement from SIs? Is there evidence of adverse selection on SI-routed orders? How does the fill rate at SIs compare to lit venues?
• For Bonds ▴ The governance process focuses on the effectiveness of the counterparty selection process. The committee should ask ▴ Are we including all relevant SIs in our RFQs for applicable bonds? Is there a concentration risk with a small number of SIs? Does the data show that certain SIs consistently provide better pricing or a higher likelihood of execution?

This continuous monitoring and review process ensures that the firm’s best execution policy is a living document, adapting to changes in market structure and the performance of its execution venues. It moves the firm from a static, compliance-focused approach to a dynamic, performance-oriented strategy for achieving the best possible results for its clients.

Execution

An Operational Playbook for SI Integration

Executing a best execution policy that properly incorporates Systematic Internalisers requires a detailed and auditable operational workflow. This process must be embedded within the firm’s trading systems and managed by clear internal guidelines. The objective is to create a repeatable and evidence-based procedure that demonstrates how the firm achieves the best possible outcome for its clients on a consistent basis. This involves a fusion of technology, data analysis, and trader oversight.

The implementation of this playbook is asset-class specific, reflecting the different market dynamics. For equities, the process is highly automated, relying on pre-trade data and sophisticated algorithms. For bonds, it is a more deliberative process, blending system-driven data with the qualitative judgment of experienced traders. Both, however, require a foundation of robust data management and clear documentation to satisfy regulatory scrutiny.

Procedural Steps for Best Execution with SIs

1. Policy Definition and Venue Selection ▴
   • Maintain a formal Best Execution Policy document that explicitly lists the SIs the firm is permitted to trade with for both equities and bonds.
   • The selection of SIs must be justified based on an initial due diligence process that assesses their market share, instrument coverage, and technological capabilities. This selection must be reviewed at least annually.
2. Pre-Trade Process (Equities) ▴
   • Ensure the firm’s Smart Order Router (SOR) is configured to receive and process quote data from all selected equity SIs via APIs or direct FIX connectivity.
   • The SOR logic must compare SI quotes against the lit market’s European Best Bid and Offer (EBBO) in real-time, considering factors like fees, potential for price improvement, and order size.
   • For orders above a certain size, the SOR should have logic to determine whether to route to an SI for a potential block trade or to use an algorithmic execution strategy across multiple venues.
3. Pre-Trade Process (Bonds) ▴
   • The Order Management System (OMS) must have a function to identify which approved dealers are SIs for a specific bond being traded.
   • When initiating a Request for Quote (RFQ), the system should prompt the trader to include a sufficient number of counterparties, ensuring that relevant SIs are on the list. The definition of “sufficient” should be documented in the policy (e.g. a minimum of three to five quotes).
   • The trader must document the rationale if a known SI for an instrument is not included in an RFQ.
4. Trade Execution and Data Capture ▴
   • All order routing decisions and executions must be time-stamped and logged, creating a complete audit trail.
   • For bond RFQs, all quotes received (both winning and losing) must be captured in the OMS, along with the time of receipt and the final execution price and time. This data is the primary evidence of surveying the market.
5. Post-Trade Monitoring and Analysis ▴
   • On a regular basis (at least quarterly), the firm must ingest and analyze the RTS 27 reports published by the SIs it uses. This data provides insights into their execution quality across various metrics.
   • The firm must perform its own Transaction Cost Analysis (TCA) on its trades, comparing execution prices against relevant benchmarks (e.g. arrival price, VWAP for equities; composite price for bonds).
   • A governance committee must review the outputs of both the RTS 27 analysis and the internal TCA to identify any SIs that are underperforming and determine if they should remain in the execution policy. This review process and its conclusions must be formally minuted.

Quantitative Analysis of SI Execution Quality

The core of a data-driven best execution framework is the ability to quantitatively assess the performance of execution venues. The SI regime, through its reporting requirements, provides a rich dataset for this purpose. Firms must develop the capability to not only consume this data but to interpret it in the context of their own trading activity. This allows for a precise, evidence-based evaluation of whether SIs are contributing positively to the firm’s execution outcomes.

Effective best execution is impossible without a rigorous quantitative framework; SI reporting provides the raw material, but the firm must build the analytical engine.

The following tables provide illustrative examples of how this quantitative analysis can be structured. The first shows a simplified version of an RTS 27 report for a corporate bond, and the second demonstrates a TCA comparison for an equity trade.

Illustrative RTS 27 Report Analysis for a Corporate Bond SI

Hypothetical TCA Report for an Equity Order

This level of detailed, quantitative analysis forms the bedrock of an executable and defensible best execution policy. It transforms the obligation from a subjective assessment into an objective, data-driven process of continuous improvement and risk management.

Reflection

From Mandate to Mechanism

The integration of Systematic Internalisers into the fabric of European financial markets marks a significant evolution in the regulatory landscape. Viewing this development solely through the lens of a compliance mandate, however, is to miss the underlying operational opportunity. The regime provides a formal structure and a new stream of data that, when properly harnessed, can transform a firm’s best execution framework from a static policy document into a dynamic, intelligent, and performance-oriented system. The core challenge is not simply to connect to SIs, but to build the internal architecture ▴ the combination of technology, data analytics, and human oversight ▴ capable of interpreting this new market information.

This process compels a deeper introspection into a firm’s own operational capabilities. Does our order management system possess the sophistication to manage complex RFQ workflows for bonds? Is our smart order router truly smart, capable of making nuanced, data-driven decisions in real-time for equities? The SI regime effectively holds up a mirror to a firm’s internal systems.

The answers to these questions reveal the true state of a firm’s execution intelligence. Ultimately, mastering the complexities of the SI regime is a proxy for mastering the modern market itself. The firms that build the most robust and adaptive mechanisms for integrating this liquidity will be the ones that consistently deliver a superior operational edge and demonstrably better outcomes for their clients.