How Does the SI Regime Affect Best Execution Proof for Illiquid Assets?

Concept

The Systematic Internaliser (SI) regime, a core component of the MiFID II architecture, introduces a structural paradox when applied to illiquid assets. Its primary function is to bring transparency and order to significant bilateral trading by formalizing principal-desk activities into a defined regulatory category. For an investment firm executing client orders on its own account, achieving SI status is a function of crossing quantitative thresholds for frequency and volume in a specific instrument class.

This framework fundamentally alters the nature of demonstrating best execution. The process shifts from one of discovery within a transparent, multilateral order book to one of constructing a defensible justification for a price arrived at bilaterally.

This challenge is magnified exponentially in the context of illiquid assets, such as bespoke over-the-counter (OTC) derivatives or thinly traded corporate bonds. These instruments lack the continuous, reliable public price feeds that are the bedrock of best execution validation for liquid equities or futures. The very nature of an SI is to internalize flow.

When that flow is in an asset with no contemporaneous public print, the SI’s quoted price becomes a dominant, yet isolated, data point. The core operational question becomes how to prove that this internally generated price is fair and represents the best possible outcome for the client, when external reference points are scarce or non-existent.

The SI regime recasts best execution for illiquids from a process of price discovery to a process of price justification.

How Does an SI Reconcile Principal Trading with Fiduciary Duty?

The reconciliation of a firm’s commercial interest as a principal with its fiduciary duty to the client is the central challenge. The best execution obligation under MiFID II is absolute and applies to all financial instruments, irrespective of their liquidity profile or the venue of execution. It requires firms to take all sufficient steps to obtain the best possible result, considering a matrix of factors including price, costs, speed, and likelihood of execution. For an SI, this means its internal processes must be robust enough to withstand regulatory scrutiny and prove that the price offered to a client was not merely convenient for the firm’s own book, but was genuinely the best outcome available under the prevailing market conditions.

This is achieved by building an internal system of checks and balances. The firm must create a verifiable data trail that substantiates the fairness of its price. This involves gathering market data for comparable or correlated products, soliciting quotes from other liquidity providers, and using internal valuation models. The objective is to construct a “virtual” competitive environment around the illiquid trade, demonstrating that the final execution price is benchmarked against a credible and objective set of data points, even if a single, definitive market price is absent.

The Architectural Shift in Proving Compliance

The SI framework forces a firm to move from being a passive consumer of market-wide execution data to an active producer and curator of its own justification data. For liquid instruments, proof of best execution can often be established by referencing the consolidated tape or the state of the order book on a public venue at the time of the trade. For an illiquid instrument traded with an SI, this external proof is unavailable. The burden of proof shifts inward.

Consequently, the firm’s compliance architecture must be redesigned. It requires systems capable of capturing not just the executed trade details, but the entire context of the execution decision. This includes records of all quotes requested and received, the inputs and outputs of internal pricing models, the rationale for selecting a specific execution strategy, and timestamps for every step of the process. The focus is on creating an auditable, evidence-based narrative that demonstrates a systematic and consistent approach to achieving the best client outcome, transforming a compliance obligation into a driver for more sophisticated internal data infrastructure.

Strategy

The strategic response to the SI regime’s impact on illiquid assets is the development and implementation of a “Best Execution Conclusive Framework.” This is a holistic system of policies, data architecture, and operational procedures designed to create a defensible and auditable record for every transaction. Its purpose is to systematically address the inherent information asymmetry in bilateral illiquid markets and provide a robust answer to the question of price fairness before it is ever asked by a regulator or client.

This framework is built on the principle of verifiable comparison. Since a public, contemporaneous price is unavailable for an illiquid asset, the SI must create a synthetic benchmark through a structured process. This involves checking the fairness of the price proposed to the client by gathering market data used in the estimation of the price and, where possible, comparing it with similar or comparable products. The strategy is to treat every illiquid execution not as a single event, but as the conclusion of a documented, multi-faceted validation process.

A Conclusive Framework transforms the best execution obligation from a post-trade reporting task into a pre-trade risk management discipline.

What Data Constitutes a Fair Market Price?

In the absence of a liquid market, the definition of a “fair price” becomes a composite of several data sources. A core strategy for an SI is to define, in its formal execution policy, what constitutes this composite price. This policy becomes the cornerstone of its Conclusive Framework. The data inputs are methodically gathered and weighted to form a defensible price range.

• Comparable Instrument Benchmarking ▴ This involves identifying a “proxy” instrument that is more liquid but shares key characteristics with the illiquid asset. For a specific corporate bond, this could be a more frequently traded bond from the same issuer or sector with a similar duration. The strategy requires a documented methodology for calculating the spread or price differential between the illiquid asset and its liquid proxy.
• Multi-Counterparty Quote Solicitation ▴ The Request for Quote (RFQ) process is central. Even when executing as principal, the SI must demonstrate it has surveyed the available market. By sending RFQs to a pre-defined and objectively selected group of other liquidity providers, the SI creates a competitive tension and generates a set of contemporaneous, executable prices. Capturing all responses, including declines, is a critical part of the data trail.
• Internal Model Validation ▴ SIs must use internal pricing models to generate their own independent valuation. The strategy here is one of transparency and consistency. The models, their inputs (e.g. yield curves, volatility surfaces), and their assumptions must be documented, validated by an independent function within the firm, and applied consistently across similar transactions.

The table below compares the strategic attributes of executing an illiquid asset through different channels, highlighting the unique position of the SI.

The Architecture of a Defensible Policy

The strategic foundation of the Conclusive Framework is the firm’s best execution policy. This document is not a high-level statement of intent; it is a detailed operational manual that prescribes the firm’s approach. It must be specific, granular, and leave no room for ambiguity in its application to illiquid instruments.

A successful policy architecture includes several key components:

1. Instrument Classification System ▴ A clear methodology for categorizing instruments by liquidity. This determines which execution protocols apply and must be based on objective criteria like trading frequency and volume.
2. Venue and Counterparty Selection Criteria ▴ The policy must define the “sufficient steps” taken to ensure best execution. This includes the process for selecting the pool of counterparties for an RFQ, ensuring the selection is objective and designed to access meaningful liquidity.
3. Price Fairness Validation Procedure ▴ This section explicitly details the waterfall of validation steps ▴ first, check for comparable instrument data; second, initiate an RFQ; third, benchmark against internal models. It defines the acceptable deviation between the execution price and the constructed benchmark.
4. Record-Keeping Mandates ▴ The policy mandates the specific data points that must be captured for every illiquid trade, ensuring that the evidence required for the Conclusive Framework is always available for review.

Execution

The execution of the best execution obligation for an illiquid asset within a Systematic Internaliser is a matter of procedural discipline and meticulous data architecture. It translates the strategic Conclusive Framework into a series of non-negotiable operational steps. The objective is to produce a self-contained, auditable “Best Execution File” for every single transaction, which serves as the definitive proof of compliance. This file is not an afterthought; its construction is integrated into the trading workflow itself.

This operationalization moves beyond policy into the realm of system design and trader conduct. The execution workflow must be engineered to enforce data capture at every stage, ensuring that the rationale behind every decision is recorded contemporaneously. For illiquid assets, where judgment plays a significant role, documenting the “why” is as important as recording the “what.”

The Best Execution File is the ultimate output of the SI’s operational workflow, demonstrating a systematic process rather than a favorable outcome.

Can a Model Price Ever Justify an Execution?

An internal model price, on its own, is insufficient to justify an execution. Its role is as a critical point of validation within a broader set of data. The execution workflow must treat the model price as a benchmark, not as the sole determinant of fairness. The process ensures the model itself is subject to oversight and its output is contextualized with real-world, executable quotes where possible.

The operational playbook for a trader executing an illiquid trade must therefore follow a clear, sequential logic. This process ensures that the final price is tested against multiple reference points, creating a robust defense against any challenge of unfair pricing. The steps are designed to be systematic and repeatable, forming the core of the firm’s execution protocol.

The Operational Playbook for an Illiquid RFQ Trade

The following steps outline the practical, sequential workflow for executing an illiquid trade and constructing the corresponding Best Execution File. This process ensures compliance by creating a comprehensive and contemporaneous record of the actions taken to secure the best possible result for the client.

• Step 1 Pre-Trade Analysis and Classification ▴ The process begins with the formal classification of the instrument as “illiquid” according to the firm’s documented policy. The trader must record the evidence used for this classification (e.g. absence of recent trades, wide indicative spreads from data vendors). This initial step justifies the application of the specific illiquid execution protocol.
• Step 2 Counter-Pricing Data Sourcing ▴ The trader initiates a Request for Quote (RFQ) to a pre-approved pool of external liquidity providers. The system must log the identity of each provider, the exact time the request is sent, and the full content of every response received, including price, size, and any rejections or “no-bids.” This creates the primary evidence of market sounding.
• Step 3 Internal Price Validation and Benchmarking ▴ Simultaneously, the trader generates a price from the firm’s internal valuation model. This model price, along with its key inputs, is logged. The trader then benchmarks the external quotes against this internal price and any available data on comparable instruments. Any significant deviation must be flagged and investigated.
• Step 4 The Execution Decision and Rationale ▴ The trader selects the final execution price and counterparty (which may be the SI’s own desk). The critical action at this stage is the documentation of the rationale. If the best price was not chosen, a clear reason must be provided (e.g. superior settlement certainty, lower counterparty risk). This narrative is a core component of the Best Execution File.
• Step 5 Post-Trade Data Collation and Reporting ▴ Immediately following execution, all the captured data ▴ classification evidence, RFQ logs, model outputs, execution timestamps, and trader rationale ▴ is automatically collated into the final Best Execution File. This file is then used to populate the necessary fields for any required regulatory reports, such as those derived from the principles of RTS 27.

Quantitative Modeling and Data Analysis

The data captured during the execution process must be structured and granular. The following table provides a sample of what a Best Execution File might contain for a single illiquid corporate bond trade. It demonstrates the level of detail required to build a defensible record.

Reflection

The architecture required to navigate the SI regime for illiquid assets prompts a fundamental re-evaluation of a firm’s operational philosophy. The systems and protocols detailed are components of a larger institutional capability. They represent a shift from viewing compliance as a reactive, evidence-gathering burden to seeing it as a proactive driver of infrastructural investment and process integrity. The obligation to prove best execution becomes a catalyst for building a more intelligent, resilient, and ultimately more competitive trading framework.

Consider your own operational architecture. Is it a series of discrete processes held together by manual intervention, or is it a coherent system where data flows seamlessly from pre-trade analysis to post-trade justification? The challenge presented by illiquid assets within the SI regime is a stress test for the entire execution platform. Acing that test provides more than regulatory safety; it provides a strategic advantage rooted in superior operational control and demonstrable client value.