How Does MiFID II Define Best Execution for RFQ Based Trades?

Concept

The Markets in Financial Instruments Directive II (MiFID II) reframes best execution from a passive obligation into an active, demonstrable, and data-driven process. For bilateral price discovery mechanisms like the Request for Quote (RFQ) protocol, this represents a significant architectural shift. The directive mandates that investment firms design and implement a systemic process to ensure they are taking “all sufficient steps” to obtain the best possible result for their clients. This standard moves beyond the previous “all reasonable steps” language, signaling a higher bar for diligence and proof.

At its core, the obligation is built upon a multi-factor model. A firm’s execution policy must weigh several critical variables to determine the optimal outcome for a client order. These factors include not just the headline price, but also the associated costs, the speed of execution, the likelihood of both execution and settlement, and the size and nature of the specific order.

For RFQ-based trades, which often occur in less liquid, over-the-counter (OTC) markets, this multi-dimensional analysis is particularly salient. In these environments, factors like counterparty reliability and the likelihood of settlement can carry substantial weight alongside the quoted price.

MiFID II requires firms to construct a clear, evidence-based framework that justifies their execution choices for every client order.

A central component of this framework is the “legitimate reliance test,” a concept carried forward to assess whether best execution applies to a firm dealing on its own account, as is common in RFQ scenarios. The test considers whether a client has a legitimate expectation that the firm will protect its interests. This is evaluated through a four-fold analysis that looks at which party initiated the transaction, the prevailing market practices, the relative price transparency of the instrument, and how the firm has presented its services to the client. When a client, particularly a less sophisticated one, solicits a quote for an opaque product, their reliance on the firm to provide a fair price is high, firmly triggering the best execution duty.

Therefore, defining best execution for RFQ trades under MiFID II is an exercise in system design. It requires the creation of a robust order execution policy, a transparent counterparty selection process, and a rigorous data collection mechanism to monitor and prove the effectiveness of the chosen execution strategy. The directive compels firms to view every RFQ not as an isolated transaction, but as a data point within a larger, auditable system designed to consistently deliver and verify superior client outcomes.

Strategy

Achieving compliance with MiFID II’s best execution requirements for RFQ-based trades necessitates a deliberate and systematic strategy. This strategy extends beyond mere policy documentation into the very architecture of a firm’s trading and compliance functions. The objective is to build a resilient framework that is both operationally effective and demonstrably compliant through rigorous data analysis.

The Architecture of a Compliant Execution Policy

The foundational element of the strategy is the firm’s order execution policy. This document is the blueprint for how the firm will achieve best execution. For RFQ trades, the policy must be granular, specifying the procedures for handling these specific order types across different asset classes.

A robust policy architecture includes:

• Counterparty Selection Criteria ▴ The policy must define the qualitative and quantitative criteria used to select the liquidity providers (LPs) to whom RFQs will be sent. This includes factors like financial stability, historical response rates, and pricing competitiveness.
• Venue Analysis ▴ For each class of financial instruments, the policy must list the execution venues the firm relies on, which in the RFQ context are the liquidity providers themselves. It must also explain the factors that guide the choice of one LP over another for a particular trade.
• Factor Weighting ▴ The firm must determine the relative importance of the best execution factors (price, cost, speed, etc.) for different client types and order characteristics. For a professional client executing a large, illiquid block trade via RFQ, likelihood of execution might be weighted more heavily than speed. For a retail client, total consideration (price and costs) is paramount.
• Review and Monitoring Cycle ▴ The policy must specify a regular cycle for reviewing its own effectiveness. This involves analyzing execution data to identify any deficiencies and making necessary adjustments to the counterparty list or internal processes.

Data Driven Counterparty Evaluation

A core strategic challenge in the RFQ workflow is the selection of appropriate counterparties. MiFID II requires this process to be methodical and evidence-based. Firms must move from relationship-based counterparty selection to a quantitative evaluation model. This involves systematically capturing and analyzing data from every RFQ interaction to build a comprehensive performance profile for each liquidity provider.

Effective best execution strategy transforms anecdotal counterparty knowledge into a structured, quantifiable, and defensible selection process.

The following table illustrates a simplified quantitative framework for evaluating LP performance, a critical component of a MiFID II-compliant strategy.

How Should Firms Structure Their RFQ Process?

The strategy must also define the operational process for soliciting quotes. This involves making a conscious choice between a competitive multi-dealer RFQ and a more targeted single-dealer RFQ. A competitive RFQ to three to five LPs is the standard approach for demonstrating that the firm has surveyed the market to achieve the best price.

However, for very large or sensitive orders, a single-dealer RFQ may be justified to minimize information leakage, a key consideration under the ‘nature of the order’ factor. The justification for this choice must be documented within the execution record.

Execution

The execution of a MiFID II-compliant best execution framework for RFQ trades is a matter of operational precision and rigorous data management. It translates the strategic principles outlined in the execution policy into a series of concrete, auditable actions performed by the trading desk and monitored by the compliance function. This requires seamless integration between the firm’s Order Management System (OMS), Execution Management System (EMS), and its data analysis capabilities.

The Operational Playbook for an RFQ Trade

Executing a single RFQ trade under this regime involves a detailed, multi-step procedure. Each step is designed to generate the necessary data to justify the final execution outcome. The process forms a clear audit trail from client order to post-trade analysis.

1. Order Receipt and Characterization ▴ Upon receiving a client order, the trader must first characterize it according to the execution policy. This involves classifying the client (retail or professional) and the instrument, and assessing the order’s characteristics (size, liquidity profile) to determine the relative importance of the execution factors.
2. Pre-Trade Counterparty Selection ▴ Based on the order’s characterization, the trader selects LPs from the firm’s approved list. This selection must align with the quantitative data from the LP scorecard. For a standard trade, this may mean selecting the top 3-5 LPs based on historical price competitiveness and response rates. The justification for this selection is recorded.
3. RFQ Submission and Quote Management ▴ The RFQ is submitted, and the system captures all responses. This includes the quoted price, time of response, and any associated conditions from each LP. Quotes that are rejected or timed out are also logged as critical data points.
4. Execution Decision and Justification ▴ The trader selects the winning quote. The decision must be justified against the firm’s execution policy. If the best-priced quote is not selected, a clear, documented reason is required (e.g. the better-priced LP has a poor fill rate, or the slightly worse price comes with a much higher likelihood of settlement for a critical order). This justification is the cornerstone of the execution record.
5. Post-Trade Data Capture and Analysis ▴ Following execution, all relevant data is captured for Transaction Cost Analysis (TCA) and regulatory reporting. This includes the execution price, fees, and settlement details. This data feeds back into the LP performance scorecards, creating a continuous improvement loop.

Quantitative Analysis of Execution Quality

Demonstrating “all sufficient steps” relies heavily on post-trade quantitative analysis. Firms must perform TCA on their RFQ flow to measure execution quality against various benchmarks. This analysis provides the evidence needed to validate the effectiveness of the execution policy and the counterparty selection process.

A detailed Transaction Cost Analysis provides the definitive, quantitative evidence of a firm’s adherence to its best execution obligations.

The table below provides a hypothetical TCA report for a series of RFQ trades in corporate bonds, showcasing the level of detail required for effective monitoring.

Slippage is calculated as (Arrival Price – Execution Price) in basis points. A positive value indicates price improvement.

What Are the Reporting Obligations for RFQ Trades?

The execution process culminates in public disclosure and regulatory reporting, which serve as the ultimate proof of a compliant system. The two key reporting obligations are RTS 27 and RTS 28.

• RTS 27 Reports ▴ Execution venues, including systematic internalisers and other liquidity providers, must publish quarterly reports on execution quality. While the investment firm does not produce this report, it must consume this data as part of its ongoing monitoring of the LPs on its panel.
• RTS 28 Reports ▴ Investment firms must publish an annual report outlining their top five execution venues for each class of financial instruments, along with a summary of the analysis and conclusions drawn from their monitoring of execution quality. For firms heavily reliant on RFQs, this report will list their primary LPs and provide a detailed summary of why those venues consistently provided the best outcomes for clients.

These reporting requirements create a transparent ecosystem where execution quality can be compared across venues and firms. For the individual firm, the process of compiling the RTS 28 report is the final step in the execution loop, forcing a comprehensive annual review of its policies, counterparty choices, and overall effectiveness in meeting the best execution mandate.

Reflection

The architecture of best execution under MiFID II, particularly for RFQ-based systems, compels a fundamental re-evaluation of a firm’s operational design. The knowledge compiled here details the regulatory requirements and the strategic responses, but the ultimate implementation rests on a deeper question. How is your firm’s trading infrastructure currently configured to capture, analyze, and act upon execution quality data?

Consider the flow of information from the moment a client’s request arrives. Does your system treat each RFQ as a discrete event, or does it view it as an input into a constantly learning model of counterparty behavior and market conditions? The directive’s mandate for “all sufficient steps” is a call to build an intelligent execution framework.

This framework should not only satisfy auditors but also provide your traders with a quantifiable, data-driven edge. The true potential lies in transforming a compliance necessity into a source of competitive advantage and superior client service.