How Do MiFID II Best Execution Requirements Specifically Impact RFQ Workflows? ▴ Question

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Concept

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From Price Discovery to Demonstrable Process

The Markets in Financial Instruments Directive II (MiFID II) fundamentally recalibrated the operational calculus for institutional trading, extending its reach deep into the mechanics of Request for Quote (RFQ) workflows. This regulatory framework transformed the RFQ from a straightforward mechanism for bilateral price discovery into a highly structured and evidence-based process. The core of this transformation lies in the elevation of the best execution standard from taking “all reasonable steps” to “all sufficient steps” to achieve the best possible result for a client.

This linguistic shift imposes a higher, more quantifiable burden of proof on the investment firm. It necessitates a transition from a subjective assessment of a good price to an objective, auditable demonstration of a superior execution process across multiple factors.

For participants in RFQ markets, particularly in less liquid, over-the-counter (OTC) instruments, this means the conversation is no longer centered exclusively on the final price. Instead, the entire lifecycle of the quote solicitation becomes a data-gathering exercise designed to justify the final execution decision. The directive compels firms to systematically evaluate a range of execution factors beyond price, including costs, speed, and the likelihood of both execution and settlement.

This requirement forces a systemic change, embedding compliance and data capture into the very fabric of the trading workflow. The RFQ is no longer a discrete event but a continuous part of a firm’s obligation to monitor and prove the effectiveness of its execution arrangements.

MiFID II reframes the RFQ process, making the auditable trail of how an execution decision was reached as critical as the price itself.

This has profound implications for how liquidity is sourced and how relationships with counterparties are managed. The “legitimate reliance test” that once determined if best execution applied to a principal trade has been clarified and strengthened, making the firm’s responsibility more explicit. When a client relies on a firm to protect its interests in an RFQ, the firm must be able to produce a clear, data-backed narrative that validates its choice of counterparty and execution method. This creates a powerful incentive for the electronification and systematization of RFQ workflows, as manual processes struggle to provide the granular audit trail required for regulatory scrutiny.

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Strategy

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The Multi-Factor Execution Framework

Adapting to MiFID II’s stringent best execution requirements demands a strategic overhaul of the RFQ process, moving from a price-centric model to a holistic, multi-factor evaluation framework. Investment firms must design and implement a formal order execution policy that clearly defines how they will weigh various execution factors to achieve the best outcome for their clients. This policy is not a static document; it is a dynamic strategic guide that must be consistently applied, monitored, and reviewed for effectiveness. The strategic challenge lies in codifying a decision-making process that is both flexible enough to handle diverse market conditions and instrument types, yet rigorous enough to stand up to regulatory examination.

A core strategic shift involves the pre-definition of the relative importance of execution factors. For a liquid instrument in normal market conditions, price and cost may remain the predominant factors. However, for an illiquid or complex OTC product, factors like likelihood of execution, settlement finality, and minimizing market impact may take precedence.

The firm’s strategy must account for these nuances, creating a system that can justify why, for a specific trade, a seemingly worse price constituted a better overall execution. This requires a sophisticated approach to data gathering, including sourcing market data to check the fairness of prices for OTC products and comparing them with similar or comparable instruments where possible.

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Evolving the Counterparty Selection Calculus

The directive fundamentally alters the strategy for managing relationships with liquidity providers (LPs). A firm’s execution policy must detail the venues and counterparties it uses and the criteria for their selection. This moves the process beyond simple relationship-based trading to a quantitative and qualitative assessment of LP performance. Firms are now strategically incentivized to:

Systematically Track LP Performance ▴ Monitor metrics beyond just price, such as quote response times, rejection rates, and post-trade settlement efficiency. This data provides a defensible basis for including or excluding an LP from future RFQs.
Diversify Liquidity Pools ▴ Relying on a single or small group of LPs becomes difficult to justify. A robust strategy involves connecting to a broader range of execution venues, including regulated markets, Multilateral Trading Facilities (MTFs), and other Systematic Internalisers (SIs), to demonstrate that a comprehensive search for liquidity was undertaken.
Formalize Review Processes ▴ Implement regular, evidence-based reviews of the execution quality received from all venues and LPs. This fulfills the obligation to correct any deficiencies in the firm’s execution arrangements.

Under MiFID II, counterparty selection in RFQ workflows transitions from a relationship-based art to a data-driven science.

The following table illustrates the strategic shift in the RFQ process before and after the implementation of MiFID II’s best execution principles.

Process Component	Pre-MiFID II Strategy	Post-MiFID II Strategy
Primary Objective	Achieve the best possible price for a given trade.	Achieve the best possible result across a range of pre-defined execution factors (price, cost, speed, likelihood, etc.).
Decision Driver	Trader discretion and qualitative assessment of market conditions.	Adherence to a formal, client-consented Order Execution Policy.
Counterparty Selection	Based on established relationships and perceived competitiveness.	Based on systematic, data-driven analysis of LP performance and inclusion in a formal policy.
Record Keeping	Basic trade details and final execution price.	Granular capture of the entire RFQ lifecycle, including all quotes received, timestamps, and justification for the chosen execution.
Proof of Compliance	Difficult to demonstrate objectively; relied on market convention.	Demonstrable through detailed audit trails and quantitative reporting (e.g. Top 5 Venue reports).

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Execution

Operationalizing the Mandate for Sufficient Steps

The execution of an RFQ workflow under MiFID II is a disciplined, technology-dependent procedure. The mandate to take “all sufficient steps” translates into a requirement for a fully auditable and data-rich operational process. Investment firms must engineer their trading systems, primarily their Order Management Systems (OMS) and Execution Management Systems (EMS), to not only facilitate the RFQ but also to systematically capture the evidence needed to prove best execution. This moves the firm from a simple transactional model to one of continuous performance monitoring and reporting.

The operational workflow must provide a full audit of every trade, demonstrating that the execution was achieved at the best available price or, if not, providing a clear justification based on other execution factors. This involves capturing a snapshot of available liquidity at the moment of the trade, including all quotes received from the solicited counterparties. This data forms the core of the firm’s defense against any potential challenge to its execution quality.

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A Prescribed Workflow for Compliance

A MiFID II-compliant RFQ execution workflow can be broken down into a series of distinct, auditable stages. Each stage generates critical data points that feed into the firm’s best execution monitoring and reporting obligations.

Order Inception and Pre-Trade Analysis ▴ Upon receiving a client order, the system must first classify it according to the firm’s execution policy. This involves identifying the instrument type, size, and liquidity characteristics to determine the relative importance of the execution factors (e.g. is this a standard, liquid bond or a complex, illiquid derivative?).
Counterparty Selection and RFQ Dissemination ▴ The system selects a list of appropriate liquidity providers based on the pre-defined criteria in the execution policy. The selection must be justifiable and not merely based on habit. The RFQ is then sent to the selected LPs, and the system logs which LPs were solicited and at what time.
Quote Aggregation and Evaluation ▴ As quotes are returned, the system must capture and timestamp each one. The evaluation is conducted against the weighted execution factors. For instance, a quote with a slightly inferior price but a much higher certainty of execution (perhaps from a more reliable counterparty) might be ranked higher for an illiquid instrument.
Execution and Post-Trade Data Capture ▴ Once a quote is accepted, the execution is timestamped. The system must capture not only the winning quote but all competing quotes. This creates the “full book” view necessary for a complete audit trail. Information on execution speed (hold times) and any rejections is also logged.
Monitoring and Reporting ▴ The data captured from this workflow feeds directly into the firm’s quarterly execution quality reports and its annual Top 5 execution venue reports, as mandated by the regulation. This provides regulators and clients with transparency into the firm’s execution practices.

In the MiFID II paradigm, the RFQ workflow becomes a systematic assembly line for producing compliance evidence.

The following table provides a granular view of the data points that must be captured at each stage of the RFQ process to satisfy the best execution evidence requirements.

RFQ Stage	Required Data Points	MiFID II Justification
Pre-Trade	Client Order ID, Timestamp, Instrument Identifier (ISIN), Order Size, Order Type, Execution Factor Weighting (as per policy).	Demonstrates adherence to the Order Execution Policy and proper classification of the client’s needs.
Counterparty Selection	List of LPs selected for the RFQ, Justification for selection (e.g. top-ranked for this instrument type), Timestamp of RFQ dissemination.	Provides evidence that a sufficient and appropriate pool of liquidity was accessed.
Quoting	All quotes received from each LP (price, size), Timestamp for each quote, Quote response times, Rejection messages.	Creates the audit trail of available liquidity and forms the basis for the execution decision.
Execution	Winning LP, Executed Price & Size, Execution Timestamp, Comparison of executed price vs. all other quotes (implicit cost analysis).	The definitive record of the final trade, which can be compared against the available alternatives.
Post-Trade	Settlement status, Data for RTS 27/28 reports (venue and quality reporting), Record of any execution deficiencies identified.	Fulfills regulatory reporting requirements and completes the feedback loop for monitoring execution policy effectiveness.

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References

BofA Securities. “Order Execution Policy.” Bank of America, Accessed August 7, 2025.
European Securities and Markets Authority. “Guide for drafting/review of Execution Policy under MiFID II.” ESMA, 2018.
“Best Execution Under MiFID II.” FinanceFeeds, Accessed August 7, 2025.
Hogan Lovells. “Achieving best execution under MiFID II.” August 31, 2017.
International Capital Market Association. “MiFID II/R Fixed Income Best Execution Requirements.” ICMA, Accessed August 7, 2025.

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Reflection

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From Regulatory Burden to Competitive Intelligence

The comprehensive data capture mandated by MiFID II for RFQ workflows presents a significant operational undertaking. The initial focus for many firms was simply achieving compliance, viewing the requirements as a regulatory burden. However, the operational framework built to satisfy these rules creates a powerful byproduct ▴ a rich, proprietary dataset on execution quality and counterparty behavior. The strategic imperative now is to transform this compliance-driven data repository into a source of competitive intelligence.

The systems engineered to prove best execution are, in essence, sophisticated market surveillance tools. Analyzing this data reveals patterns in liquidity, optimal times to trade certain instruments, and the true cost of execution beyond the quoted price. It allows for a precise, quantitative evaluation of liquidity providers, moving far beyond anecdotal evidence.

The firm that masters this internal data flow can refine its execution strategies, optimize its counterparty relationships, and ultimately provide a superior execution service to its clients. The mandate for transparency, therefore, contains the blueprint for a more efficient and intelligent execution process.