What Are the Regulatory Differences in Proving Best Execution under MiFID II and FINRA Rules?

Concept

The Two Mandates on Execution

At the highest level of abstraction, the best execution mandates enforced by the European Union’s Markets in Financial Instruments Directive (MiFID II) and the United States’ Financial Industry Regulatory Authority (FINRA) share a congruent purpose. Both frameworks are constructed to ensure that investment firms act in the best interest of their clients when executing orders. They exist to codify a firm’s fiduciary responsibility into a set of verifiable actions, protecting investors from conflicts of interest and suboptimal outcomes. The core principle is that a client’s order must be handled with diligence and care, seeking the most favorable terms reasonably available under the prevailing market conditions.

This shared objective, however, represents a point of departure, not a parallel journey. The operational and philosophical structures of their respective rule sets diverge significantly, creating distinct compliance challenges and strategic considerations for any firm operating across both jurisdictions.

The divergence begins with the prescriptive nature of the regulatory language. MiFID II, through its associated Regulatory Technical Standards (RTS), particularly RTS 27 and RTS 28, establishes a highly detailed and data-intensive reporting regime. It moves the requirement from “all reasonable steps” under its predecessor to “all sufficient steps,” a subtle but powerful shift in language that implies a more exhaustive and demonstrable process. This framework compels firms to quantify and publicly disclose their execution quality across a wide range of factors.

The European model is one of mandated transparency, operating on the principle that public data disclosure will foster competition between venues and empower clients to hold their brokers accountable. It is a system built on quantitative proof, demanding that firms not only achieve best execution but also generate the empirical evidence to prove it conclusively and publicly.

The fundamental distinction lies in MiFID II’s prescriptive, data-driven transparency versus FINRA’s principles-based, “reasonable diligence” standard.

Conversely, FINRA’s Rule 5310 approaches the same objective from a principles-based standpoint. It requires firms to use “reasonable diligence” to ascertain the best market for a security and to buy or sell in that market so the resulting price is as favorable as possible for the customer. While factors such as price, volatility, liquidity, and speed of execution are central to this diligence, the rule provides firms with more latitude in how they structure their review and documentation processes. The emphasis is on having a robust, systematic process for reviewing execution quality, which must be conducted regularly and rigorously, but the specific format of this review is not as rigidly defined as under MiFID II.

FINRA’s approach is less about public disclosure and more about internal process and supervisory oversight. It places the onus on the firm to build and defend its own methodology for achieving and verifying best execution, subject to regulatory examination.

Strategy

Calibrating the Compliance Engine

For a global financial institution, navigating the dual requirements of MiFID II and FINRA necessitates a sophisticated and adaptable compliance strategy. A firm cannot simply adopt the more stringent requirements of one regime and assume compliance with the other. The philosophical differences are too great. The strategic challenge is to build a unified best execution framework that is flexible enough to produce the distinct evidentiary outputs required by each regulator without creating redundant or conflicting internal processes.

This begins with the firm’s Order Execution Policy (OEP), a foundational document under both regimes, but one that serves different functions. Under MiFID II, the OEP is a detailed disclosure to clients, outlining the specific venues and factors considered for each instrument class. For FINRA, the equivalent policies and procedures are more of an internal guide that informs the firm’s “regular and rigorous” review process.

A successful strategy harmonizes the data collection process at the most granular level. Since MiFID II demands extensive data for its public RTS 27 (from venues) and RTS 28 (from firms) reports, a firm’s systems must be architected to capture a wide array of execution metrics. This includes not just price and cost, but also speed, likelihood of execution, and settlement size.

The strategic insight is to leverage this highly granular data, collected for MiFID II purposes, as the quantitative backbone for the more qualitative “regular and rigorous” reviews required by FINRA. The data provides the empirical foundation for justifying routing decisions and demonstrating to FINRA examiners that the firm’s diligence is not merely procedural but is informed by a deep, quantitative understanding of market quality across different venues.

Comparative Analysis of Core Obligations

The operational distinctions between the two regimes become clear when their core tenets are placed side-by-side. While both aim to protect the client, their methods for achieving this goal dictate different internal workflows, data architectures, and governance structures. A global firm must design its compliance systems to accommodate these differences from the ground up.

Managing Conflicts of Interest

Both regulatory frameworks are acutely concerned with managing conflicts of interest, particularly the practice of payment for order flow (PFOF). However, they approach the issue from different angles. MiFID II takes a hard line, effectively banning PFOF for investment firms providing portfolio management or independent advice, and imposing strict transparency requirements where it is permitted. The regime operates on the assumption that such payments can compromise a firm’s duty to its clients.

FINRA, while also viewing PFOF as a significant potential conflict, does not ban it outright. Instead, it requires firms to conduct rigorous reviews to ensure that routing decisions are based on execution quality, not the inducements received. A firm’s routing logic must be demonstrably free from the influence of PFOF, and this must be a key component of the quarterly review process.

A firm’s data architecture must be robust enough to satisfy MiFID II’s public reporting while also providing the analytical depth for FINRA’s internal reviews.

This creates a critical strategic decision point for a global firm. It may be operationally simpler to adopt the stricter MiFID II approach to PFOF across all business lines, thereby ensuring compliance in both jurisdictions. Alternatively, a firm could maintain separate policies, which would require a more complex and segregated compliance infrastructure to demonstrate to FINRA that its US-based PFOF arrangements do not compromise best execution, while simultaneously adhering to the stricter rules in Europe. The chosen path depends on the firm’s business model, risk appetite, and the sophistication of its compliance and data analysis capabilities.

Execution

The Transaction Cost Analysis Framework

At the point of execution, proving best execution transforms from a policy challenge into a data science problem. Transaction Cost Analysis (TCA) is the primary tool for meeting this challenge, yet its application differs substantially between the MiFID II and FINRA environments. Under MiFID II, TCA is not just an internal tool; it is the engine that produces the public-facing evidence of compliance. The RTS 28 reports require firms to provide a quantitative summary of the execution quality obtained from their top five venues for each class of financial instrument.

This necessitates a TCA framework capable of systematically analyzing vast amounts of trade data and presenting it according to prescribed regulatory templates. The analysis must go beyond simple price improvement metrics and incorporate a holistic view of total cost, including fees, commissions, and settlement charges.

For FINRA compliance, the role of TCA is more forensic and diagnostic. It is used internally to support the “regular and rigorous” review process. Here, the TCA system must be configured to compare execution quality across a range of potential venues, not just the ones used. This involves comparing execution speeds, fill rates, and price improvement statistics for the firm’s order flow against the execution quality achievable at competing market centers.

The output of this analysis forms the core of the documented review, providing the evidence that the firm has exercised “reasonable diligence.” A deficiency in this comparative analysis is a common finding in FINRA examinations. Therefore, the TCA system must be dynamic, capable of ingesting market-wide data and running hypothetical routing scenarios to defend the firm’s existing arrangements.

Key Procedural Steps for a Dual-Compliance Framework

A firm seeking compliance with both regimes must embed a series of critical procedures into its operational workflow. These steps ensure that data is captured correctly at the source and that the subsequent analysis meets the distinct requirements of each regulator.

• Data Capture at Point of Execution. All relevant order and execution data must be captured in real-time. This includes not only the price and size of the trade but also a host of metadata such as order type, client instructions, and timestamps to the millisecond level across the order lifecycle. For MiFID II, this data must be sufficient to populate the detailed fields of the RTS 27 and 28 reports.
• Establishment of a Best Execution Committee. A cross-functional committee, comprising representatives from trading, compliance, technology, and risk, should be responsible for overseeing the firm’s best execution policies and procedures. This committee would review the TCA reports, approve the Order Execution Policy, and document the rationale for venue selection and routing logic.
• Quarterly Rigorous Review. For FINRA purposes, a formal, documented review must be conducted at least quarterly. This review should leverage the TCA data to compare execution quality across venues on a security-by-security and order-by-order basis. Any identified deficiencies or material differences in quality must be addressed, and the rationale for any decisions must be recorded.
• Annual RTS 28 Reporting. For MiFID II, the firm must prepare and publish its annual RTS 28 report. This involves aggregating a full year’s worth of trading data, analyzing it to identify the top five execution venues for each instrument class, and summarizing the quality of execution obtained. This is a significant data management and analytical undertaking.

A Granular View of Required Data Points

The data intensity of the MiFID II regime is one of its defining characteristics. The table below illustrates the level of detail required for public reporting, which stands in contrast to the internal, process-oriented evidence required by FINRA. A global firm’s data infrastructure must be capable of capturing and reporting on these specific fields to meet its European obligations.

Reflection

From Obligation to Intelligence

Ultimately, the regulatory frameworks for best execution should be viewed as the minimum specification for a much more ambitious system. Compliance is the baseline. The true objective for a sophisticated institution is to transform the machinery of regulatory compliance into a source of competitive intelligence.

The vast quantities of data collected to satisfy MiFID II’s reporting mandates and FINRA’s review processes contain powerful insights into market microstructure, venue performance, and algorithmic behavior. A firm that merely generates reports to meet its obligations is squandering a valuable asset.

The next evolution in this domain involves moving beyond retrospective TCA to predictive execution routing. By applying advanced data analytics and machine learning models to the rich historical dataset mandated by the regulations, a firm can begin to forecast execution quality. The system can learn to predict the optimal placement for a given order, at a specific time, under certain market conditions, based on its desired execution profile.

This transforms the best execution process from a reactive, evidence-gathering exercise into a proactive, performance-enhancing engine. The question then shifts from “Did we achieve best execution?” to “How can we architect our systems to continuously redefine what best execution means for our clients?” The answer lies in viewing the regulatory requirements not as a burden, but as the foundational data layer for a superior execution intelligence system.