FINRA Rule 6893

This distinction matters because it shapes what a compliance examination reasonably can and cannot fault a firm for regarding LEI accuracy. A firm that submits an LEI a customer itself provided, without independent reason to doubt its accuracy, has not violated Rule 6893(b) even if that LEI later proves to be incorrect, since the firm did not knowingly submit inaccurate information. A firm that discovers a specific LEI is wrong, however, and continues submitting it anyway without correction, would fall squarely within the conduct this provision prohibits.

The Error Rate and Compliance Threshold Framework

Paragraph (c) establishes the more consequential, quantitative dimension of Rule 6893: if an Industry Member reports data to the Central Repository with errors such that the error percentage exceeds the maximum Error Rate the Operating Committee has established under the CAT NMS Plan, that Industry Member is not in compliance with the Rule 6800 Series. This Error Rate functions as an aggregate, industry-wide ceiling, a threshold FINRA and the other Participants apply uniformly rather than tailoring firm by firm.

Paragraph (d) then layers a second, genuinely distinct concept on top of this aggregate standard: each Industry Member must separately meet its own individualized Compliance Threshold, comparing that specific member's own error rate against the broader aggregate Error Rate over a defined measurement period. Candidates and practitioners should understand precisely how these two concepts differ and interact. The Error Rate is a single, industry-wide ceiling; the Compliance Threshold is a firm-specific metric measuring how that individual firm's own performance compares against the aggregate standard, potentially serving as a basis for further FINRA review or inquiry into that specific firm's CAT reporting practices. Critically, FINRA has been explicit that falling short of an individual firm's Compliance Threshold does not, as a matter of law, automatically establish that the firm has violated the Rule Series; it functions as a surveillance and monitoring trigger rather than an automatic violation finding, a meaningfully different legal consequence than exceeding the aggregate Error Rate under paragraph (c) carries.

The August 2023 Enforcement Action

Rule 6893 moved from a largely theoretical compliance standard to a demonstrated, actively enforced one through a significant FINRA enforcement action announced on August 16, 2023. FINRA's Enforcement Division reached an industry settlement addressing violations of Rules 6830, 6893, 2010, and FINRA's general supervision rule, Rule 3110, arising from CAT reporting deficiencies that, over time, accumulated to tens of billions of erroneous CAT events. The resulting sanctions included censure, substantial fines, and a requirement that the firm retain an Independent Consultant to review and help remediate its CAT reporting deficiencies going forward, sanctions of a magnitude that signaled FINRA's willingness to pursue serious enforcement consequences for sustained, large-scale CAT data quality failures rather than treating Rule 6893 as a purely aspirational standard.

This action illustrates the practical relationship between Rule 6893 and Rule 2010, FINRA's general commercial honor and just and equitable principles of trade standard: a sustained, sufficiently severe pattern of CAT reporting failures does not merely expose a firm to a technical Rule 6893 finding, but can independently support a broader Rule 2010 violation and an accompanying Rule 3110 supervisory failure finding, layering multiple distinct violations onto what began as a data quality problem. Industry commentary following this action has suggested it likely marks the beginning of a sustained, multi-year period of CAT-related regulatory findings, drawing a direct historical parallel to OATS, which generated regulatory findings and enforcement activity across more than two decades of its own operational life before its 2021 retirement.

What Counts as Inaccurate or Incomplete Reporting in Practice

FINRA's own examination guidance identifies specific data fields that most commonly generate Rule 6893-related findings when reported incorrectly or incompletely, including the Event Timestamp, Event Type Code, Time in Force, Account Holder Type, Handling Instructions, Trading Session ID, and Firm Designated ID. This list gives firms concrete guidance on where to concentrate quality assurance efforts, since these represent the specific fields FINRA's own examination experience has identified as recurring sources of data quality deficiency across the industry, rather than an abstract, undifferentiated category of "errors" firms must guess at addressing.

FINRA has also specifically flagged unreasonable third-party vendor supervision as a distinct examination finding connected to this broader data quality framework, addressing firms that fail to establish reasonable written supervisory procedures covering CAT reporting and clock synchronization performed by third-party vendors on the firm's behalf. This ties Rule 6893's data quality standard directly back to the non-delegation principle discussed in the Rule 6870 entry elsewhere in this dictionary: a firm relying on a vendor for CAT reporting remains fully exposed to Rule 6893 data quality findings regardless of whether the underlying error originated in the firm's own systems or in a vendor's.

Self-Reporting as a Mitigating Practice

FINRA maintains a dedicated FINRA CAT Self-Reporting Erroneous Events Form, alongside the FINRA CAT Help Desk, specifically for firms that discover their own CAT reporting issues and wish to proactively disclose them. FINRA's examination guidance treats this kind of proactive self-reporting as a favorable factor firms should actively utilize, since a firm that identifies and discloses its own data quality problem, rather than waiting for FINRA to independently discover the same issue through examination, is generally viewed considerably more favorably in how FINRA calibrates its ultimate enforcement response.

Why This Enforcement Action Signals a Broader Regulatory Shift

The scale of the August 2023 action, tens of billions of erroneous events accumulated over time, deserves careful interpretation rather than simply being read as evidence of one firm's exceptional carelessness. CAT's sheer data volume means that even a comparatively low percentage error rate, applied across the enormous number of Reportable Events a large, active firm generates daily, can compound into an astronomically large absolute number of erroneous events over a sustained period. This mathematical reality means firms should not take false comfort from a seemingly low percentage-based error rate without also considering what that percentage translates to in absolute terms given the firm's actual reporting volume, since a rate that sounds modest in isolation can still represent an enormous number of individually inaccurate records once multiplied across CAT's characteristic scale.

FINRA's decision to pursue this matter through a formal enforcement action, rather than resolving it through the Minor Rule Violation Plan discussed elsewhere in this dictionary, itself signals something important about how FINRA calibrates its response to CAT data quality problems. The MRVP framework exists specifically for minor, technical violations; a sustained, multi-year pattern generating tens of billions of erroneous events, evidencing what FINRA characterized as an underlying supervisory failure under Rule 3110, falls well outside what any reasonable minor-violation framework was designed to address. Firms should understand this as FINRA drawing a genuine, meaningful line between isolated technical lapses appropriate for streamlined resolution and systemic, sustained data quality failures warranting FINRA's full disciplinary apparatus, including public censure, substantial monetary sanctions, and mandated independent oversight extending over a multi-year remediation period.

A Worked Illustration of the Error Rate and Compliance Threshold Distinction

Consider two hypothetical firms operating in the same reporting period. Firm A reports CAT data with an error rate that happens to exceed the maximum Error Rate the Operating Committee has established under paragraph (c); this places Firm A in direct, straightforward non-compliance with the Rule 6800 Series, a finding that follows mechanically from the numeric comparison itself. Firm B, by contrast, reports data with an error rate below the aggregate Error Rate ceiling, but that error rate is nonetheless meaningfully higher than the average performance of its peers, causing Firm B to fall short of its own individualized Compliance Threshold under paragraph (d).

Firm B has not, by virtue of this Compliance Threshold shortfall alone, been found in violation of Rule 6893; FINRA's own guidance is explicit that this outcome instead functions as a surveillance trigger, prompting further review or inquiry into why Firm B's performance lags its peers despite remaining within the overall industry ceiling. Firm B's actual compliance exposure depends on what that further review reveals: if the underlying cause traces back to a genuine, correctable operational gap that Firm B addresses promptly once identified, the Compliance Threshold shortfall alone is unlikely to escalate into a formal violation finding. If, however, FINRA's review reveals the kind of sustained, unaddressed, systemic problem the August 2023 enforcement action ultimately involved, that same starting point, an initial Compliance Threshold shortfall, could indeed develop into significant enforcement exposure over time, illustrating why firms should treat a Compliance Threshold shortfall as a genuine early warning signal rather than dismissing it simply because it does not carry automatic violation consequences on its own.

Relevance Across FINRA's Exam Programs

The SIE, Series 63, and Series 65 do not test Rule 6893's specific data quality mechanics, since these exams do not reach into CAT's technical compliance infrastructure. A Series 7 candidate is unlikely to encounter this rule directly, though the 2023 enforcement action's scale illustrates a broader lesson relevant across FINRA regulation generally: sustained, large-scale technical compliance failures can generate serious regulatory consequences even where no single instance of misconduct was individually egregious.

A Series 24 candidate supervising CAT compliance needs precise command of the Error Rate versus Compliance Threshold distinction, since a principal reviewing the firm's CAT performance metrics needs to understand that falling short of the firm's own Compliance Threshold is a monitoring trigger warranting investigation, not an automatic violation, while exceeding the industry-wide Error Rate under paragraph (c) carries more direct compliance consequences. A principal should also understand the 2023 enforcement action as a genuine precedent illustrating how Rule 6893 findings can combine with Rule 2010 and Rule 3110 findings when the underlying data quality problem is sufficiently sustained and severe. A Series 57 candidate handling order entry should understand the specific data fields FINRA's examination guidance flags most frequently, since accuracy in these particular fields at the point of order entry meaningfully reduces the firm's overall CAT data quality risk.

Practical Guidance for Firms

Firms should build ongoing monitoring of both the aggregate industry Error Rate and their own individual Compliance Threshold performance into their regular CAT compliance reporting to senior management, treating a Compliance Threshold shortfall as a genuine trigger for internal investigation rather than dismissing it simply because falling short of the threshold does not automatically constitute a violation. Given that FINRA itself uses this metric as a surveillance trigger, a firm that proactively investigates and addresses a Compliance Threshold shortfall before FINRA raises the issue independently is in a considerably stronger position than a firm that waits for external inquiry.

Firms should treat the August 2023 enforcement action as a direct, cautionary case study rather than an abstract regulatory development, specifically reviewing whether their own CAT reporting infrastructure and vendor supervision practices could be vulnerable to the same kind of sustained, large-scale accumulation of errors that generated that action's severe sanctions. A firm's own internal CAT quality assurance review should specifically prioritize the data fields FINRA has identified as most frequently problematic, including Event Timestamp, Event Type Code, Time in Force, Account Holder Type, Handling Instructions, Trading Session ID, and Firm Designated ID, rather than treating quality assurance as a generalized, undifferentiated review effort.

Firms should actively utilize the FINRA CAT Self-Reporting Erroneous Events Form whenever they discover a genuine CAT reporting deficiency internally, rather than treating self-disclosure as an unnecessary invitation to regulatory scrutiny. Given FINRA's demonstrated favorable treatment of proactive self-reporting, and the severe consequences the 2023 enforcement action illustrates for sustained, undisclosed data quality failures, firms should build a clear internal escalation path ensuring that any significant CAT reporting issue discovered through internal review is promptly evaluated for self-reporting rather than allowed to persist undisclosed while the firm attempts to quietly remediate it internally.

Firms should specifically model their own error rate in absolute terms, not merely as a percentage, given how the August 2023 action illustrates that a seemingly modest percentage error rate can still translate into an enormous absolute volume of erroneous records once multiplied across a firm's actual reporting activity. A firm's own internal risk assessment should calculate what its current error rate percentage actually represents in raw event counts over a monthly or quarterly period, giving senior management a more intuitive, tangible sense of the data quality problem's true scale than a bare percentage figure alone would convey.

Firms should also recognize that FINRA's decision to pursue full enforcement action, rather than MRVP resolution, in the August 2023 matter reflects a meaningful line firms should keep in view when assessing their own risk exposure. A firm with an isolated, promptly corrected data quality lapse faces a fundamentally different regulatory posture than a firm with a sustained, multi-year pattern reflecting an underlying supervisory gap, and firms should ensure their own internal escalation and remediation processes are robust enough to keep any identified data quality issue firmly in the former category rather than allowing it to develop into the latter through inattention or delayed remediation.