Post Trade Compliance

Post-Trade Compliance

Core Concepts

Trade Surveillance Framework

Trade surveillance is the systematic, ongoing monitoring of executed transactions to detect potential violations of securities laws, firm policies, and regulatory rules. A surveillance program operates across multiple time horizons:

• T+0 (same-day) monitoring — Real-time or end-of-day reviews targeting time-sensitive patterns such as front-running (trading ahead of a customer block order), late trading (mutual fund orders placed after the 4:00 p.m. ET NAV pricing cutoff), and marking the close (orders placed to influence the closing price). T+0 alerts require immediate investigation because the regulatory harm is ongoing or the evidence window is narrow.
• T+1 through T+3 monitoring — Next-day and settlement-window reviews for patterns that emerge across a short sequence of events: allocation fairness on block trades, partial fill distribution, and settlement failures. These alerts align with the trade settlement cycle and CAT error correction windows.
• T+N rolling-window monitoring — Longer-horizon reviews (weekly, monthly, quarterly) for patterns that only become visible over time: churning and excessive trading (turnover ratios measured over months), coordinated trading across accounts, systematic favoritism in allocations, and insider trading correlations (trading patterns around earnings announcements or M&A events). Rolling windows must be calibrated to the specific pattern — churning detection typically requires 3-12 months of data, while insider trading correlation windows may span 30-90 days around a material event.

Surveillance scope varies by firm type and business activity. A full-service broker-dealer conducting equities, fixed income, and derivatives trading must maintain surveillance across all asset classes. An RIA managing model portfolios may focus surveillance on allocation fairness, best execution, and personal trading. The surveillance program must cover both customer/client accounts and proprietary/firm accounts.

Alert generation is the process of applying quantitative thresholds, pattern matching rules, or scoring models to transaction data to produce alerts requiring human review. Effective alert generation requires clean, normalized data from multiple sources: order management systems, execution management systems, account master data, market data, and — for insider trading detection — corporate event calendars and restricted lists.

Investigation workflow follows a standard lifecycle:

1. Alert generation
2. Initial triage and prioritization
3. Investigation and fact gathering
4. Disposition (close with no finding, close with finding, escalate)
5. Escalation to senior compliance or legal
6. Regulatory filing if warranted (SAR, STR, or self-report)

Each stage must be documented in a case management system with timestamps, analyst notes, evidence, and supervisory sign-off.

Disposition and escalation decisions are among the most consequential in a compliance program. A disposition of "no finding" must be supported by documented analysis — regulators will review closed alerts during examinations. Escalation criteria should be defined in written procedures: escalate when the pattern is consistent with a securities law violation, when the activity involves a senior person or high-risk account, when the dollar amount exceeds a defined threshold, or when a pattern recurs after a prior warning.

Regulatory filing triggers — Post-trade surveillance may identify activity that requires a SAR filing (for broker-dealers; FinCEN's 2024 rule extending AML program and SAR obligations to covered investment advisers, originally effective January 1, 2026, was postponed to January 1, 2028 by a final rule issued December 2025), an STR (Suspicious Transaction Report, the international equivalent under FATF standards), or a self-report to FINRA or the SEC. The decision to file a SAR based on surveillance findings must be made by the AML Compliance Officer in coordination with the surveillance team. The SAR tipping-off prohibition (31 U.S.C. Section 5318(g)(2)) applies — the subject of the surveillance alert must not be informed of a SAR filing.

Pattern Detection

Surveillance systems must be designed to detect specific prohibited trading patterns. Each pattern has distinct data requirements, detection logic, and evidentiary standards:

Churning / excessive trading — Quantitative metrics include turnover ratio (aggregate purchases divided by average equity, with ratios above 6 presumptively excessive), cost-to-equity ratio (annualized costs as a percentage of average equity, with ratios above 20% generally excessive), and in-and-out trading frequency. Detection requires account-level transaction history, commission and fee data, and the customer's stated investment objectives. Churning surveillance is typically run on a rolling 3-12 month window.

Front-running — Trading in a firm or personal account ahead of a pending customer order that is expected to move the market. Detection requires correlating proprietary/personal trading activity with the timestamps of customer order receipt and execution. Key data elements: order receipt time (from CAT or order management system), execution time, account ownership, and the direction and size of the customer order. Front-running alerts are time-sensitive and should be generated on T+0 or T+1.

Cherry-picking (favorable allocations) — A pattern where an adviser or trader allocates profitable trades to favored accounts and unprofitable trades to disfavored accounts. Detection involves comparing the performance of allocations across accounts within a block trade or across trades over time. Statistical methods include comparing average returns by account against the expected distribution under fair allocation. Cherry-picking is a form of fraud that violates fiduciary duty and Section 10(b) of the Exchange Act.

Insider trading — Trading by persons with access to material non-public information (MNPI) ahead of corporate events such as earnings announcements, M&A transactions, FDA approvals, or regulatory actions. Detection requires correlating trading activity with an events calendar and identifying trades that are unusual in timing, size, or profitability relative to the trader's historical pattern. Insider trading surveillance often relies on restricted list and watch list monitoring, where securities of companies about which the firm possesses MNPI are placed on restricted or watch lists and trading activity is monitored or prohibited.

Layering / spoofing — Placing non-bona fide orders on one side of the order book to create a false impression of supply or demand, then executing on the opposite side and canceling the layered orders. Detection requires order-level data (not just executions) including order submissions, modifications, and cancellations with timestamps. Key indicators: high order-to-execution ratios, rapid cancellation patterns, and consistent profitability on the execution side when layered orders are present.

Wash trading — Simultaneously or near-simultaneously buying and selling the same security with no change in beneficial ownership, creating the appearance of market activity. Detection involves identifying offsetting transactions in the same security, same account (or related accounts), within a narrow time window. Wash trading can also occur across accounts controlled by the same beneficial owner.

Marking the close — Placing orders near the end of the trading session to influence the closing price. Detection requires analyzing order timestamps relative to market close, particularly for securities where the closing price affects portfolio valuations, options settlements, or performance calculations. Key indicator: late-session orders in securities where the firm or its clients have a valuation interest.