AI-assisted trade surveillance software for spoofing, layering, wash-trades—end-to-end market abuse surveillance.
Market manipulation (spoofing, wash trading, insider trading, pump & dump schemes, etc.) poses serious threats to brokerages and market integrity. H3M’s KROTON analytics platform is designed for SEC- and CIRO-regulated brokerages to spot these schemes using AI-driven surveillance. Its modules – Suspect Miner, Link Miner, and RUMI – work
Market manipulation (spoofing, wash trading, insider trading, pump & dump schemes, etc.) poses serious threats to brokerages and market integrity. H3M’s KROTON analytics platform is designed for SEC- and CIRO-regulated brokerages to spot these schemes using AI-driven surveillance. Its modules – Suspect Miner, Link Miner, and RUMI – work together to flag anomalous trading and collusion in real time. By combining machine learning with network analysis and external intelligence, KROTON delivers daily alerts and auditable signals of manipulation. In the AkInvest case study below, our solution successfully identified coordinated manipulations in stock trading.
H3M built KROTON for regulated broker-dealers. It aligns with SEC, CIRO (and IIROC) requirements for market surveillance and best execution oversight. The platform’s daily alerts fit into standard compliance workflows, ensuring suspicious trades are reviewed promptly every day. With full audit trails – including data lineage and model r
H3M built KROTON for regulated broker-dealers. It aligns with SEC, CIRO (and IIROC) requirements for market surveillance and best execution oversight. The platform’s daily alerts fit into standard compliance workflows, ensuring suspicious trades are reviewed promptly every day. With full audit trails – including data lineage and model rationale for each alert – firms can easily document their surveillance efforts for regulators. KROTON’s network-based detection also addresses regulators’ focus on collusion and systemic abuse: instead of isolated alarms, it reveals the broader behavior of trading groups. In sum, KROTON helps compliance officers demonstrate proactive, evidence-based monitoring of market manipulation.
CIRO Rule Alignment with KROTON AI Modules
Detailed cross-reference of KROTON modules with CIRO Investment-Dealer rules—covering KYC, sanctions, trade surveillance, audit-trail & supervision.
Trade surveillance analyzes orders and executions to flag market-abuse patterns such as spoofing, layering, wash trading, ramping/marking the close, pump-and-dump, cross-venue manipulation, and insider-trading–like behaviors (e.g., repeated profitable trading around material events). Scenarios evaluate intent signals (order placement/cancel timing, order-to-trade ratios) alongside market context to separate benign activity from manipulative tactics.
Yes. You can monitor near real-time order flow (API/stream) for urgent behaviors and run end-of-day or periodic batches for deeper analytics. Policies stay consistent across channels and venues. Actual latency depends on feeds and infrastructure, but the design supports T+0 alerting, so high-risk patterns are escalated promptly while longer-horizon reviews run on schedule.
Core inputs include OMS/EMS data (orders, amendments, cancels, fills), venue identifiers, trader/desk IDs, account hierarchies, and market data (L1/L2) plus reference data (symbols, instruments, calendars). Many firms also add device/IP, counterparty and settlement data, and optionally comms metadata for context. Cross-venue, cross-asset ingestion helps detect abuse that spans markets.
Use Scenario Manager to combine flexible filters (venue, instrument, trader, time-window), velocity/ratio checks, and conditional logic. Backtest and champion–challenger new versions against guardrail KPIs (precision/recall, alert volume, case yield). Active Learning surfaces uncertain/novel patterns for review, and reason codes keep outcomes explainable—reducing noise without weakening coverage.
Yes. Link Miner maps relationships across accounts, devices, IPs, shared beneficiaries/counterparties, and order overlap, then highlights strong connections and hubs. Analysts see clusters that indicate collusive spoofing, wash pairs, or coordinated ramping. This network context complements rule scenarios and reveals organized behavior that single-account rules miss.
Alerts land in Case Manager with a full timeline (orders→cancels→fills), contributing factors, and market-snapshot context. Analysts follow a two-level approval workflow, attach evidence, and export regulator-ready reports in consistent formats. All actions—thresholds, versions, dispositions—are audit-trailed, giving clean hand-offs to QA, internal audit, and supervisors.
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