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Market Integrity Monitoring: 4-Week Assessment

MAQ Software

The Challenge

Market abuse, manipulation, and information leakage rarely announce themselves. In fast-moving trading environments, surveillance still depends on periodic, sampled, manual review — leaving windows where spoofing, layering, insider dealing, and cross-channel leakage go undetected until after the damage is done. Alert backlogs, false positives, and siloed trade-versus-communications data compound the exposure.

Do you know how quickly you could detect a coordinated manipulation pattern today — in minutes, or only after end-of-day review?

MAQ Software's 4-Week Market Integrity Monitoring Feasibility & Prototype Assessment moves you from periodic review to a working prototype of an always-on surveillance agent — validating detection value against your real trading and communications data using Azure AI Foundry, Azure Machine Learning, Microsoft Sentinel, and Microsoft Fabric.

Key questions

  • Can you detect market abuse patterns in near real-time, or only through periodic, after-the-fact review?
  • Are trading signals and communications data correlated to surface intent, or reviewed in isolation?
  • Do your current surveillance tools generate so many false positives that real signals are buried?
  • Can you explain and reconstruct why an alert fired to satisfy regulators, auditors, and internal risk committees?
  • Is agentic, continuous monitoring feasible on your data — and what would a production rollout require?

Our approach

  1. Week 1: Discovery & Scenario Definition — Workshop with SecOps, compliance, and trading surveillance leads to prioritize abuse scenarios (spoofing, layering, insider dealing, information leakage). Map current detection gaps, review times, and false-positive pain. Define success metrics for the prototype.
  2. Week 2: Data & Signal Assessment — Assess available trading, order-book, and communications data. Evaluate ingestion into Microsoft Fabric (Real-Time Intelligence / Eventstream) and signal readiness for Azure Machine Learning. Confirm Sentinel integration points for correlation and alerting.
  3. Weeks 3–4: Prototype Build & Validation — Build a scoped surveillance-agent prototype on Azure AI Foundry that correlates trading and communications signals and flags anomalies in near real-time. Validate detection quality against sample cases with your team. Deliver findings, feasibility verdict, and a production roadmap in an executive readout.

Deliverables

  • Abuse Scenario & Gap Analysis — Prioritized market-abuse scenarios mapped against current detection coverage and review latency
  • Data & Signal Readiness Report — Assessment of trading and communications data for real-time monitoring on Fabric and Azure ML
  • Working Prototype — Scoped surveillance-agent prototype on Azure AI Foundry with near real-time anomaly flagging
  • Validation Summary — Detection results against sample cases, including false-positive observations and explainability notes
  • Implementation Roadmap — Prioritized path to production with effort estimates, sequencing, and quick wins

Business impact

  • Move from periodic sampling to near real-time detection of market abuse and information leakage
  • Validate feasibility on your own data before committing to a full surveillance build
  • Correlate trading and communications signals to surface intent that isolated reviews miss
  • Reduce false-positive noise so analysts focus on genuine, high-risk cases
  • Strengthen audit-readiness with traceable, explainable alerts for regulators and risk committees

Who benefits

Users: Trade Surveillance Analysts, Security Operations Engineers, Compliance & Market Abuse Officers, BI & Data Platform Leads

Decision makers: CISOs, Chief Compliance Officers, Heads of Financial Crime / Market Integrity, VP of IT / IT Directors

Prerequisites

  • Read access to sample trading, order-book, and communications data (partial or anonymized samples are fine)
  • Access to existing surveillance policies, abuse typologies, and current detection tooling
  • Azure environment availability for prototype deployment (Azure AI Foundry, Azure ML, Fabric, Sentinel)
  • Key stakeholder availability for workshops in Weeks 1 and 4 (surveillance, compliance, SecOps, data)

Why MAQ Software

  • Structured, repeatable methodology — our feasibility framework is purpose-built for agentic surveillance on Azure, not a generic analytics review
  • Business + technical coverage — we bridge compliance and market-integrity requirements with data and AI engineering, ensuring the prototype reflects real regulatory needs
  • Clear path forward — this assessment produces a validated prototype and roadmap, giving you an immediate next step toward production surveillance

Contact us: CustomerSuccess@MAQSoftware.com to schedule your Market Integrity Monitoring Assessment and take the first step toward continuous, explainable surveillance.

لمحة سريعة

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