Revolutionizing Trade Surveillance with Big Data Intelligence

Trade Surveillance 360


  • Ingests any type of structured or unstructured data, including but not limited to: orders, trades, positions, market data, email, chat logs, user activity, KYC and CRM
  • Delivers “first generation,” rule-based controls plus “next generation” intelligence and analytical capabilities
  • Identifies and monitors risky traders and investment decision-makers using a multitude of out-of-the-box threat and behavior models coupled with trade and compliance analytics
  • Applies behavior models to surface the riskiest accounts, traders and securities
  • Configures and customizes additional policies and checks with ease
  • Holistic approach provides a view into all related activity of the risky entity
  • Rich interface provides investigative workbench for easy analysis
  • Centralized case management hub streamlines workflow from the point of behavior detection to investigation, escalation and resolution
  • Reduces false positives by up to 95 percent

Current Landscape

The regulatory landscape has shifted dramatically over the past few years. Regulatory controls are increasingly complex and time frames to comply are short. At the same time, the rise of automated, high frequency trading (HFT) has led to an explosion in the volume of trade activity we regulate and surveil for compliance. The complexity of the regulatory landscape plus the growing prevalence of HFT has given rise to new, automated trade surveillance technologies that are meant to help compliance teams monitor huge volumes of data.

There are a number of automated trade surveillance solutions in the market today that all work in similar ways: they monitor a narrow scope of trade activity and alert on infractions to a static set of predetermined rules. The result is an enormous flood of false positives. Compliance teams are left with the unenviable task of sifting through haystacks of alerts. It is labor intensive, expensive and ineffective. These are “first generation” trade surveillance technologies. They’re fast, but they’re not smart.

The need of the hour is an intelligent, automated approach to trade surveillance that integrates disparate data sets (e.g. orders, trades, positions, market data, chat, email, user activity) to produce accurate, context-enriched, sensible output. However, this level of data complexity could very easily escalate into data overload. Big data trading requires big data surveillance: a tool that infuses artificial intelligence into automated surveillance, allowing compliance officers to see more and do more in less time.

Our Approach

Securonix is the leader in big data security analytics. The company pioneered the use of user and entity behavior analytics (UEBA) to detect insider threats and cyber attacks on enterprise, and later expanded the application of its technologies to other use cases including trade surveillance.

Securonix Trade Surveillance 360 is leading the securities market toward a next generation, big data approach to trade surveillance. The platform ingests and cross-correlates any type of structured or unstructured data, recognizes noncompliance to static rules, applies UEBA to identify behavior anomalies and infuses unsupervised machine learning to produce artificial intelligence. The result is a sophisticated, automated trade surveillance solution that reduces false positives by 95 percent, detects truly high risk activity and narrows down the entities (traders, securities and accounts) compliance officers should focus on.

FIRST GENERATION: Traditional, Rule-Based Surveillance
Robust, out-of-the-box, static rules across different surveillance pillars including fiduciary obligation, market abuse, conflicts management, insider trading and personal account dealing.

NEXT GENERATION: Securonix Intelligent Surveillance
Overlay of sophisticated behavior models algorithms, analytics and cross correlation on static rules to surface the riskiest traders, portfolio managers, securities and accounts.

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