Global Forex Brokerage Manages Cybersecurity Risk

Corvil's machine learning anomaly detection and risk assessment improves cybersecurity without impacting trading performance

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About the Customer

Global Forex Brokerage:

  • Provides online trading solutions for foreign exchange, derivatives, bullion, and commodities
  • Approximately $1.7 trillion in annual traded value
  • Approximately 20,000 active users, including institutional, private and retail investors


Escalating Cybersecurity Risks to Financial Markets Infrastructure

With regulators and industry experts asserting the systemic financial system risk of cyber-attacks, the firm was determined to protect its growing annual traded value from these threats, and maintain the high performance trading experience that attracted clients worldwide. While the firm had strict access control measures, defenses against external denial of service attacks and other data protection capabilities, it sought to extend its cyber defenses to address:

  • Inadequate visibility into attack indicators and unusual activity patterns on its internal networks
  • Limited insight to efficiently triage and investigate incidents without additional host-based performance-impacting logging and surveillance


Machine Learning-Based Threat Detection and Cybersecurity Risk Assessment

Analyzing approximately 1.25TB/day of granular, electronic transaction and network communications data, Corvil provided:

  • New levels of security analysis across user and host generated network traffic patterns, including baseline deviation analysis without impacting operational performance
  • Automated anomaly detection and risk assessment of new communications and traffic patterns
  • Correlated findings from multiple anomaly and threat detection methods to prioritize investigations
  • Automated daily and on-demand executive-consumable and operational level reporting of cyber-risk across the environment


More Effective Cyber Resilience with Zero Impact on Trading Performance

Scope of breach detection through more comprehensive visibility
Collaboration between trading operations and security teams
ROI of existing network analysis investment
Business performance impact of deploying security analytics
Deployment complexity by leveraging existing monitoring instrumentation

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