Solidus Labs Unveils Agentic-Based Compliance: A New Model for Trade Surveillance Operations
NEW YORK — Solidus Labs, the category-definer in trade surveillance and risk monitoring for digital and traditional asset classes, today announced the launch of Agentic-Based Compliance, a groundbreaking model for surveillance operations that leverages a network of AI agents to deliver exponential efficiency, precision, and intelligence across the entire trade surveillance and transaction monitoring investigation lifecycle.
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Legacy compliance solutions have failed to keep up with the rapid modernization and growing complexity of global markets. Compliance teams are forced to work with a patchwork of disconnected and expensive tools that fail to deliver results efficiently. According to McKinsey, compliance analysts spend 80% of their time on low or moderate-risk issues, often repetitively resolving false positives or performing menial work. This inefficiency extends to market abuse detection: Despite the enormous resources and efforts invested in compliance technology, firms continue to face enforcement actions for missed manipulation. Research shows that market abuse like insider trading occurs in 20% of mergers and acquisitions and 5% of quarterly earnings announcements in U.S. markets. More broadly, only 4% of Suspicious Activity Reports (SARs) lead to law enforcement investigations. This isn't a failure of effort – it's a failure of architecture.
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Built on Solidus' proprietary platform, HALO, Agentic-Based Compliance reimagines how financial institutions detect, investigate, and resolve market abuse risks. It replaces legacy systems and siloed workflows with a unified, intelligence-led architecture powered by autonomous AI agents that augment human analysts and operate across a multi-dimensional risk environment.
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'Agentic-Based Compliance is the only way compliance teams can stay ahead of emerging complexities like 24/7 off-platform trading, enhanced retail participation and the heightened risks they carry for cyber-enhanced financial crimes and cross-product and cross-market manipulation,' said Asaf Meir, Founder and Chief Executive of Solidus Labs. 'Our vision is simple: Compliance operations should be as scalable, intelligent, and efficient as the markets they're designed to protect. Solidus' Agentic-Based Compliance delivers just that, solving for tech sprawl, alert fatigue, talent shortage and surveillance blind spots that cost firms thousands of hours and can reach billions of dollars in losses and fines.'
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HALO embeds a fleet of purpose-built AI agents, each designed to streamline a specific stage of the compliance investigation lifecycle — from signal enrichment and alert remediation to model testing, OSINT intelligence feeds, case management, and regulatory reporting.
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Born in crypto's highly fragmented and complex environment, Solidus' Agentic-Based Compliance is future-proof by design for all asset classes, leading to 20X faster investigations and saving compliance analysts as much as 5 hours of menial work per day. Like all Solidus Labs' solutions, it was developed in tandem with regulatory feedback – aligning with the current and evolving demands of modern financial markets, including the imperatives of market abuse regulations in the U.S., EU, and other leading jurisdictions.
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Poised to power the next generation of surveillance operations, Solidus' Agentic-Based Compliance is already gaining traction among forward-looking financial firms seeking to modernize their compliance capabilities and reduce operational strain.
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Solidus Labs is the category-definer for Agentic-Based Compliance in trade surveillance and risk monitoring. Founded in 2018 by Goldman Sachs veterans, the company merges Wall Street rigor, crypto-native innovation, and cybersecurity principles to reinvent compliance for the modern financial era. At the core is HALO, an AI-powered risk-based platform trusted by financial institutions, crypto firms, and regulators globally to drive proactive, intelligence-led oversight — across any product, venue, or asset class.
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