Synopsis: Artius Global addresses the “AI hallucination hurdle” pertaining to regulatory compliance. Traditional Large Language Models (LLMs) fail to deliver in financial environments where compliance is everything and the synergy of Retrieval-Augmented Generation (RAG) and Knowledge Graphs is creating the new standard for grounded, client-specific intelligence a massive delta from today’s pure hallucination. Discover how we are moving beyond probabilistic guesses towards a future of predictive, auditable, and automated compliance.
AI in the Regulatory Compliance Space
In the rapidly evolving world of regulatory compliance, AI is advancing at an even faster pace. This raises an important question: can AI ever keep up with, or even outpace, the speed of regulatory change to help tackle compliance challenge of both understanding and keeping up to date with new regulations? At Artius Global, this is a question we are actively exploring as part of our strategic direction, laying the foundation for how we integrate AI responsibly into our platform and compliance workflows.
Challenges with AI in Compliance
AI has been hailed as the ultimate efficiency tool, but for compliance officers, it carries a “trust tax.” Most users have heard the cautionary tales like the well-publicized case of attorney Michael Fourte, who submitted court filings containing fabricated citations generated by an AI.In a field where a single misinterpretation of a filing threshold or a missed effective date can trigger multi-million dollar sanctions, “mostly right” is the same as “entirely wrong.”
The Core Conflict:
Traditional AI is non-deterministic. It predicts the next most likely word based on patterns in vast datasets.
RegTech is deterministic. It requires specific logic, legal reasoning, and absolute adherence to the letter of the law to ensure an accurate response.
Grounded AI with RAG: Reducing Risk
At Artius Global, we are looking to address this challenge by utilising Retrieval-Augmented Generation (RAG). RAG ensures that AI outputs are anchored to authoritative regulatory sources, preventing hallucinations and generating factual results.
Grounding in facts: Every answer references actual filings, rules, or guidance.
Traceability: Outputs can be audited, showing exactly which source documents informed the AI’s response.
Accuracy: By retrieving relevant data first, the AI avoids creating plausible but incorrect information.
With RAG, compliance teams can leverage AI to quickly extract and interpret regulatory information with confidence, knowing the system is grounded in reality rather than probability.
Knowledge Graphs: The Next Step in Intelligent Compliance
While RAG provides reliable answers, knowledge graphs take compliance AI to the next level. By structuring regulatory information including rules, thresholds, jurisdictions, exemptions, and effective dates knowledge graphs allow AI to not only provide correct answers but also map them to your organization’s unique context.
Client-specific mapping: The system can determine which rules apply to specific business units, portfolios, or operations.
Holistic intelligence: Combining RAG with a knowledge graph transforms AI from a retrieval tool into an anticipatory compliance copilot.
In essence, RAG solves the “accuracy problem”, ensuring outputs are grounded and verifiable. Knowledge graphs then solve the “context problem”, tailoring those outputs to your organization and enabling predictive, actionable intelligence. Together, they create a system that is not only fast and scalable but also defensible, auditable, and forward-looking.
This is just the first part of Artius Global’s journey. Watch this space as we continue to explore how the AI space is rapidly growing, the emerging trends in generative and predictive AI, and how Artius Global plans to harness these innovations to enhance compliance intelligence for our clients.
