While technological solutions are essential, they must be integrated into the fabric of the business, rather than deploxyed in isolation, or without considering interrelated use cases and activities.
A few shifts that I’ve observed in the market related to regulatory change solutions that illustrates the need for an integrated approach and ToM, described in the following three phases of maturity:
- Firehose stage: unfiltered volume, low relevance
Firms operate reactively, consuming large volumes of global regulatory data with minimal discrimination. The lack of filtering leads to information overload, high manual effort, and significant noise, making it difficult to identify actionable change.
- Structured intelligence stage – contextual filtering and relevance
Organisations begin applying structured taxonomies, ontologies, and rule-based filters to segment regulatory data. This enables the exclusion of irrelevant content and aligns regulatory updates to business-specific domains, reducing manual triage and improving signal-to-noise ratio.
- Integrated governance stage – data-driven traceability and control alignment
Regulatory intelligence becomes fully integrated with internal governance structures. Obligations are automatically mapped to relevant policies, controls and risk frameworks. This traceability supports impact analysis, accountability, and proactive change management, enabling demonstrable compliance and operational agility.
Technology should serve the ToM, ensuring that every compliance process, data element, and decision is traceable, efficient, risk-aligned, and strategically governed.
As regulatory compliance becomes increasingly data-driven, the next frontier is the deployment of AI and AI agents to manage various aspects of the regulatory lifecycle autonomously. Institutions that future-proof their Operating Models today will be in the best position to harness these innovations safely, responsibly, and competitively.
Future-proofing a regulatory lifecycle ToM for AI readiness involves several key components:
- Data Readiness: Ensuring that regulatory and compliance data is centralised, structured and of high quality. This data will serve as a reliable foundation for AI models.
- Workflow Modularity: Designing compliance workflows that are modular and API-enabled. This allows AI agents to integrate with specific tasks such as regulatory monitoring, control testing, issue triage, and evidence gathering.
- AI Governance: Establishing governance frameworks to oversee AI and agent-based decision-making. This ensures transparency, explainability, and compliance with emerging AI regulations, such as the EU AI Act.
- Human-AI Collaboration Models: Defining “human-in-the-loop” and “human-on-the-loop” controls, where compliance professionals oversee and enhance AI-driven processes instead of being replaced by them.
- Continuous Learning Loops: Embedding mechanisms for AI agents to continually learn from regulatory developments, enforcement actions, and operational outcomes, thereby refining compliance operations over time.
An AI-enabled ToM will not only streamline current compliance activities but also transform compliance from a reactive function into a predictive and advisory capability.
This model can anticipate regulatory changes, adapt controls dynamically, and provide real-time assurance to regulators, executive management, and the Board.
Conclusion: Building a Resilient and Intelligent Risk and Compliance Function
Creating a robust, technology-enabled, and future-ready Target Operating Model is not optional; it is a strategic necessity for financial institutions facing increasing regulatory complexity and digital disruption.
Firms that invest in aligning their people, processes, technology, data, and governance under a unified ToM will be better positioned to:
- Navigate regulatory changes with agility
- Strengthen regulatory trust and credibility
- Drive operational resilience and efficiency
- Unlock the transformational potential of AI
The time to act is now. Those who lay strong foundations today will define the compliant, efficient and intelligent organisations of tomorrow.
By Freddie Frith, Corlytics