The financial industry is facing increased regulatory scrutiny on the use of Artificial Intelligence (AI) and Machine Learning (ML) in regulatory compliance, particularly in the area of regulatory change management (RCM). Integrating these technologies is no longer just a competitive advantage but an expectation as regulators raise the bar on accuracy, efficiency, and transparency.
Guidelines and Standards for Regulatory Change Management
Regulators are issuing guidelines that emphasize transparency, accountability, and risk mitigation when using AI and ML in regulatory processes. For example, the EU AI Act mandates strict oversight of AI models in financial services, ensuring compliance with transparency, safety, and ethical standards. In regulatory change management, AI must meet these standards by enabling financial institutions (FIs) to trace decisions, log interpretations, and explain outcomes.
Penalties for non-compliance can be steep. For instance, regulatory fines imposed by the Financial Conduct Authority (FCA) in the UK for inadequate governance and oversight over compliance models demonstrate that institutions must not only capture regulatory updates but also ensure those updates are integrated properly across internal processes.
The Evolution of Regulatory Change Management in Financial Institutions
Historically, financial institutions have relied on spreadsheets and manual workflows to track regulatory updates. However, this method is becoming obsolete as regulators expect more sophisticated systems that capture, analyse, and integrate regulatory changes in real-time. Financial institutions are moving toward adopting automated solutions that perform regulatory change impact assessments, which allow them to:
- Assess regulatory changes against existing compliance controls and frameworks.
- Track actions taken, including documentation of decisions on what rules apply and what don’t.
- Implement a structured process to demonstrate how regulatory updates affect internal policies, procedures, and controls.
Such systems enable a full audit trail of how changes are managed, reviewed, and applied, meeting regulatory requirements for transparency and accountability.
Ensuring Comprehensive Regulatory Impact Assessments
For financial institutions to meet regulatory requirements, their regulatory change impact assessments must:
- Engage all necessary stakeholders, including compliance, risk, legal, and business units.
- Integrate policy, procedures, and controls data, ensuring that every impacted area is thoroughly examined.
- Perform gap analysis to identify discrepancies between current practices and new regulatory obligations.
FinregE’s AI-driven platform is uniquely positioned to assist firms in automating these processes, ensuring that all relevant data points are captured, and stakeholders are involved in real-time decisions.
Adapting Regulatory Change Frameworks to Meet Evolving Expectations
To ensure compliance while maintaining business-as-usual (BAU) activities, financial institutions must:
- Enhance collaboration across departments by centralizing the regulatory change management process.
- Implement real-time monitoring and automated workflows that track compliance activities, deadlines, and tasks assigned to various teams.
- Utilize AI-powered impact assessments to accurately analyse and document the implications of regulatory updates on internal controls.
Adapting to these expectations requires institutions to move away from siloed, manual processes toward integrated, automated solutions that enhance oversight and traceability.
How FinregE Supports Regulatory Change Management
FinregE provides FIs with a fully integrated platform that automates the entire regulatory change process:
Regulatory Horizon Scanning: FinregE’s platform monitors real-time updates from regulatory bodies, ensuring that institutions receive immediate notifications of changes.
AI-driven analysis: FinregE’s Regulatory Insights Generator (RIG) uses machine learning to interpret regulatory texts, automatically identifying obligations and mapping them to internal controls.
Impact Assessments and Workflows: The platform offers comprehensive impact assessments, assigning tasks and managing workflows to ensure that all necessary actions are tracked and completed.
By leveraging AI and automation, FinregE ensures that financial institutions not only meet current regulatory expectations but also remain agile and responsive to future regulatory changes, reducing the risk of fines and enhancing operational efficiency.
In conclusion, regulatory expectations around integrating AI and ML into regulatory change management are evolving rapidly. Financial institutions must adopt advanced technology solutions like FinregE to stay compliant, reduce costs, and proactively manage regulatory risks. Book a demo today.
