Established, time-tested methods are the cornerstone of effective compliance programs. According to Saifr, these methods are characterized by adherence to regulatory demands, a commitment to best practices, and a policy framework that enables both operational efficiency and the identification of procedural failures.
For decades, compliance professionals have utilized rigorous oversight processes to monitor and address potential issues. However, the rise of real-time FinTech applications and artificial intelligence is revolutionizing the way compliance functions carry out their oversight duties.
Traditionally, compliance departments have relied on a suite of proven practices to stay updated on regulatory changes and identify potential non-compliance issues. These practices were designed to help firms detect and prevent compliance failures.
Examples of such practices include:
- Compliance training for staff to ensure adherence to regulatory standards.
- Transaction reviews to determine the appropriateness of financial advice given to clients.
- Monitoring employee behavior to prevent regulatory infractions and conflicts of interest.
- Manual checks by compliance teams on marketing materials and public communications.
- Verifying the legitimacy of counterparties and potential business partnerships.
While these measures have historically been effective, the advent of technology in financial services necessitates a reevaluation of how compliance oversight is conducted. Traditional tools, though useful, are limited by their episodic nature—real-time detection is often not feasible with existing methods.
Saifr suggests that artificial intelligence could significantly change how compliance is managed and executed. Advanced AI tools could potentially act as round-the-clock virtual compliance officers, analyzing data in real-time and enabling proactive compliance management with human oversight.
For instance, consider the ethical obligations to assess conflicts arising from external business interests. Traditional reliance on employee self-disclosure limits a firm’s ability to uncover undisclosed conflicts or unauthorized activities. AI intervention could dramatically enhance the firm’s capability to detect such issues.
Additionally, with the introduction of Regulation Best Interest (Reg BI) in 2019, the requirements for overseeing securities recommendations have tightened, particularly with the increasing prevalence of digital investment advice. AI-enhanced oversight could prevent lapses that periodic reviews might overlook.
In areas like anti-money laundering, where episodic screenings might miss violations, AI’s ability to continuously monitor for risks could significantly aid compliance officers, reducing the likelihood of oversight failures and decreasing liability for the firm.
Real-time monitoring and analysis through AI could also mitigate risks faced by compliance officers under SEC scrutiny. AI-driven monitoring allows early detection of compliance issues, helping officers demonstrate proactive management and defend against allegations of negligence.
Moreover, continuous AI support can relieve compliance and risk professionals from routine, less impactful tasks, allowing them to focus on more critical issues.
At a recent “SEC Speaks” event, Richard Best, Director of the SEC’s Division of Examinations, emphasized the need for compliance officers to remain proactive in identifying and mitigating emerging risks, ensuring their programs provide effective guidance and protection.
An AI-driven, real-time compliance oversight program aligns well with the SEC’s expectations, potentially increasing the effectiveness of compliance functions and safeguarding firms from regulatory criticisms and market repercussions.
Source: fintech.global
