Harnessing the promise of AI for real-time compliance management


Time-tested, established methods form the backbone of effective compliance programmes.

According to Saifr, such methods are characterised by adherence to regulatory demands, commitment to best practices, and a policy framework that enables both operational efficiency and the identification of procedural failures.

For decades, compliance professionals have employed rigorous oversight processes to monitor and address potential issues. However, the emergence of real-time FinTech applications and artificial intelligence is transforming the way compliance functions perform their oversight duties.

Traditionally, compliance departments have relied on a suite of proven practices to stay updated on regulatory changes and pinpoint potential non-compliance issues. These practices aimed to aid firms in detecting and preventing compliance failures.

Examples of this include compliance training for staff to ensure adherence to regulatory standards, transaction reviews to ascertain the appropriateness of financial advice given to clients and monitoring of employee behaviour to prevent regulatory infractions and conflicts of interest.

Other examples include manual checks by compliance teams on marketing materials and public communications and verifying the legitimacy of counterparties and potential business partnerships.

While these measures were effective historically, the advent of technology in financial services necessitates a reevaluation of how compliance oversight is conducted. The traditional tools, although useful, are limited by their episodic nature—real-time detection is often not feasible with existing methods.

Saifr added that artificial intelligence could significantly change how compliance is managed and executed. Sophisticated AI tools could potentially function as around-the-clock virtual compliance officers, analysing data in real time and facilitating proactive compliance management with human oversight.

For instance, consider the ethical obligations to assess conflicts arising from external business interests. The traditional reliance on employee self-disclosure limits a firm’s ability to uncover undisclosed conflicts or unauthorised activities. AI intervention could dramatically improve the firm’s capability to detect such issues.

Furthermore, with the introduction of Reg BI in 2019, the requirements for overseeing securities recommendations have tightened, particularly with digital investment advice becoming more prevalent. AI-enhanced oversight could prevent lapses that periodic reviews might overlook.

In scenarios like anti-money laundering, where episodic screenings could 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 the risks faced by compliance officers under SEC scrutiny. AI-driven monitoring allows early detection of compliance issues, helping officers demonstrate proactive management and defence against allegations of negligence.

Moreover, continuous AI support can relieve compliance and risk professionals from routine, less impactful tasks, enabling them to concentrate on more critical issues.

At a recent “SEC Speaks” event, Richard Best, Director of the SEC’s Division of Examinations, emphasised the need for compliance officers to remain proactive in identifying and mitigating emerging risks, ensuring their programmes provide effective guidance and protection.

An AI-driven real-time compliance oversight programme aligns well with the SEC’s expectations, potentially increasing the effectiveness of compliance functions and safeguarding firms from regulatory criticisms and market repercussions.

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