Don’t get me wrong. I have nothing against AI. But its use requires considerable thought, not just in initial application, but in oversight too. It’s not yet the magic answer we might have hoped for. This is especially so in the financial services industry, where the demands of regulatory compliance are not just complex and onerous, they’re non-negotiable and sometimes nuanced. Ensuring compliance is crucial; it safeguards businesses and their customers against financial crime, avoids regulatory penalties, and preserves reputational integrity. For banks, for example, this means navigating labyrinthine rules and regulations on a daily basis.
The Compliance Maze: Human Oversight Meets Automation
The primary tasks required for compliance require an integrated approach to regulation and risk. Thus, Know Your Customer and Customer Due Diligence lead to a variety of checks including AML, CTF and sanctions lists. Add to this the variations in regulation across jurisdictions, and the scale of the task is clear. The scope of these requirements, and the workload involved, necessitate an approach that blends human oversight with automation.
This is where AI enters the conversation. Potentially. Contemporary artificial intelligences are powerful, capable of processing vast amounts of data and executing complex tasks efficiently. However, AI is task-driven and it does not think. It lacks certain human capabilities such as leaps of logic, intuition, and the ability to connect seemingly unrelated events. For compliance, these gaps are significant because understanding context and subtleties is often as important as processing the data.
This is not to undermine AI’s potential. Yet it comes with vulnerabilities. Even for the specialist models that might be used in this context, think potential biases, a tendency to make random errors, and a lust for the huge quantities of data that enable continued “learning”. Despite appearances, AI are still expensive machines in development.
Balancing Tech and Human Judgment in KYC
Another facet of this complexity is the ongoing KYC debate between scheduled KYC reviews and Perpetual KYC (pKYC) which further highlights the need for nuance. While regular KYC reviews involve set intervals for re-running checks, pKYC opts for a continuous, real-time approach. Each has its merits and challenges, particularly in data management and operational consistency. Much depends on context, and for that human judgement is still indispensable.
In fact, what stands out as essential is this: the need for comprehensive services that not only function consistently well but are also flexible, effective, and easily used. The holy grail of compliance is not about seemingly magic solutions. It is in systems and services that provide the whole range of processes to enable humans to make genuinely informed choices. This ranges from automated transaction monitoring, with activities compared against a range of behavioural patterns, to overcoming the blind spots created by data silos – and much more in between.
Pioneering Excellence in Regulatory Compliance
In step solutions like Compli from Essiell Compli, a beacon of proficiency in this intricate landscape. Designed to navigate the pathways of regulatory compliance, Compli offers a balanced blend of technological sophistication and user-friendly operation. A wide range of characteristics make this a customizable, scalable and powerful solution – including its “global person” concept, which calls upon multiple databases to create customer profiles of granular accuracy.
The role of AI in compliance will undoubtedly expand. However, the focus should remain on solutions that holistically address the industry’s needs today and tomorrow, which AI cannot yet do. The need is for services that are practical, reliable, efficient, and adaptable. AI can be powerful but it’s not yet the answer – and it’s unlikely to be so anytime soon. In the meantime, it’s comprehensive services like Compli that are the future of genuinely effective compliance.
By Declan Morton, staff writer at Essiell Compli.