AI and the Future of Scalable Compliance

Published on: Monday, 12 August, 2024

The fundamentals of artificial intelligence (AI) date back to the mid-20th century, when scientists began conceptualising giant brains that would enable machines to learn and think. In the decades since, bursts of progress interspersed with occasional “AI winters” have now given rise to the emergence of powerful AI tools and applications that are transforming industries across the globe.

At Tenet, to provide premier, engineering-first banking within this rapidly evolving financial landscape, we are ever mindful of how this power can be wielded to improve critical banking functions: and one area of focus for us is compliance.

As banking has grown more global and digital, compliance has become an increasingly important function. It ensures that institutions adhere to a complex set of regulations designed to protect consumers, prevent fraud, and maintain the integrity of the financial system.

Traditional compliance processes are often manual, data-intensive, and repetitive, leading to delays, errors, and increased costs that ultimately undermine a bank’s client service. The ability of AI to improve the accuracy and speed of compliance presents a significant opportunity for forward-thinking banks like Tenet to scale effectively, while keeping focused on continuously engineering in-demand features for evolving client needs.

From processing vast amounts of data from various sources – including client onboarding documents, transaction records, and regulatory requirements – to identifying patterns, assessing risks, and making informed decisions much faster and more accurately than humans (who provide oversight and make final judgements), AI has the capability to revolutionise the way risk management is approached, and even how companies are staffed.

Specifically, AI-related innovations can be leveraged in KYC (Know Your Customer) processes to:

• Incorporate sentiment analysis: Analyse customer interactions across various channels, such as chatbots and customer service calls, to detect potential compliance issues and assess customer satisfaction in real-time
• Streamline compliance reporting: Automatically generate comprehensive compliance reports by aggregating and analysing data from various sources, reducing the time and effort required for manual reporting and ensuring timely submissions to regulatory bodies
• Utilise AI-driven document verification: Automating the verification of documents to ensure authenticity and accuracy, significantly speeding up the onboarding process and reducing human error

In anomaly detection and risk assessment, AI can be used to:

• Monitor transactions in real-time: Flagging suspicious activity to prevent fraud and other financial crimes
• Adapt risk models continuously: Updating risk-assessment models based on emergent data and threats to ensure they remain effective
• Leverage predictive analytics: Anticipating future risks and compliance issues to proactively address potential problems

While AI models are constantly evolving, they have already proven effective in various compliance applications. For instance, graph analytics can visualise network relationships to identify potential money laundering schemes, while Suspicious Activity Report (SAR) narrative-generation can automate the creation of detailed SAR reports, reducing the burden on compliance professionals.

There are, of course, important challenges that need to be addressed for successful implementation of AI-enhanced compliance solutions, including:

• Data quality and bias: AI algorithms are only as good as the data they are trained on. Ensuring data quality and addressing potential biases in the data is crucial for preventing AI models from making discriminatory decisions
• Explainability and transparency: AI models can be complex and difficult to explain. This can make it challenging for compliance professionals, including regulators playing an essential oversight role, to understand how decisions are being made and to trust the AI system
• Regulatory compliance: Financial institutions must meticulously adhere to a complex set of important regulations. As AI becomes increasingly integrated into compliance processes, institutions must ensure that their use of these technologies aligns with the evolving regulatory landscape. This may require additional documentation and approvals from regulators, as well as ongoing monitoring to maintain compliance
• Model development, testing, and optimisation*: Developing and maintaining AI models is a complex and resource-intensive process. Institutions need to have the necessary expertise, resources, and patience to effectively manage and iterate the AI lifecycle

At Tenet, we assure you that AI assists in our processes, but human oversight is paramount. Our compliance team employs AI as a powerful tool, not a decision-maker. Our human experts use AI insights to make informed, final decisions. This human-AI collaboration ensures the highest standards of safety and reliability, giving you peace of mind that your data is handled with care and expertise.

Tenet’s deep understanding of the regulatory landscape, coupled with our expertise in technology development and implementation, positions us uniquely to overcome these challenges and unleash the benefits of AI for the financial world. Ultimately, this is to the advantage of our clients and partners who are pursuing the untold opportunities of today’s tech-driven economy.

Authored by:

Brandon Caruana

Brandon is Tenet's CEO and a member of its Board of Directors. He is an IT leader with nearly two decades' experience planning, developing, and implementing multimillion-dollar projects in the …