How AI Simplifies Regulatory Compliance for Trading Firms

Compliance with regulations demands the implementation of sound policies, procedures, worker training programs and contingency plans in order to mitigate potential threats to show-stopping risks. Unfortunately, even enterprise-wide controls may sometimes prove insufficient in meeting this goal.

AI can offer substantial benefits to consumers, financial services firms and markets alike; however, its use may also present new or intensify existing challenges. With their respective statutory objectives in mind, the PRA and FCA aim to ensure their AI regulations are proportionate.

1. Automated Compliance

With AI becoming more commonplace among trading firms, compliance must be monitored to ensure they comply with industry regulations, laws, and policies. An accurate risk management system must exist that connects internal controls to regulatory requirements for maximum effectiveness.

The PRA and FCA play an essential role in ensuring financial services markets are properly regulated in order to protect consumers, firms and competition in an equitable and proportionate manner – without acting as barriers against beneficial innovation.

2. Real-time Alerts

Alerts allow companies to quickly identify and correct mistakes before they threaten the bottom line. This helps decrease compliance costs by decreasing errors in their system and reduce risks by enabling traders to quickly react to changes in prices or market events.

This project examines whether stakeholders believe current sectoral legal requirements and guidance to address risks and harms associated with AI are sufficient, where any gaps exist in this regulatory framework, and what other interventions could support safe adoption of AI within financial services in line with their statutory objectives.

Regulators and guidance currently cover three core areas of AI lifecycle: data, models and governance. The Data Protection Officer’s (DP’s) focus lies on potential implications for firms’ ability to effectively manage data-related risks associated with AI as well as model-related risks that may have an effect on capital modelling practices.

3. Streamlined Compliance Processes

Staying abreast of all of the requirements an organization must abide by when employing AI can be a formidable task, particularly since many requirements change frequently due to updates or rules being added from authoritative sources.

Regulatory frameworks are intended to assist companies with managing risks, but can become an impediment to innovation if they become overly restrictive or cumbersome. Furthermore, creating and updating them requires substantial interdisciplinary expertise as well as time.

Furthermore, certain frameworks may be difficult to explain to regulators or consumers due to relying on subtle correlations among thousands of variables that cannot easily be explained or comprehended. As such, companies find it challenging to comply with regulations mandating transparency and accountability of decision-making processes.

4. Increased Efficiency

AI can improve efficiency for financial services firms by automating repetitive manual processes, freeing employees to focus on more valuable tasks like responding to consumer inquiries and analyzing large volumes of data.

AI can enhance customer experience by making it faster and easier for them to find answers or resolve problems, decreasing frustration levels and making customers more likely to return for future transactions.

Artificial intelligence offers many advantages to consumers, firms and the wider economy; however, its implementation could create or intensify existing risks. Supervisory authorities therefore have an interest in understanding how AI may be implemented safely and responsibly within UK financial markets.

5. Reduced False Positives

False positives generated by legacy sanctions screening technologies can be significantly decreased using AI. This is possible as AI can extract hidden context from names and screen them with proven algorithms such as fuzzy matching to significantly decrease false alerts so investigators can focus on those cases most important to them.

Regulatory agencies are currently scrutinizing how firms implement AI, especially around privacy and data protection issues. They’re investigating whether companies must certify that their AI meets specific standards while also being able to explain how they reached their conclusions.

Finally, the Bank and FCA are exploring whether a more precise definition of artificial intelligence (AI) would help create clarity regarding existing legal requirements and guidance applicable to this area and determine whether further regulation may be necessary given domestic and global developments concerning AI.