FINRA Report: Industry agrees that AI is the ‘holy grail’ of regulatory change management

The US’ Financial Industry Regulatory Authority (FINRA) has published a comprehensive report exploring the use of artificial intelligence (AI) in the Securities Industry. CUBE picks out the highlights.

FINRA Report: Industry agrees that AI is the ‘holy grail’ of regulatory change management

The US’ Financial Industry Regulatory Authority (FINRA) has published a comprehensive report exploring the use of artificial intelligence (AI) in the Securities Industry. CUBE picks out the highlights.

The US’ Financial Industry Regulatory Authority (FINRA) has published a report exploring the use of artificial intelligence (AI) in the Securities Industry. The Report follows a year of “active dialogue” between FINRA’s Office of Financial Innovation (OFI) and the industry.

The comprehensive Report explores the length and breadth of AI – from a general overview of artificial intelligence and common terminology, to a deep-dive into how AI Applications are being used across the securities industry, to regulatory challenges and considerations. In a survey-based report from 2018, 77% of executives at financial institutions agreed that “AI possesses high or very high overall importance to their business” over the next two years.

CUBE has picked out the highlights.

Data is more valuable than oil

The importance of data, it notes, has rapidly increased over the past few years, with data being referenced as “a more valuable resource than oil”, in some instances. This explosion of data – and the ability to collect and analyse both structured and unstructured data – has allowed financial institutions to identify opportunities for revenue generation, as well as cost savings. Undoubtedly, better and more data has been a key contributing factor to the increased exploration and adoption of AI within financial services.

Automating regulatory change management is the ‘holy grail’

As well as contributing significantly to the transformation of investment processes and customer communication, the Report highlights that industry participants confessed to spending “significant time and resources” in developing AI-based applications to enhance their compliance and risk management models. A 2018 report by Chartis Research and IBM, in fact, revealed that 70% of risk and technology professionals were using AI in risk and compliance functions. These functions vary, from surveillance and monitoring to customer identification and financial crime monitoring.

What is of particular interest to CUBE, unsurprisingly, is the Report’s focus on Regulatory Intelligence management – whereby broker-dealers are increasingly using regulatory intelligence to identify, interpret and comply with new and changing rules and regulations across jurisdictions. What has traditionally been a manually process is being overhauled by AI tools to “digitize, review, and interpret new and existing regulatory intelligence.”

The Report notes that industry participants have said that regulatory intelligence management programs, such as CUBE, have the potential to increase overall compliance, while reducing both costs and time spent implementing regulatory change. It adds that “[a]utomating the process of regulatory change management is something of a ‘holy grail’ in the use of AI.”

It’s not human vs computer

FINRA highlights that ideas of a financial industry free from human interaction is a long way off. Instead, it notes that human involvement is “imperative throughout the life cycle of any AI application”. As data is collected and prepared, humans are essential to the process of review – to curate the data so that it is appropriate for the application. Humans are also critical after output, to review for relevancy, accuracy and usefulness. In fact, the Report adds, that the absence of such human review could lead to “irrelevant, incorrect, or inappropriate results from the AI systems, potentially creating […] new risks.”

CUBE comment

The idea that automating regulatory change management is the ‘holy grail’ when it comes to using AI, is not new to us at CUBE.

Regulatory change management has notoriously been a laborious process. Historically, successful systems have required teams of skilled individuals to trawl thousands of regulatory rulebooks for changes, which they subsequently assess for relevance and impact – before applying them to their business. The processes have been long, error prone and used immense resource for administration.

The use of artificial intelligence and automation within the change management sphere has been revolutionary. Companies are finally able to employ smart technology to carry out these protracted manual tasks – freeing up their staff to manage the stuff of real value – applying the rules and remaining compliant with regulations. As AI develops, the value of these products increases tenfold.

The benefits of automating regulatory change are insurmountable – it’s no wonder that 77% of executives at financial institutions agree it’s a high priority for their business.


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