Technological advancements are inevitable. From the first stone tool, the discovery of the uses of fire, forging metals, farming, the Industrial Revolution to the information age; we have been consistently inventing tools to make our lives easier.
Artificial Intelligence is one such tool. The term ‘Artificial Intelligence’ was first coined in 1956 by a Dartmouth University professor, John McCarthy. He defined Artificial Intelligence as
“Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to stimulate it. An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.”
Today, 60 years later, AI has subtly found its way into our lives through technology we use everyday.
The next stage of AI will see advancements in Machine Learning. This means machines will learn like humans, through experience. Machines process available data to create algorithms that then help form patterns. Patterns help predict and suggest possible courses of action. All this information is then stored as ‘learnt’ data or experience for future use. More the data, deeper the learning and a more accurate outcome.
The bottom line is, ‘data’ is the foundation for any form of intelligence, including AI and machine learning and including financial regulation.
Financial Regulators make decisions about the health of financial institutions and their impact on the economy through compliance reports and financial market trends over a period of time. The speed and accuracy with which Regulators can sift through mountains of data, enables them to make timely and precise financial decisions. We are witnessing an explosion of data so vast that without the support of automation and artificial intelligence, efficient compliance will be a grave challenge.
The financial world is on the edge of a technological revolution that will enforce AI and constant availability of machine-readable data as the blueprint for sustainable business models to build a long-term supervisory strategy.
Euromoney conducted a global survey called ‘Ghosts in the Machine’ on AI, risk and regulation in financial markets. They interviewed 424 senior executives from financial institutions and FinTech companies and asked them about their views on Artificial Intelligence in financial regulation. They learnt that many executives see AI as a tool that will help improve financial institutions’ risk management through more in-depth assessment of risk in companies and more incisive, comprehensive and informed credit-risk assessment. They also found that AI to be unbiased, prudent and offered an unprecedented depth and breadth of insight, and the ability to acton information and learning from its actions.
The survey also concluded that over the next three years, risk management, credit assessment and regulatory compliance the key areas of focus for application of AI. Financial regulators across the globe have also chimed in about their views of AI in regulation.
Basel Committee of Banking Supervision
BCBS deems that banking standards and supervisory expectations should be adaptive to new innovations, while maintaining appropriate prudential standards. The Committee has identified ten key recommendations on the adoption of AI for efficient supervision.
Securities and Exchange Commission USA
Post Scott Bauguess Chief Economist of SEC’s speech “The Role of Big Data, Machine Learning and AI in Assessing Risks: A Regulatory Perspective” SEC stated that this technology will no doubt make the risk assessment process more efficient and effective, but is not likely to replace human judgment in regulation of financial markets.
Federal Reserve USA
The folks at Federal Reserve commented that machine learning lets the available data speak for itself, potentially revealing important relationships that have not yet been identified by theorists.
Financial Conduct Authority UK
July 2017 – FCA announces that it is looking into possible use of AI and Machine Learning to enforce regulatory compliance. FCA to use “supervised machine-learning” from analytics and “unsupervised AI” to detect financial irregularities.
Australian Securities and Investments Commission ASIC
ASIC have launched a pilot program in partnership with Australian RegTech Association in using cognitive learning tools and application to webpages of accountants to examine potential unlicensed or misleading conduct in relation to self-managed superannuation fund activities.
There is a growing consensus across the globe that regulators will be enabled to maintain a high standard of compliance and prudential standards through effective AI, machine learning and big data solutions. Now is the time for regulatory organizations to proactively plan to migrate from legacy systems to the latest regulation technology and also educate their staff to embrace the power of AI.
Change is the only constant, are you ready?
SQL Power Group Inc., a global application software firm specializing in Financial Supervision technology and Artificial Intelligence – We simplify the process of financial submissions while enabling successful timely intervention by regulatory bodies. Since 1989, through transformative thinking and innovative technology, SQL Power has been changing the way regulatory organizations worldwide, gather, control, mine, consume and report against data.
If your organization could benefit from SQL Power’s advanced, tailored, and cost-effective solution, we’d love to hear from you!
