By: Shira Rottner, Business Development Manager, Shield FC
Artificial Intelligence (AI) is carving out a growing niche in regulatory compliance because AI and Machine Learning (ML) applications address common challenges and systematic issues that compliance officers face every day. Enterprise software applications that integrate AI can increase the efficiency and effectiveness of regulatory compliance programs across a variety of industries. While the potential benefits of technological breakthroughs in AI and ML are endless, current applications of AI in compliance systems have already demonstrated at least three clear benefits for regulatory compliance officers: reducing false positives, lowering costs, and addressing human error.
1. Reducing false positives
Large banks are experiencing false positives in their compliance systems at alarmingly high rates. Compliance alert systems based on standard technologies are triggering hundreds – if not thousands – of false positives every day. More often than not, each of these false alarms must be reviewed by a human compliance officer, which invites opportunities for inefficiency and human error.
By using AI and ML to capture, analyse, and filter dozens of data elements, sophisticated enterprise technology solutions can address the problem of false positives that waste banks’ time and money every day. For example, ML solutions can improve the way compliance officers manage workflow. By autonomously categorizing compliance-related activities and alerting them to important updates, events, and activities. Because these technologies are built to learn from compliance officers’ own data, AI and ML applications can streamline compliance alert systems to near-perfection. In this way, AI technology can improve the efficiency of compliance operations and reduce costs in today’s data-driven compliance environment.
2. Lowering costs
Modern financial institutions are being forced to adapt to regulatory requirements that revolve around the management and analysis of big data. Regtech software developers are using AI and ML applications to increase the efficiency and lower the costs of compliance by automating processes that previously required onerous manual work.
Artificial Intelligence, particularly when it’s partnered with Machine Learning, can automate workflow. This means less time and human capital are necessary to support compliance operations. This, taken together with the accuracy gains possible through the effective integration of AI and ML technology, can save financial institutions millions in annual compliance costs industry-wide.
3. Addressing human error
Whether attributable to poor due diligence, outdated technology, or ineffective processes, human error costs regulated industries billions every year. Financial regulations passed following the global financial recession require compliance officers to track, manage, and analyse detailed data about transactions, customers, and operational activities at large banks. The sheer volume of this information raises several opportunities for confusion that can easily give rise to human error. And with regulatory compliance growing more technology-driven by the day, AL and ML applications can be invaluable in mitigating the impacts of human error.
Just like using a calculator to check manual computations, AI and ML technologies can shed light on blind spots, reasonable errors, and other things that humans may not necessarily pick up on. Further, good AI and ML programs can spot trends and patterns, which is particularly helpful for financial intuitions looking to access savvy millennial and gen-z customers.
Successfully implementing AI and ML technology requires skill and realistic expectations
Artificial Intelligence and Machine Learning technologies are incredibly powerful, but expectations must not exceed reality. A substantial investment of time and resources may be necessary in order for firms to implement AI and ML into their existing regulatory compliance processes. For example, since AI and ML work based on analysis of sufficient quantities of relevant data, regulated companies should expect for it to take some time for the software to collect sufficient historical information to learn effectively. Further, this cutting-edge technology is so new that few possess the expertise necessary to install and manage AI and ML driven systems effectively.
AI and ML systems are complex and sophisticated, and some firms may struggle to develop the infrastructure, systems, data, and human capital necessary to create effective regulatory compliance programs with tailored AI and ML software solutions. However, once these systems are off the ground, they only continue to make themselves faster, stronger, and better with technology that autonomously improves itself with every piece of data it processes.
Investing in AI and ML now will only have compounding benefits for the future. In the highly-competitive world of global finance and regulated industries, any technology that can increase the accuracy and efficiency of compliance systems is a wise investment. This is true not only because better compliance systems help firms avoid costly fines and audits, but also because the nature of this technology gives early implementers a massive competitive edge. At the end of the day, regulated companies that implement AI and ML solutions swiftly and effectively will be the ones to reap the benefits of this self-learning technology.
Regulatory compliance is growing more challenging by the day. While no technology offers a cure-all solution to every potential challenge facing today’s compliance officers, well-implemented AI and ML solutions can improve compliance systems substantially. And with fines for noncompliance increasing year over year, any technology that can reduce false positives, reduce costs, and address human error offers a valuable addition to regulatory compliance programs. The first companies that are able to effectively harness AI and ML solutions will be the first to see meaningful reductions in the cost and complexity of their compliance programs – a critical leg-up in today’s competitive financial services markets.
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