Every industry -- from healthcare to entertainment -- is overlooked by some or another form of regulatory body. In fact, in some key sectors such as finance, multiple regulators control different aspects of the sector. For instance, just in the US, there are at least ten different financial regulators such as the Securities and Exchange Commission, The Federal Reserve, and the Consumer Financial Protection Bureau, among others. Each of these regulatory agencies has hundreds of regulations that apply to different entities to ensure the fairness and stability of the economic system as well as to protect the interests of the common people. It is these agencies’ duty to ensure that:
- the economy grows in a balanced manner,
- people trust the economic system,
- businesses compete fairly, and
- Consumers (or the general public) are not exploited.
To uphold these conditions in the face of rapid change driven primarily by technological evolution, the regulators are passing new regulations or modifying existing ones almost every day. This does not only complicate the enforcement process for the regulators but also makes things hard to track for the entities that need to comply with these regulations. And such problems have led organizations to explore the application of technologies like analytics and AI in regulatory compliance to ease the burden on all the stakeholders involved. And the need for regulatory technology is only set to increase in the future.
The growing need for regulatory technology
Regulatory technology, referred to simply as Regtech, is an emerging application area of digital technology that aims at making regulatory compliance easier and, eventually, even automatic. Regulatory bodies across the world are faced with the numerous challenges of monitoring the events in the industry they are overseeing to ensure balance with the help of laws and rules. And the entities that come under the jurisdiction of these regulators have the obligation to keep track of the changing regulations and keeping their practices in alignment with those rules. A failure to comply may lead to the businesses subjected to financial penalization, disrepute, and in extreme cases, criminal litigation and imprisonment.
The challenge for the regulated is keeping track of the myriad regulations laid out by the different agencies overlooking their areas of operation (both geographical and functional) and making changes to their internal processes and practices. They are also required to document their processes to report them to the authorities either periodically or on demand. Keeping track of frequently changing regulations and changing their internal operations and reporting procedures can be hard for businesses who often end up paying end paying considerably for handling these processes. And the cost of compliance only keeps increasing for these businesses.
Regulators have the obligation to monitor all the entities that fall under their jurisdiction to ensure that their regulations are followed and there is no exploitation of customers as well as businesses. They must, as often as they can, verify the compliance of these entities either by checking their documentation or their processes. If they find any discrepancies or deliberate fraud attempts, they must take legal action against the defaulters. However, constantly monitoring an ever-growing number of businesses and individuals under their regulatory purview and effectively ensuring compliance can be too much as it requires the scrutiny of several parameters associated with each entity. This can be especially hard considering the fact that these regulators have limited resources, both in terms of people and funds.
The use of regulation technology like AI in regulatory compliance can help both the regulators and the regulated to play their part in maintaining compliance.
The role of AI in regulatory compliance
AI’s ability to process large volumes of data with speed and accuracy can potentially transform regulatory compliance. In the short term, the technology can be used to assist business leaders to understand compliance requirements easily and take apposite action. Eventually, the continued use of AI in regulatory compliance can eliminate the need for humans in the process altogether.
Simplifying regulatory compliance for business leaders
Regulations are usually created and shared in the form of large documents with pages on pages of text that must be read thoroughly to take compliant actions. However, compliance officers and other business leaders who might have a role in ensuring compliance may not have the time to go through the entire documentation and keep track of the changes in them. They might have to spend valuable hours on reading regulatory documentation to infer the actions that must be taken to maintain compliance.
To help in such situations, AI applications that can read and interpret compliance documents to deliver actionable insights to compliance leaders are being developed and used by leading corporations. Such applications can condense lengthy and complicated compliance documentation into a short, easily readable format consisting of just the most pertinent and critical portions of the document. Thus, compliance officers can get actionable insights without having to spend hours of time as well as effort trying to figure out what to make of compliance requirements. They can initiate effective action quickly and ensure that their operations keep up with all emerging compliance requirements.
Notifying stakeholders of regulatory changes
AI applications can even help businesses in maintaining compliance by constantly checking sources of compliance rules and notifying leaders about any changes in regulations. These systems can use deep learning and natural language processing to read compliance requirements from the websites of regulators and notify businesses of any changes in regulations. This can ensure that businesses stay on top of evolving regulatory requirements and align their processes and reporting procedures with them.
The use of the semantic web, which involves structuring all the data on the internet to make it machine-readable, can help regulators to communicate regulatory changes to organizations in a more effective way. Since changes are in a machine-readable format, they can be read by the AI-driven tools used by organizations.
Monitoring adherence to regulations
Technologies like analytics, machine learning, and deep learning can also enable regulators to monitor entities to ensure compliance. Instead of performing periodic audits, which can be time-consuming and hasslesome for the personnel involved, these agencies can constantly monitor the parameters of businesses that indicate compliance with regulations. The businesses themselves can also gain access to such information to take preventive actions if their processes shift towards non-compliance.
Such systems can also alert authorities about non-compliance immediately and record the necessary evidence indicating the same. This can help in taking legal action against non-compliant parties and even act as a deterrent for potential fraudsters, thus gradually minimizing the occurrence of non-compliance.
Regulations and the need for compliance, although vital for economic and social systems, must not be the central point of focus for businesses as they are currently turning out to be. Thus, while the burden of compliance will increase in the coming future, the use of AI in regulatory compliance will come as a welcome respite for the businesses.
