The next big thing in regtech

  • By Christine St Anne

Regulation has traditionally been approached from the position of hindsight, but regulators are starting to eye technology that allows them to gauge emerging risks 

It is an assessment made by EY principal and financial services regulator leader Eugène Goyne . He was one of the lead authors in the global consultant’s Bank Regulatory Outlook report. 

“We are not in the world of Minority Report,” he said, referring to the critically acclaimed action blockbuster about a futuristic world where law enforcement can nab criminals before they have actually committed the crime. 

“We do have to be realistic about the value of what predictive risk indicators. But regulation has traditionally been a game of hindsight. Now in 2020, regulators are starting to think about what value they can get from predictive data.” 

While financial services regulators are not yet at the point of deploying predictive analytical suptech applications, Goyne said they are now interested in their potential applications. 

This might include identifying possible areas of heightened prudential or systemic risk, for example in terms of credit exposures or misaligned asset prices. 

“Another potential application could be in the identification of conduct issues, such as patterns of relationships that may be predictors of a higher risk of inappropriate market or corporate behaviour,” Goyne added.  

“Over the next few years, we expect to see further interest from regulators in the use of these types of data analytics as they seek to manage evolving prudential, systemic and conduct risks.” 

Professor of Disruptive Innovation Ross Buckley alluded to this trend at a RegTech Association event last year. 

The academic who also works at KPMG Law and King and Wood Malleson could see a day where a regulator could dial into a CEO and says we have a problem we have identified, and you need to fix it before the world crashes.

As technologies have impacted the end customer, they have attracted more scrutiny, particularly in the areas of bias and discrimination

He also paraphrased Bank of England’s chief economist Andy Haldane whose dream is not “futuristic but realistic and involves a Star Trek chair and bank monitors”.

This would allow Haldane to assess emerging risks across the region through the application of technology.

Outside of predictive analytics, the E&Y report also assessed trends in emerging technology with artificial intelligence and machine learning now hot button issues in global banking. 

While AI and ML have been used – predominately this technology has been applied to low-risk automation. The report found that AI and ML is now increasingly being used in decision making such as risk management and product pricing. 

“As technologies have impacted the end customer, they have attracted more scrutiny, particularly in the areas of bias and discrimination,” Goyne said.

Currently there are is no specific regulatory framework developed. 

The EY report noted that regulators can point to existing guidance and risk management frameworks, but the public scrutiny of AI and ML may encourage them to provide new or enhanced guidelines. 

“The absence of specific rules in most jurisdictions is partly driven by the desire of regulators to avoid stifling innovation, and to retain a technology-neutral approach to their rule-making. 

“At the same time, they are more closely evaluating the risks underlying these applications, using the supervisory process to assess their risk profile and identify any concerns.” 

Regulators such as the Monetary Authority of Singapore and Hong Kong Monetary Authority are also moving to implement guidelines to address AI risks such as discrimination.  

For example, the Fairness, Ethics, Accountability and Transparency (FEAT) guidelines have been developed in the use of AI and data analytics, and most recently by the Hong Kong Monetary Authority.