Today, financial institutions are using artificial intelligence (AI) and machine learning (ML) for everything from credit underwriting to fraud detection and anti-money laundering. It seems inevitable, moreover, that disruptive technologies will continue to grow in this space. But how will this affect the employment prospects of aspiring and early-career risk managers?
History suggests technological advances will make some jobs obsolete. While this generally doesn’t destroy jobs for the economy as a whole, it is natural to wonder how the rise of AI and ML will impact the risk management industry.
Cristian deRitis, Deputy Chief Economist, Moody's Analytics
The Current State of AI/ML in Risk Management
Cristian deRitis, Deputy Chief Economist at Moody’s Analytics, says AI/ML is spreading throughout financial institutions. These technologies have been used for years to prevent credit card fraud, and deRitis says they’re now helping a range of departments, from lending and operational risk to human resources and legal.
Why is the use of advanced technologies growing so quickly in financial services? deRitis notes that humans can’t possibly keep up with the speed with which algorithms can sift through massive amounts of data to recognize patterns – both direct and indirect. They can rapidly scrape and absorb information (such as social media posts), looking for developing risks on a minute-by-minute basis.
However, while the pandemic accelerated the adoption of AI/ML at financial institutions, it also revealed why human judgment remains crucial. When there is no precedent for current conditions, algorithms can make deeply flawed predictions by assuming past associations will continue.
For example, models predicted a massive spike in defaults in 2020 due to pandemic-related unemployment. But risk managers immediately recognized this was unlikely, because of government-sponsored support programs for both individuals and businesses. “When relationships break down, the algorithms can give you false signals and false confidence about what’s going to happen in the future,” deRitis explains.
For competitive reasons, risk managers must stay one step ahead of the field, via, for example, developing and using tools that allow for nearly instantaneous risk measurement. But that doesn’t mean you can put risk management on autopilot.
Indeed, the expectation is that risk managers will continue to play an important role in forecasting and scenario analysis. “Humans have a lot of creativity when thinking about what could happen next,” says deRitis. “Even if we don’t get it exactly right, we can create a scenario and project some of the consequences of that scenario.”
As more and more risk functions become partially or completely automated, should risk managers be concerned about significant job losses? Or will the historical pattern of technology increasing net job opportunities repeat itself?
deRitis anticipates creative risk managers will increase their own productivity by incorporating tools like AI and ML into their workflow. “We tend to think about AI and ML taking over the world and making all the decisions. But they’re just tools,” he notes.
Early-career risk professionals may have a slight edge over veterans, deRitis elaborates, because they tend to have greater exposure to AI and ML algorithms. Risk managers who are “aware of algorithms” and the languages in which they’re written, he emphasizes, will stand out from the crowd.
Indeed, people with programming skills and/or a working knowledge of AI/ML should be in high demand. What’s more, since computers struggle with comprehending and counteracting biases in data, deRitis also anticipates gains in jobs for risk “psychologists” who can convert human behavior into something that algorithms can understand.
In short, we’ll just have to wait and see where the technology takes us. But history suggests it will yield exciting new opportunities.
Tod Ginnis is a content specialist at GARP. He is the author of a GARP blog that is aimed at early-career risk managers and professionals aspiring to earn their Financial Risk Manager (FRM) certification.