How AI is Reshaping the Job Market for MBAs in Finance

Finance continues to rank among the most popular concentrations for MBAs, and some of the reasons for that trend relate to strong employment demand, job security, and excellent compensation. However, MBA applicants and students planning on a finance concentration need to consider the impact that artificial intelligence (AI) will have on their expertise.

Hiring within the finance industry is ripe for disruption, as we pointed out in our BSchools guide Which Business Skills are Most Valuable in 2019?

The tech revolution that eliminated many popular jobs in industries like media and publishing hasn’t yet impacted Wall Street. But because of the threat of AI, that situation is about to change.

How is Artificial Intelligence Reshaping the Job Market for MBAs

Most of us assume that artificial intelligence and related technologies like machine learning and robotics will only put low-level, repetitive, manual labor and back-office clerical jobs on the chopping block. But in testimony during December 2019, a professor from Cornell University warned a Congressional committee that as many as one-third of the highest paying jobs in the capital markets, financial services, and insurance sectors face elimination.

In the tense hearing, which took place before the Committee on Financial Services of the U.S. House of Representatives, Dr. Marcos López de Prado of Cornell’s School of Operations Research and Information Engineering delivered to legislators this ominous warning:

Financial machine learning creates a number of challenges for the 6.14 million people employed in the finance and insurance industry, many of whom will lose their jobs—not necessarily because they are replaced by machines, but because they are not trained to work alongside algorithms. The retraining of these workers is an urgent and difficult task.

Dr. López de Prado should know what he’s talking about. He is one of the few business school professors in the world to hold not one, but two doctorates—one in financial economics and a second in mathematical finance. He has more than two decades of experience developing investment strategies assisted by supercomputers and machine learning algorithms, with eight of those years working as a research fellow at the U.S. Department of Energy’s Lawrence Berkeley National Laboratory. What’s more, he managed $13 billion in assets for Guggenheim Partners and wrote a textbook on financial machine learning for graduate students. One account currently ranks him as the world’s most-read author in economics.

Dr. López de Prado testified that starting in 2005, tens of thousands of order execution trading jobs have already been eliminated around the world. Those were the traders who used to be responsible for ensuring that transactions correctly completed on schedule.

But what’s especially concerning about Dr. López de Prado’s testimony for MBAs are his claims that we’re rapidly approaching an era when artificial intelligence will be capable of performing many of the most highly-skilled, expert-level roles on Wall Street. He asserts that many of the functions currently performed by these jobs will soon be managed by programmers instead.

In other words, many of the finance jobs that currently require MBA degrees plus years of industry experience will no longer exist. That’s because, he explained, a whole array of jobs will soon be threatened by technologies that can perform technical functions better than skilled human experts.

Here is an overview of the financial areas undergoing AI’s rapid disruption.

Pricing, Risk Management & Pattern Recognition

These algorithms model and forecast the prices of securities under various conditions of risk and uncertainty. Banks have started to apply machine learning algorithms to price structured products and manage risks because the systems can do these tasks better than traditional approaches to valuation conducted by experts.

Portfolio Construction, Bet Sizing & Asset Allocation

At-risk in this category are some truly plumb jobs. These are some of the best-paying and most sought-after jobs in the entire industry—including expert roles that model, build and maintain investment portfolios.

Nevertheless, Dr. López de Prado has published research demonstrating how, in contrast to investment managers, machine learning algorithms can build better portfolios while avoiding bet sizing behavioral biases. He believes that machine learning algorithms will eventually supplant fallible human discretion, as well as traditional econometric approaches like multiple regression analysis.

Credit Ratings, Scoring & Fraud Detection

Already, bond rating firms routinely use machine learning algorithms to monitor companies’ ability to meet their obligations and to recommend corrective actions once they detect significant changes in the creditworthiness of debt issuers. And banks, credit card firms, and underwriters are calling potentially fraudulent transactions to the attention of customers with the help of machine learning algorithms.

Sentiment Extraction & Recommender Systems

Algorithms can help assess whether individual stocks seem to be the focus of positive or negative press coverage by classifying news reports each day by the tens of thousands. Furthermore, automated “recommenders” suggest stocks that might increase in value due to media attention.

AI: The Mother of All Finance Job Incinerators?

In his prepared remarks, Dr. López de Prado also describes an astonishing and highly disruptive job-killing possibility. To pay homage to Professor Scott Galloway of New York University’s Stern School of Business, this one may well be called the “mother of all finance job incinerators.”

As Dr. López de Prado explains, this arrangement involves the crowdsourcing of financial data analysis through “tournaments” conducted online. At first, it sounds like a creation dreamed up by the author of a science fiction novel:

Financial firms employ tens of thousands of analysts to model financial datasets. This silo approach made sense in the past, because financial data was largely proprietary and datasets were small.

Today, data vendors offer a wide range of datasets that were not available a couple of years ago. As a result, some technology firms have begun to distribute this data and crowdsource the jobs of data analysts through tournaments.

In a tournament, an organizer proposes an investment challenge (e.g., the forecasting of stock prices) and distributes the data needed to solve this challenge to a crowd of data scientists. Because tournament organizers use their knowledge of financial markets to narrowly define the investment problem, tournament participants can work on this problem, even if they lack financial knowledge and they are not employees of financial companies.

The tournament approach has the potential to disrupt some of the highest paying jobs in finance. For example, asset managers could crowdsource their entire research function, by organizing tournaments where millions of data scientists from outside the financial sector participate.

Other Authorities Agree With Dr. López de Prado

Also testifying at the hearings and concurring with Dr. López de Prado was the senior director of the Certified Financial Analyst (CFA) Institute, Rebecca Fender. An MBA alumni of the Darden School of Business at the University of Virginia, Fender testified that a survey of 3,800 CFA Institute members disclosed that 43 percent expect significant changes to their jobs within the next five to ten years. The study revealed that besides traders, performance analyst and sales agent jobs are those most likely to disappear as well.

Interestingly, this Congressional hearing took place only days following a report released by the British research firm IHS Markit that claims that in the banking sector alone, more than a million employees will soon lose their jobs. According to Business Insider:
The report estimates job losses or reassignments will affect 1.3 million bank workers in the US alone by 2030. Specific roles that stand to be disrupted, according to Don Tait, principal analyst at IHS Markit, include customer-service reps, financial managers, and compliance and loan officers.

Clearly, the current trend among experts is to suggest that high-skilled jobs will not escape the effects of artificial intelligence. A November 2019 Brookings Institution study also concluded that employees holding graduate degrees are four times as likely as high school graduates to have their jobs affected or eliminated because of artificial intelligence.

Are Finance MBA Jobs Already Obsolete?

It’s hard to understand how skilled jobs in some traditional MBA sectors, like investment banking, could be entirely performed by artificial intelligence systems. Nonetheless, the challenge for finance MBA students appears to be that—although adoption may seem scattered—the biggest banking employers are already investing heavily in artificial intelligence technology behind the scenes.

A UBS Evidence Lab study of professionals in financial services disclosed that three-quarters of respondents at banks with more than $100 billion in assets under management claim to be implementing artificial intelligence strategies. That’s opposed to only 46 percent of banks managing less than $100 billion. In other words, any MBA employer that’s one of the 36 largest commercial or investment banks in the United States is probably deploying artificial intelligence solutions right now.

The Great Unknown: AI’s Impact on Finance into the Future

It’s important to point out that some experts continue to speculate that the impact of artificial intelligence will be felt the hardest by poor, low-skilled workers.

Kai-Fu Lee, a former executive at Google, Microsoft, and Apple, caused quite a stir when in 2018 he told the audience at an artificial intelligence conference that:

I think AI will exacerbate wealth and inequality… at the very bottom rank are the people, many of whose jobs will be replaced because they’re routine and AI will do their jobs for them, so it’s actually having a doubling effect on giving more wealth to the wealthiest, creating new AI tycoons at the same time taking away from the poorest of society.

Ouch! That’s the outcome that labor leaders, politicians, and even science fiction writers have warned about for more than half a century. When asked about a possible solution, he added:

Well, the brute force solution is redistribution (of wealth). Many of us hate to see that but Bill Gates talked about the robot tax. I think more seriously what he means is a very high tax for very highly profitable companies. Some people talk about universal basic income. I actually think that it’s a very flawed idea but it’s a very good start.

Finally, Dr. López de Prado offers this optimistic closing thought:

But not everything is bad news. Minorities are currently underrepresented in finance. As technical skills become more important than personal connections or privileged upbringing, the wage gap between genders, ethnicities and other classifications should narrow.

The key is to ensure equal access to technical education. In finance, too, math could be “the great equalizer.”