The next big financial fraud may eclipse the recent collapse of cryptocurrency exchange FTX, which at last count had liabilities estimated at $8 billion. “You’re going to have larger frauds, and there might be more frauds,” Wharton accounting professor Daniel Taylor said during a panel discussion titled “The Analytics of Finance” held earlier this month. Stricter regulatory checks and audits may have averted the FTX scandal, he added, noting that it was the outcome of weak internal controls.
In the future, if regulators fail to embrace analytics as aggressively as sophisticated fraudsters do, “the frauds will get bigger, persist for longer, and be more devastating,” Taylor said. According to him, the largest frauds occur due to complexity, and the financial markets are getting increasingly complex.
This year’s three-part Beyond Business series “shines a light on how analytics, artificial intelligence, and machine learning are providing viable pathways for solutions in every domain,” said Wharton Dean Erika James. She led the discussion with Wharton finance professor Michael Roberts and Taylor, who is also director of the Wharton Forensic Analytics Lab.
Investing in technologies such as analytics is one of the surest ways to combat financial crimes, Roberts said. He noted that compared to the Securities and Exchange Commission’s 2022 budget of $2.7 billion, JP Morgan alone spends $12 billion annually on technology, and the entire financial sector may have a combined annual outlay of $100 billion. “The only hope, since [regulators] can’t compete on scale, is efficiency. And that means embracing data and analytics to try and ferret out any potential wrongdoing,” he said.
Taylor noted that as financial crimes are becoming increasingly sophisticated and difficult to detect, regulators are recognizing the power of analytics and “are starting to tool up.” Awareness is also filtering into education, with law schools including classes in data and quantitative analysis, he added.
Growth and New Efficiencies
For sure, regulators have used analytics to good effect in many settings. James pointed out that the public gets to hear of financial scandals that have reached a certain stage. “I would imagine there’s a ballast on the other side of that, with all of the [financial crimes] that [regulators] have been able to prevent,” she said.
The use of analytics in finance has also brought other gains, such as growth and new efficiencies to markets, and expanded household access to financial products, thereby leveling the playing field for them in many ways.
Analytics has “a critical and growing role” beyond its traditional domain of capital markets. “On Main Street, we see more effective capital budgeting because of data integration and exploitation via data science initiatives,” said Roberts. “Among households, we’re seeing improvements in budgeting, retirement savings, asset allocation, and credit usage, due largely to the democratization of data and technological innovation from fintech.”
Within the capital markets, analytics is finding new uses such as machine learning to develop predictive business models in valuations of businesses, Roberts said. Of late, data and predictive models are being used for due diligence in mergers and acquisitions, buyouts, and capital-raising activities, he added. He noted that practitioners are already seeing “impressive results” in terms of improved predictive accuracy and increased benefits to shareholders and other claim holders at firms.
According to Taylor, analytics could also help track corporate citizenry and adherence to ESG values. “Analytics with satellite monitoring could help distill greenwashing versus what’s called ‘true ESG’ or ‘true green’ investments,” while technologies such as infrared imaging could track and verify carbon emissions at specific units, he noted. “Those will help investors more efficiently allocate their capital to corporations who embrace their values.”
Depending on how analytics is used in finance, it could bring either good or bad outcomes. “We need to think about data and analytics as investments,” Roberts said in response to James’s question about whether it could create “a new class of haves and have-nots.” He pointed out that first movers have to be incentivized to take on the attendant investment risks. “But over time, competition will erode those returns and we’ll see a diffusion of technology and knowledge to the broader population — something we’re already seeing with inexpensive and widely available robo-advisors and electronic payment systems,” he added.
“If humans have been replaced by algorithms, you conceptually could imagine a world in which the algorithms don’t have those human biases that are detrimental to prices or to market efficiency,” said Taylor. But some algorithms focused on correlations between two stocks or between various indices are vulnerable to occurrences outside their programming, which could create “large distortions, suddenly, in markets,” he added. “[With analytics] we’ve removed some of the human biases from prices, but we may have introduced other biases. It’s an open question — which we might prefer, and which is better for society.”
Challenges and Opportunities Ahead
Looking ahead five or 10 years, Roberts identified the goalposts for analytics. The top challenge for analytics is around data ownership, where people have control over their personal data. On the other hand, analytics will bring “cutting edge, customized financial planning to households at a negligible cost” to help them make more efficient decisions. Businesses, including those in the small and medium sectors, will also find expanding uses for analytics in areas like capital budgeting processes and resource allocation.
In an evolving field such as analytics, it’s critical to distinguish between technological failures and human failures, Roberts said. “First, better-informed participants that don’t blindly rely on technology, data, and analytics, will make a big difference. There has to be personal agency, because it’s going to help discipline behavior and ensure robustness. Second, markets themselves must install and enforce trip wires and guard rails that can handle the new technological reality.”
Finding the right approaches to avoid inequities will be an ongoing challenge. For instance, high-frequency traders such as hedge funds with sophisticated models might gain an advantage over retail investors, Taylor said. Alternatively, analytics is often used “to democratize finance and help spur retail investor participation,” he added. “You’re going to see that sort itself out based on those that can make profits from analytics by adopting it — and those that potentially can’t, not doing so.”
