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Gauri Bhat is a globe-trotter. She grew up in India, where she became a chartered accountant and a management (cost) accountant. She was intrigued by academia, but for a while, a Ph.D. in accounting didn’t seem to be in the cards, as doctoral training in accounting wasn’t an established path in India in the ’90s.

After moving to Canada, she discovered the potential of an academic career in accounting research and teaching, which helped her unlock all kinds of possibilities for herself and her students.

Now she’s at the Cox School of Business helping current and future business leaders sharpen their evergreen skills. Although the prevalence of AI across sectors simplifies routine tasks, the decision-making and judgment skills her students develop through studying accounting are increasingly valuable across fields—especially those that require interpreting complex and uncertain information.

You started your career in practice before transitioning into academia. What led you to pursue a Ph.D. after working in audit and corporate banking?

Gauri Bhat: I grew up in India, and my initial professional training was as a chartered accountant and a management (cost) accountant. I worked with KPMG and then Citibank in the corporate banking division in risk administration. While practice taught me to focus on single scenarios and outcomes, I became increasingly curious about the bigger picture. I wanted to understand how those specific decisions and outcomes translated more broadly.

When my personal journey brought me to Canada, I was exposed to academic accounting in a business school environment for the first time. That’s when I saw there was a way to study these things in a very disciplined manner and that a Ph.D. would give me the tools to use data to answer the questions I’d always been interested in.

How does your industry experience inform the research you do today?

GB: I feel strongly that practice and academia move hand in hand—and they ought to for both to be successful. Practice gives you an in-depth view of a particular company. When I was at Citibank, the decisions being made had very real outcomes for the bank. But when you step back and look at thousands of banks across the economy, the average patterns you see are exactly what research captures.

This is even more fascinating in banking, because banks are so interrelated. The health of one bank affects not just that bank but the broader economy. We’ve seen this in history, and we saw it again with the Silicon Valley Bank collapse—panic at one bank affected others. Those ripple effects across the banking system make the connection between practice and research even more critical.

How have your research interests evolved since the beginning of your academic career?

GB: Most of my work has been in banking. Early on, I focused on fair value accounting rules and information: how fair market numbers are measured and how the market perceives them. Over time, I moved more toward the interplay between regulation, incentives and judgment.

What impact do you hope this research will have on industry or policy?

GB: Let me give you examples from my current co-authored working papers. In the current expected credit loss (CECL) paper, we highlight that accounting rule changes have ripple effects—some intended, some unintended. CECL was designed to make loan loss recognition more forward-looking, but our evidence shows it has affected the use of earnings-based metrics in executive compensation.

My other paper, which looks at bank failure during the financial crisis, has direct policy implications. We’re identifying early-warning indicators that distinguish banks that fail from those that can merge when they fall into trouble. Regulators can use these indicators to prevent costly collapses that deplete the deposit insurance fund.

Finally, I have a paper that studies the impact of audit partners on financial reporting. Audit firms have long argued that audit standardization is high and that individual partners within an audit firm do not affect financial reporting differently. Overall, our evidence does confirm the belief of the audit firms, but we also find that individual auditor traits seem to matter during crises or in very small firms.

What skills are today’s business students developing in your classes?

GB: I teach MBA and executive MBA students who come from diverse backgrounds: engineering, architecture, medicine, education and more. None are training to be accountants, but all will use accounting information throughout their careers. I tell them my role is really that of a facilitator: I help them understand both the power and the weaknesses of accounting numbers. And I always spend a few minutes each class talking about research—mine or others’—to help them see that accounting is shaped by evidence and inquiry. Research informs teaching and helps me be a better teacher.

With so much changing in business— AI, data, technology—what skills remain essential?

GB: The methods have changed dramatically since I worked at KPMG and Citibank. Students today work with far more data and increasingly sophisticated tools, but what hasn’t changed is the core requirement in our profession: the need for good judgment. Data can help us process information, but it cannot tell us which questions to ask, how to weigh competing incentives, or when something “looks off” in a way only experience can detect. Good judgment is what allows accountants, auditors and financial managers to interpret evidence, anticipate consequences, balance risk and ultimately make decisions that stand up to real-world complexity. That human element has always been central to accounting—and it is even more indispensable in today’s data-rich environment in the United States.

This is especially valuable in finance and banking. Banks do not produce physical goods; they create and manage risk. That makes them a natural laboratory for understanding the interaction of regulation, human judgment and accounting numbers. Because the banking system is so deeply interconnected, what happens to one bank can have far-reaching macroeconomic implications. The SVB collapse reminded us how quickly a bank run can happen, even today. That complexity is what makes banking research both intellectually challenging and economically significant.