By Benjamin Perlman, Part-Time Lecturer in the Enterprise Risk Management (ERM) Program, School of Professional Studies
I am fortunate to practice enterprise risk management (ERM) in two complementary arenas: the professional world and the academic classroom. As managing director and head of ERM at ORIX, I am responsible for overseeing a broad spectrum of financial and non‑financial risks across the organization. This role aligns seamlessly with my position as a lecturer in what I consider to be the premier ERM program in the country. The interplay between these two roles — one grounded in real‑world application and the other in academic exploration — creates a dynamic feedback loop that enhances both my teaching and my day‑to‑day responsibilities.
One of my central responsibilities at ORIX is to function, in effect, as the organization’s chief economist. This responsibility arises in part from the requirements of the CECL (current expected credit losses) accounting standard. CECL mandates that organizations maintain a forward‑looking, lifetime loss estimate for their portfolios. To do this effectively, companies must adopt a single, consistent set of economic assumptions — interest rate paths, unemployment expectations, GDP trajectories, and other macroeconomic variables — that flow through finance, accounting, credit risk, stress testing, and asset‑liability management. CECL essentially prevents organizations from “talking out of both sides of their mouths” by forcing alignment across teams that historically may have operated with different assumptions when convenient. Someone must own this unified economic perspective, and a “head of ERM” is uniquely positioned to take on that responsibility.
In my “chief economist” capacity, I publish a quarterly letter titled “The State of Risk.” This document begins with a broad economic overview — rates, spreads, and market conditions — before gradually narrowing its focus to metrics more directly tied to my portfolio. These include segment‑specific spreads, sector‑specific cap rates, and other indicators that help translate macroeconomic movements into portfolio‑level implications. The letter ultimately evolves into a direct assessment of the financial and non‑financial risks facing the organization, providing a structured narrative that connects the global economic environment to the realities of our balance sheet.
This analytical work directly informs my teaching, particularly in the Value‑Based ERM and capstone courses. In both classes, students develop scenarios that require them to think critically about economic shocks and their downstream effects. The economic analysis I conduct at ORIX enhances my ability to guide students in designing these scenarios, especially when conceptualizing a “credible worst‑case” scenario. We explore shocks such as oil price spikes, shifts in monetary policy, inflation dynamics, and unemployment trends. When interest rates or credit spreads widen, students must incorporate the resulting increase in financing costs into their models, particularly as debt matures within their subject companies. This exercise helps them understand how macroeconomic forces cascade into operational and financial pressures.
In one memorable class session, a group of students made a particularly insightful observation. They argued that the historical shocks we often use in scenario design tend to last longer than modern market dislocations. Their claim was initially anecdotal, but they supported it with compelling evidence suggesting a regime shift in market behavior. They compared the Russia-Ukraine conflict in 2022 with the “Liberation Day” tariff package dislocation in 2025. In the former case, equity markets such as the S&P 500 fell sharply and took nearly two years to recover to pre‑shock levels. In contrast, following Liberation Day, markets rebounded within a single month. The speed of recovery was dramatically different.
Intrigued by this observation, I carried the question back into my day job, where my focus is more on private credit than public equities. I examined whether this pattern of faster recovery held in spread markets as well. Spoiler alert: it did. The discount margin (DM) of the S&P/LSTA Leveraged Loan Index — a widely used proxy for credit spreads — took roughly three years to normalize after the 2022 shock. Yet following Liberation Day, spreads returned to normal levels within just a couple of weeks. While the comparison is imperfect — akin to comparing apples to bowling balls, given the difference between a geopolitical conflict and a unilateral policy announcement — the broader point remains. Across multiple examples, including the Israel-Iran conflict and President Trump’s threatening the independence of the Federal Reserve, markets appear to recover more quickly today than they did historically.
This interplay between my professional and academic roles is mutually reinforcing. My hands‑on experience as ORIX’s “chief economist” strengthens my ability to help students develop rigorous, realistic scenarios. Conversely, the insights and questions that emerge in the classroom often prompt me to re‑examine assumptions and stress‑testing approaches in my day‑to‑day work. In this way, teaching and practice continually inform and elevate one another.
Views and opinions expressed here are those of the authors, and do not necessarily reflect the official position of Columbia University School of Professional Studies or Columbia University.
About the Program
The Master of Science in Enterprise Risk Management (ERM) program at Columbia University prepares graduates to inform better risk-reward decisions by providing a complete, robust, and integrated picture of both upside and downside volatility across an entire enterprise. For both the full-time and part-time options, students may take all their courses on Columbia’s New York City campus or choose the synchronous online class experience.
Learn more about the program here.
