Behavior & Risk

In this episode, we compare shareholder-oriented and stakeholder-oriented organizations, defining shareholder primacy as maximizing profits, share price, and dividends (e.g., GE under Jack Welch, ExxonMobil) and contrasting it with stakeholder models that balance employees, customers, communities, and the environment for long-term value (e.g., Unilever under Paul Polman, Patagonia), shaped by differing legal and cultural frameworks such as Delaware corporate law, Germany’s co-determination, and EU sustainability directives. We argue the “stakeholder good, shareholder bad” framing is oversimplified, explore how agency problems between owners and management affect decisions, and note stakeholder can mean many different constituencies. The discussion highlights time-horizon bias and short-term earnings pressure in shareholder models, impacts on R&D and innovation, and how activist investors and private equity influence governance, risk custody, and the need for clear risk messaging and metrics.

The episode examines the “iron law of midterms.” Since World War II the party holding the White House has lost ground in Congress in 18 of 20 midterm elections. We discuss early 2026 signals such as presidential approval in the high thirties, cool independent voters, and models suggesting a potential House shift. We explore behavioral explanations beyond topline numbers, focusing on turnout changes between presidential and midterm electorates, salience and recency effects, retrospective voting in the US, and how loss aversion can overwhelm uncertainty aversion to drive anti-incumbent swings. We contrast US two-party choice complexity with Europe’s more prospective voting, discuss perceived equivalence between president and party, and consider why presidential incumbency can remain strong even as House seats flip. We also debate conflicting forecasts, predictive markets, polling errors, gerrymandering, and shifting party coalitions as factors that could alter the usual pattern in 2026.

In this episode, we explore why nonprofits and charities, while generally beneficial, are uniquely susceptible to malfeasance due to a regulatory hodgepodge, donor identity attachment, and management incentives. We explore how donations often involve reciprocity in the form of internal rewards (wellbeing, moral elevation, guilt reduction) tied to self-concept, which can be exploited and can sustain giving even after documented scandals (e.g., United Way). We contrast rogue individuals in otherwise good organizations with inherently fraudulent charities and note how ethics can gradually slip. Key risk domains include inconsistent 501(c)(3) oversight with audit-avoidance thresholds, fundraising and donor concentration risks, seasonal revenue forecasting risk,reliance on “vibes” and branding, operational risks (fraud, data breaches, litigation, compliance), volatile volunteer dependence, reputational fragility, and “boiled frog” cultures of small lapses escalating. We conclude: avoid over-identifying with charities, don’t run them like for-profits, and don’t do due diligence by vibes.

The episode argues that the opioid crisis was not a failed risk calculation but a knowingly scaled, dangerous product driven by “profit first” incentives, echoing a broader cultural shift. It focuses on Purdue Pharma and the Sackler family, who had internal data undermining claims that OxyContin was less addictive yet aggressively marketed it, influenced guidelines, and shaped regulators. We explore how authority bias, framing, social proof, and status quo effects were leveraged through pain societies, “pain as the fifth vital sign,” influential physicians, and normalized side-effect disclaimers to manipulate perceived risk. We discuss conflicts of interest and regulatory capture at the FDA, plus distributors ignoring data red flags despite duties to monitor suspicious orders. Concluding, we call for risk programs that account for financial motivation but extend beyond profit to long-term human well-being.

This episode reviews the rise and fall of Archegos, the 2013 Midtown Manhattan family office run by Bill Hwang, who previously settled SEC insider-trading charges at Tiger Asia. Using financing from six banks—Goldman Sachs, Morgan Stanley, Credit Suisse, Nomura, Deutsche Bank, and UBS—Archegos employed heavy leverage and total return swaps to build concentrated, largely undisclosed exposures, amplifying gains as stocks rose. In March 2021, declines— especially around ViacomCBS—triggered margin calls, forced selling, and a downward spiral that led to a bank fire sale, roughly $20B in Archegos losses and about $10B in combined bank losses, with Credit Suisse and Nomura hit hardest. The discussion highlights Hwang’s information-control style, misrepresentation to banks, behavioral dynamics like overconfidence and risk perception, a prisoner’s-dilemma unwind among banks, and the central lesson: reduce information asymmetry through due diligence in complex, high-stakes transactions.

This episode of Behavior and Risk examines how AI is being deployed across healthcare—from chatbots and personalized treatment planning to imaging and surgical tools—and focuses on the regulatory landscape, especially in the United States. We argue U.S. oversight is a patchwork that relies heavily on the FDA’s “substantial equivalence” pathway (97% of authorizations), a framework rooted in older standards, while AI systems function as black boxes and evolve rapidly. We discuss information asymmetry between developers and regulators, FDA staffing losses, and how incentives and cognitive biases (inertia, conflict aversion, availability, groupthink, intertemporal discounting) may lead to underappreciated risk. We cite concerns about patient inability to opt out or even be informed and highlight Epic’s sepsis prediction model’s performance issues and potential harm. The conversation ends by emphasizing the need to reduce uncertainty and communicate AI risks clearly without causing cognitive overload.

We break from past episodes to analyze the ongoing Blue Owl Capital saga and make predictions about a current case's outcome, using it as a live case study in risk management and investor psychology. We discuss private credit markets, why borrowers use it versus public markets, and how Blue Owl’s OBDC II fund became stressed amid heavy concentration in tech/SaaS-focused loans. After proposing a merger with publicly traded OBDC that would have effectively locked in about a 20% loss, investors resisted; soon after, Blue Owl closed OBDC II’s redemption window, shifted to discretionary distributions, and later paid a one-time 30% NAV redemption funded partly by selling $1.4B of loans at par, triggering a steep share decline and six class-action lawsuits. We compare Blue Owl’s approach with Blackstone’s increased redemptions and $400M injection and BlackRock’s contract-based stance, discuss anchoring, loss aversion, learned helplessness, and predict tighter underwriting and new valuation models, while debating whether Blue Owl can survive.

We compare memories of the failed AOL–Time Warner merger with the turbulent 2025–2026 battle for Warner Bros. Discovery, arguing the new case is fundamentally different despite superficial parallels. We trace the timeline from WBD’s plan to split streaming/studios from legacy cable debt, through Paramount’s escalating bids, Netflix’s later entry and perceived “white knight” alignment with WBD’s breakup strategy, and eventual government intervention that derailed Netflix and enabled Paramount’s February agreement. We discuss behavioral forces shaping decisions—representativeness, availability, deal lust, sunk costs, loss aversion, groupthink, authority bias, and intertemporal choice—alongside financial and regulatory risks, including heavy leverage, planned cost synergies, antitrust scrutiny, labor union concerns, and Fitch’s junk downgrade that reversed an initial market rally.

In this episode of Behavior and Risk, we discuss Singapore’s Monetary Authority imposing collective fines totaling $21.5M on nine financial institutions—including UBS, Citibank, and Julius Baer—tied to a 2023 money laundering case involving more than $2.2B in illicit assets, the second-largest collective penalty in Singapore’s history. We recap how authorities detected suspicious networks in 2021, investigated through 2022, and executed island-wide raids on August 15, 2023 with over 400 officers, arresting nine men and one woman and seizing nearly 100 properties, 50 luxury vehicles, cash, bank accounts, and luxury goods, with total seizures later exceeding $2B. The conversation focuses on why penalties and jail terms (13–17 months for the foreign nationals) seemed low, and how the absence of charges against senior bank leadership shifts the interpretation from corruption to negligence and poor risk management. We examine MAS findings that breaches stemmed from inconsistent implementation of existing controls, including failures to conduct general money laundering risk assessments for new clients, validate sources of wealth for high-risk customers, and properly escalate concerns. We connect the breakdown to behavioral and organizational factors such as overconfidence fueled by Singapore’s reputation, automation bias, check-the-box compliance culture, loss aversion, normalization from competitors onboarding the same clients, and challenges of enforcing enterprise-wide standards across global organizations, emphasizing the gap between documented protocols and real execution—“failing to put the E in ERM,” including execution itself.

In this thought-provoking episode, Rich & John delve deep into the concept of loss aversion and its pervasive influence on human behavior and decision-making. Unlike previous episodes that focus on specific cases, this discussion explores the foundational aspects of loss aversion, describing its implications for risk management and beyond. Listeners will gain insights into the formal definition of loss aversion, its distinction from risk aversion, and how these concepts manifest in various domains, including finance, social status, and identity. The conversation further explores the evolution and neuronal basis of loss aversion, emphasizing its inherent, unavoidable nature. Rich & John also discuss the interplay between loss aversion and strategic planning, particularly in the context of enterprise risk management (ERM), and highlight the importance of balancing loss aversion with opportunity-seeking behaviors to avoid stagnation in both organizations and personal careers.