Geopolitical shocks expose dangerous blind spots in financial risk models

Geopolitical risk has moved from the margins of financial risk management to the center of model design.

For banks navigating sanctions regimes, trade fragmentation, and policy volatility, traditional risk frameworks increasingly struggle to capture the scale and speed of modern shocks.

Krishan Sharma, SVP, Model Risk - Regulatory Stress Testing and Capital Forecasting at Citi, believes the industry’s reliance on historical data has created a fundamental weakness in how institutions assess emerging geopolitical threats.

“The fundamental issue is that our traditional models are empirically calibrated,” Sharma said. “They rely on the assumption that the future statistical properties of a system will resemble the past.”

That assumption breaks down during geopolitical crises. According to Sharma, sudden sanctions, military conflict, or supply chain disruptions do not behave like normal market volatility events.

Instead, they represent structural breaks that alter the entire distribution of risk.

“Geopolitical shocks are structural breaks,” he said. “A sudden sanction regime or blockade does not behave like a standard deviation move in a normal distribution. It changes the distribution entirely.”

The result is that many widely used risk tools, including value at risk and credit models, become backward looking precisely when institutions need forward looking insight.

“Traditional models are rearview mirror driven,” Sharma said. “When a geopolitical shock hits, correlations spike and historical calibration windows fail to capture the velocity of the transmission.”

For Sharma, the challenge is not simply about designing more severe stress scenarios. Instead, firms must rethink how shocks propagate through the financial system.

“We are trying to model unknown unknowns using a dataset of known knowns,” he said. “That creates a dangerous lag in signal detection.”

In the current geopolitical environment, Sharma argues that firms should move beyond stress testing frameworks that assume gradual economic deterioration. Instead, scenarios must capture rapid regime shifts and persistent disruptions.

“We need to move beyond regulatory exercises that assume a linear degradation of variables over nine quarters,” he said.

One critical improvement involves modeling regime switching dynamics. Traditional portfolio diversification assumptions may collapse during periods of geopolitical turmoil.

“In a stagflation scenario, the typical negative correlation between equities and bonds might flip to positive,” Sharma explained. “That nullifies diversification benefits.”

Another approach involves reverse stress testing. Instead of starting with macroeconomic shocks, institutions should identify events that could destabilize their balance sheets and work backward to understand how those conditions might arise.

“What geopolitical event would break our liquidity position,” Sharma said. “That is the question firms should be asking.”

Policy volatility is another factor that models often fail to capture. Standard scenarios typically assume central banks respond predictably to economic shocks, smoothing market stress.

“We need to stress test for policy errors or policy volatility,” Sharma said. “Central bank reaction functions may become unpredictable or even conflict with fiscal policy.”

Beyond macroeconomic stress testing, Sharma also argues that institutions must improve how geopolitical events are linked to cascading risk effects across the organization.