NEW YORK — Financial firms are increasingly turning to sophisticated risk models traditionally used to forecast hurricanes and earthquakes in an effort to predict wars, coups, and geopolitical crises before they erupt.
In late May, risk-analytics company Verisk introduced a new tool known as the Predictive War Index, which uses machine learning to estimate the likelihood of armed conflict occurring within individual countries over the following 12 months.
According to Sam Haynes, head of data and analytics at Verisk Maplecroft, clients are demanding tools that look forward rather than merely explaining historical events.
“They want a predictive forward-looking view,” Haynes said.
The model was trained using political, economic, and social data spanning 1995 through 2022, allowing it to identify patterns associated with conflict risk.
Although the model does not incorporate the current Iran conflict, Verisk said testing suggested it would have assigned a 66% probability of war in Iran roughly six weeks before hostilities began.
The company also launched a companion product called the Geopolitical Relations Index, designed to measure tensions between countries by evaluating factors such as military history, geographic proximity, political systems, and diplomatic relationships.
The effort is part of a broader expansion of political-risk modeling.
Verisk has previously developed forecasting tools for civil unrest, strikes, riots, and government instability. According to the company, a separate model introduced in 2023 successfully anticipated six of the last seven government collapses, including political upheavals in Syria and Venezuela.
The growing interest reflects the financial impact of geopolitical events.
Wars, trade disruptions, sanctions, and political instability have increasingly influenced commodity markets, shipping routes, energy prices, and global investment flows.
Major financial institutions have acknowledged that traditional risk-management frameworks may no longer be sufficient.
Citigroup has warned against relying too heavily on backward-looking models, while Morgan Stanley has argued that firms must rethink how they evaluate geopolitical threats.
The concern is that rare but severe events can erase years of gains in a matter of days.
For banks, insurers, and asset managers, reliable forecasting tools could influence everything from insurance pricing and catastrophe bonds to investment decisions and regulatory stress tests.
The goal is to assign measurable probabilities to risks that were once viewed as largely unpredictable.
There are limitations.
Models trained primarily on historical data may struggle to capture rapidly changing political realities. Human decisions, especially those involving war and diplomacy, remain far more complex than natural disasters.
Even Verisk emphasizes that its products are designed to supplement judgment rather than replace it.
Nevertheless, demand continues to grow.
As geopolitical tensions increasingly become a central factor in financial markets, institutions are investing heavily in tools that may provide earlier warning of emerging threats.
The adoption of disaster-modeling techniques for geopolitical forecasting underscores a broader trend on Wall Street: wars and political shocks are increasingly being treated as risks that can be quantified, priced, and managed.
JBizNews will continue monitoring advances in risk modeling and their broader effects on financial markets and global stability.
Wall Street — JBizNews Desk
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