Wall Street turns to war-risk models as conflicts shake economies
What's the story
As wars continue to disrupt the financial industry, Wall Street is turning to new catastrophe models for predicting military conflicts. The move comes as the number of countries involved in external conflicts has nearly doubled since 2008. According to the Institute for Economics and Peace, there are now just over 100 such nations. The economic impact of violence has also skyrocketed, reaching nearly $22 trillion, over 10% of the world's GDP.
Model reassessment
Financial industry struggles with war predictions
The finance industry is struggling to predict everything from oil prices to mortgage costs due to wars. Citigroup Inc. has cautioned against relying on "rear-view mirror" models based on historical data, while Morgan Stanley believes it's time to "rethink" the status quo of geopolitical risks more broadly. Sam Haynes, head of data and analytics at Verisk Maplecroft, a global risk consultancy, said insurers and investors now want a predictive, forward-looking view rather than looking back.
Innovative model
Verisk's Predictive War Index
Verisk Maplecroft has launched a new model, the Predictive War Index, to help financial professionals predict wars. The index uses a machine learning (ML) algorithm to forecast the likelihood of war in a country over the next 12 months. It was trained on political, economic, and social datasets from 1995-2022, and back-testing showed that it would have predicted a 66% probability of war breaking out in Iran if it had been available in early January.
Tension tracker
Geopolitical Relations Index
Verisk Maplecroft has also launched the Geopolitical Relations Index, which tracks changing levels of tension between pairs of countries. The model considers factors such as past military clashes, similarities in government styles, and geographical proximity. A separate Verisk model launched in October 2023 accurately predicted six out of seven government collapses since then, including the ouster of Bashar al-Assad in Syria in 2024 and Venezuela's Nicolas Maduro's sudden removal in January.
AI forecasting
RAND Corporation's AI model for predicting scenarios
The RAND Corporation has developed an artificial intelligence (AI) model that converts complex and uncertain questions like regime change into concrete probability estimates. The model uses the aggregated opinions of non-experts to predict future scenarios. When tested in mid-May, it showed a 20% likelihood that Iran's regime wouldn't survive into 2027. Anthony Vassalo, director of the RAND Forecasting Initiative, said these results aim to show policymakers how specific actions could influence those probabilities in practice.
Algorithm adaptation
Need for new risk algorithms in marine insurance
The disruption of shipping in the Strait of Hormuz has highlighted the need for new risk algorithms for marine insurance and global trade. After the Iran war started on February 28, Lloyds of London quoted premiums for marine war risk in this region as high as 1% of a vessel's value per voyage. Modeling experts are now treating conflict scenarios like terrorist attacks, where low-cost acts can lead to disproportionate economic losses.