The world of finance is undergoing a dramatic shift as Wall Street grapples with the increasing unpredictability of global conflicts. The rise in the number of countries engaged in external wars and the staggering economic impact of violence have forced financial institutions to reevaluate their risk models. The traditional approach of relying on historical data and rear-view mirror models is no longer sufficient in a rapidly changing geopolitical landscape. This is where the expertise of catastrophe modelers comes into play, as they adapt their skills to predict military conflicts and help investors, banks, and insurers navigate the treacherous waters of global politics.
The Institute for Economics and Peace reports that the economic impact of violence now stands at almost $22 trillion, equivalent to more than 10% of the world's GDP. This staggering figure highlights the urgent need for more accurate and forward-looking risk models. Citigroup and Morgan Stanley have both warned against the limitations of historical models, urging a rethinking of geopolitical risks. The demand for predictive, forward-looking models is clear, and companies like Verisk Maplecroft are rising to the challenge.
Verisk's Predictive War Index is a groundbreaking model that uses machine learning to forecast the likelihood of war in a country over the next 12 months. Trained on political, economic, and social datasets from 1995-2022, it demonstrated impressive accuracy in back-testing. For instance, in early January, the model predicted a 66% probability of war breaking out in Iran within 1.5 months, a remarkable feat. Verisk's Geopolitical Relations Index further enhances their capabilities by tracking tension levels between countries, considering factors like military clashes, government styles, and geographical proximity.
Verisk's models have already proven their worth. Their separate model, launched in October 2023, correctly predicted six out of seven government collapses, including the ouster of Bashar al-Assad in Syria and the sudden removal of Venezuela's Nicolas Maduro. These predictions are not just about describing potential outcomes but also about guiding policymakers with specific actions to influence probabilities. For instance, the model suggests that sanctions pressure, diplomatic engagement, or support for civil society could significantly impact the likelihood of regime change.
The traditional models often fall short in the current climate, as events like trade blockades or economic sanctions don't follow a normal distribution. This is where catastrophe risk specialists like Krishan Sharma come in, emphasizing the need for new risk algorithms to address the unique challenges posed by these events. The shipping disruption in the Strait of Hormuz is a prime example, with Lloyds of London quoting marine war risk premiums as high as 1% of a vessel's value per voyage, a stark contrast to pre-conflict rates.
The integration of these new models into underwriting and exposure management workflows is crucial for insurers. By allowing them to predict and assess disruptions across shipping routes and supply chains, these models provide a more comprehensive understanding of the potential economic losses. This shift in focus from physical damage to broader disruptions is essential in a world where relatively low-cost acts can generate disproportionate economic losses.
Tina Fordham, co-founder of Fordham Global Foresight, warns of the accelerating geopolitical volatility. The current events align with her supercycle geopolitics thesis, where increased risk drivers are breaking through global guardrails, leading to a higher number of geopolitical shocks. This trend has already marked a wake-up call for the C-suite, highlighting the need for more robust risk management strategies.
The adaptation of catastrophe modeling techniques to predict wars is a significant development. By drawing on methodologies used for natural catastrophes, strikes, riots, and civil commotion, risk experts are expanding their toolkit. This integration of predictive models into financial operations is essential for navigating a fragmented, multipolar world, where the old globalization-driven efficiency is no longer a reliable guide. As war becomes the primary concern for businesses seeking insurance, the importance of these new models cannot be overstated.
In conclusion, the financial industry is at a critical juncture, where the traditional approach to risk modeling is being challenged. The rise of geopolitical risks and the economic impact of conflicts demand a more proactive and predictive approach. Catastrophe modelers and risk experts are stepping up to the plate, offering innovative solutions to help investors, banks, and insurers make sense of a rapidly changing world. As the old guardrails crumble, the need for forward-thinking models has never been more apparent.
