Financial institutions are increasingly adopting new predictive models, originally developed for natural disasters, to forecast geopolitical conflicts and their economic impacts. Firms like Verisk Maplecroft and Rand Corporation are using machine learning and AI algorithms to estimate the likelihood of wars and regime changes, moving beyond traditional historical data-based models. These new tools aim to provide forward-looking risk assessments for investors, banks, and insurers, helping them navigate a world with a rising number of conflicts. AI
IMPACT Financial institutions are gaining new predictive capabilities for geopolitical risks, potentially altering investment strategies and risk management practices.
RANK_REASON This article discusses the application of existing AI/ML techniques (catastrophe modeling) to a new domain (geopolitical risk prediction), rather than a novel AI model release or core AI research.
- Anthony Vassalo
- Bashar al-Assad
- Chris Boylan
- Citigroup Inc.
- Institute for Economics and Peace
- Krishan Sharma
- Morgan Stanley
- Nicolas Maduro
- Rand Corporation
- Sam Haynes
- Verisk Maplecroft
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →