Researchers are using network analytics and advanced data modeling to identify weak spots in the system that otherwise might go unnoticed.

This type of analysis is part of a growing area of research that is changing how regulators and banks manage financial risk. Network analytics as well as new modeling approaches, allow researchers to show how thousands or millions of iterations of apparently simple financial exchanges or actions together can create a far more complex and at times unstable financial system than traditional economic theory might suggest. Already, such approaches are being used in bank stress-testing and to spot weaknesses in global markets. Some envision the technology eventually could be used to build a dashboard of the global financial system that regulators could monitor to spot crises before they hit.

Research by INET Oxford's Prof Doyne Farmer has been cited in a recent article in the Wall Street Journal exploring how data modelling might help monitor finacial markets. The work of Prof Farmer and his team is helping the Bank of England develop agent-based models to better understand how markets and other complex financial systems behave.

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