Systemic risks are potential trigger events or developments that could undermine the viability of entire networks or systems. For example, systemic risk from Mycoplasma bovis or COVID-19, could be significant damage to the New Zealand economy. However, artificial intelligence (AI) can identify such risks earlier and facilitate quicker responses and better outcomes. 

Introduction

We present a novel, state-of-the-art method for systemic risk detection based on AI. Development and deployment of this method could save the New Zealand economy hundreds of millions of dollars over the next decade.

Examples of systemic risks include contagious food diseases and the bankruptcy of keystone companies and they're likely to happen more frequently in the future as markets (eg financial) are becoming increasingly complex and opaque, technological change is accelerating at an unprecedent rate and the global political situation is becoming more unstable.

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