Interdisciplinary risk research
The Macquarie University Emerging Risks Research Centre conducts research across a range of themes.
Our centre's research is grouped into three key areas. Learn more about each of them below.
Economic and financial risks
Asset price bubbles, characterised by unsustainable surges in asset values driven by speculative behaviour, can lead to sharp corrections and financial crises when they burst, as evidenced by historical events like the Global Financial Crisis.
Similarly, systemic risk poses a significant threat by enabling localised financial instability to spread across institutions and markets, potentially disrupting the entire financial system.
These risks are closely tied to emerging risks due to their:
- dynamic nature
- real-time detection challenges
- sensitivity to rapidly evolving economic and technological landscapes.
The increasing availability of high-frequency data offers new opportunities to enhance risk measurement and detect market abnormalities, but it also introduces complexities in effectively analysing and responding to these risks.
As markets grow more interconnected and reliant on digital platforms, the speed and scale of risk propagation intensify, rendering traditional risk assessment methods insufficient. Addressing these challenges is critical for building resilient financial systems that can adapt to emerging risks and safeguard economic stability.
Environmental and societal risks
Pandemics, and shifting demographics, are key components of emerging risks, distinguished by their global scope, long-term consequences and intricate interdependencies.
These risks are inherently complex, often requiring high-dimensional models for effective analysis.
- Climate risks are studied using models that incorporate a vast array of variables spanning climate science, economics and social factors to predict policy impacts under various scenarios.
- Pandemics are analysed through high-dimensional epidemiological models which account for numerous interacting parameters such as transmission rates, mobility patterns and vaccination strategies.
- For demographic shifts, dynamic population models integrate variables like age structures, migration trends and economic factors to project societal impacts.
Technological risks
Technological risks, such as those related to cybersecurity, digitalisation, artificial intelligence (AI) and biotechnology, are a critical subset of emerging risks. These risks share unique features:
- they are highly dynamic
- difficult to quantify due to limited historical data
- often interdependent, amplifying their complexity.
Emerging risks like systemic cyberattacks, ethical challenges in AI, unintended consequences of digital transformation and biotechnological advancements (eg synthetic biology) can disrupt industries, economies, and societies.
To analyse these risks, a multidimensional approach is necessary. Machine learning and AI models help in predictive analytics by identifying patterns and early warning signals in vast, complex datasets. By adopting an interdisciplinary perspective, organisations can proactively mitigate and adapt to the evolving landscape of technological risks.