A recent joint study by the Swiss Re Institute and the London School of Economics and Political Science (LSE) has highlighted the emergence of new pathways for economic and operational shocks to spread rapidly across multiple sectors and economies. This increased risk transmission is attributed to the growing reliance on artificial intelligence (AI) and the interconnectedness of global supply chains. The study emphasizes that the nature of systemic risks is changing, requiring the insurance sector to reassess its risk measurement and mitigation strategies.
The study notes that AI can increase the interconnectedness of economic and operational systems, as various institutions and sectors increasingly rely on shared digital infrastructure, software, and data providers. This interdependence means that a disruption in one component can quickly affect a large number of users, rather than being confined to a single institution or sector. The growing use of AI in operational processes and decision-making further amplifies the potential impact of technical failures or data disruptions on a wide range of economic activities.
Global supply chains are another significant source of increasing interconnectedness between companies and sectors. Companies are not isolated from their suppliers, transportation networks, logistics services, technology providers, and energy suppliers. A disruption in one key component can have cascading effects that extend beyond the affected company. The sensitivity of these supply chains is exacerbated when a large group of companies relies on a single supplier or shared infrastructure, making certain risks more likely to spread throughout the economy.
The study's findings have important implications for insurance companies, particularly in understanding systemic risks that can lead to widespread disruption across multiple institutions or sectors. Systemic risks are those that cannot be contained within a single entity but can cause significant instability across a broad range of sectors and institutions. Swiss Re emphasizes that understanding systemic risks can no longer be achieved solely through the analysis of individual sectors or institutions but requires an examination of the connections between them and how shocks can propagate through these links.
The increasing interconnectedness poses significant challenges for insurance companies, as traditional pricing models may be insufficient when multiple correlated risks occur simultaneously. The study highlights the need for additional risk-bearing capacity, including the use of insurance-linked securities (ILS) and alternative capital. These tools provide an additional source of capital that can be used to transfer some insurance risks to investors, helping to expand the capacity available to insurance and reinsurance companies.
The importance of this issue is underscored by the growing investments in AI, digital infrastructure, and supply chains. As these activities continue to expand, they give rise to new clusters of risks that require more sophisticated models for measurement and pricing. The study's authors stress that insurers and reinsurers must adapt to these changing risk landscapes to ensure they can provide adequate coverage and support to their clients.
The study's findings serve as a warning to insurers, regulators, and policymakers of the need to address the evolving nature of systemic risks. By understanding the complex interactions between AI, supply chains, and systemic risks, stakeholders can work together to develop more effective risk management strategies and ensure the resilience of the global economy.
Key points
- Insurers must reassess risk measurement and mitigation strategies due to increased reliance on AI and interconnected supply chains.
- Systemic risks can no longer be understood through analysis of individual sectors or institutions alone.
- Additional risk-bearing capacity, such as ILS and alternative capital, may be necessary to address emerging risks.
