Quantum Innovation Challenge: Joint-Loss Modelling for Disaster Risk Financing

Can quantum computing improve how we model correlated disaster losses? Join ADB’s Quantum Innovation Challenge to develop and benchmark innovative approaches for disaster risk financing and resilience applications.

CHALLENGE BACKGROUND

ADB is expanding its portfolio of catastrophe risk products. A recent example is the US$160 million Disaster Relief Bond issued in May 2026 as part of the regional Risk-Layered Disaster Relief Finance Program for the Kyrgyz Republic and Tajikistan. Products like these rely on catastrophe models to price risk, and those models have a data problem. There are only a couple of decades of high-quality disaster records, so most model testing depends on synthetic event catalogues.

Joint-loss models estimate how losses from a single event can affect several assets, sectors, or regions at the same time. They are standard in insurance and actuarial analysis, but they are hardest to get right for extreme events, where data is thinnest. In this case, the two countries share fault lines and glacier systems, so one event could drive losses in both at once.

Better joint-loss models would help ADB estimate its exposure to severe shocks and test questions like “what if earthquake risk across both countries is more correlated than current models assume?” Current simulation methods need very large numbers of samples to estimate rare joint events precisely, which leaves room for new approaches.

CHALLENGE OBJECTIVES

The Quantum Innovation Challenge seeks to:

  • Evaluate whether quantum and quantum-inspired approaches can improve the modelling of correlated disaster losses compared with existing classical methods.
  • Advance joint-loss modelling techniques that capture dependencies and extreme-event risks across multiple geographies and exposures.
  • Assess the feasibility, scalability, and practical applicability of proposed solutions using current or near-term computing infrastructure.
  • Explore how improved joint-loss modelling can support disaster risk financing, catastrophe risk analysis, and related risk management applications.
 
The challenge examines how quantum technologies could be applied to improve these models through the lens of simulated scenarios based on real-world catalogues of earthquakes and extreme-precipitation events in Central Asia – mirroring recent issuances of insurance-linked securities by the Asian Development Bank.