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​Tackle the world’s most complex risks & get insights to optimise your portfolio


Our cutting-edge and scientifically rigorous models quantify the portfolio effects of primary and secondary hazards, cascading effects across systems, and agent-based decisions. This provides a holistic analysis of risks that allow you to make high-quality risk-informed decisions, including:

  • An optimised portfolio through risk insights & managing risks according to your strategies


  • Improved decision-making by ensuring decisions incorporate overlooked cascading systemic risks


  • Exposure management by being prepared for high-risk grey-swan scenarios


Customers & Key Benefits

Asset Owners

& Managers

  • Portfolio allocation: Quantify and reduce the direct and indirect impacts from CPC risks

  • Portfolio stress testing: Run through scenarios to simulate effects on your portfolio

  • Corporate guidance: Guide corporations to bettter manage CPC risks

  • Portfolio allocation: Incorporate CPC risks into portfolio and reinsurance decisions

  • Underwriting: Improve underwriting guidelines, and integrate risks into pricing

  • Stress Testing: Apply stress testing as part of risk and solvency assessment processes

Central Banks, Governments, & Financial Regulators

  • Systemic Framework:  Incorporate the cascading and systemic impacts in stress testing frameworks 

  • Stress Testing: Probe the resilience of the financial system and assess how the system can cope with severe and plausible scenarios



Modelling Methodology

We model primary and secondary hazards & threats, first-order and second-order system impacts, agent responses, and interlinkages.​ We use methods and simulations with a wide range of economic and process-based models, input-output models, agent-based models, cross-sectoral analysis, network analysis, policy analysis, and statistical analysis of existing datasets.

We use historical data and consult with academics, and forecasters to calibrate distributions and probabilities. We also use poll survey data and consult with governments to gain insight into agent-based decisions.

Our models differ from others in that we quantify interlinkages often neglected in other models, such as commodity price inflation and civil unrest, and trade and supply chain impacts, ranging from raw materials, production, processing and distribution. Quantifying these interlinkages allows us to overcome omitted variable bias.

1) Primary and Secondary Hazard Profiles & Agent-based Responses

Using data climate and environmental data, and socioeconomic data, the frequency and intensity of primary and secondary hazard profiles are mapped at the country level. Several of the systemic impacts are contingent on responses by governments, households, firms and other actors. We use agent-based models with observation-informed assumptions and geography-based localisations.

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Using public and private data, the probability that a certain loss value will be exceeded due to the primary event is calculated and graphed for a predefined amount of time in the future.

2) Exceedance Probability Data

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3) Monte Carlo Simulation of Outcomes

Monte Carlo simulations and sensitivity analysis are run to predict the impacts on sovereign debt default risk, expected loss and macroeconomic variables (i.e. GDP, interest rate, exchange rate, balance of payments, government debt, government spending, tax rate).

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Our Software Platform

Key Software Features

  • Dynamic dashboard showing cVAR and tVAR for a set of climate related natural hazards, and emerging infectious disease profiles

  • Monte Carlo simulations and sensitivity analysis to illustrate how outcomes change with input value changes

  • API for seamless integration with portfolio analysis tools

  • Investment evaluations for resilient financial productions, including how they reduce portfolio cVAR

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