Exposure modelling is often the most difficult components of risk analysis, with the value of exposure often being a complex mix of capital stock, replacement cost estimates, production, indirect and chain-linked components. We provide transparent exposure estimates using the latest global methods which contribute to our risk models. The developed assessment of financial exposure as well as human exposure is calculated from much use of historical census data, government level data and Daniell (2014).
An economic value of exposure to cyber risk or terrorism is quantifiable when combining the capital components at risk, interconnected companies, services and extended networks. Similarly for casualty insurance or decision-making, the value of intangible parameters such as life is an important measure which we have done a lot of research on. This allows cost-benefit ratios, mitigation and premiums to be calculated. In addition, we have calculated risk of death due to various causes, for use in risk modelling and exposure quantification for the life sector.
Capital stock and replacement cost need to be compared in order to create a robust estimate of economic exposure. Production data on a subnational level has been examined and collected as part of the exposure databases of Daniell (2014) which are used within our exposure modelling. We combine various levels of spatial datasets within CATDAT and years of experience creating exposure profiles to assess the financial and social capital on any scale of resolution