"We present a novel approach to quantify the uncertainty and sensitivity of risk estimates, using the CLIMADA open-source climate risk assessment platform. This work builds upon a recently developed extension of CLIMADA, which uses statistical modelling techniques to better quantify climate model ensemble uncertainty. Here, we further analyse the propagation of hazard, exposure and vulnerability uncertainties by varying a number of input factors based on a discrete, scientifically justified set of options."
"We address the problem of sharing risk among agents with preferences modelled by a general class of comonotonic additive and law-based functionals that need not be either monotone or convex. Such functionals are called distortion riskmetrics, which include many statistical measures of risk and variability used in portfolio optimization and insurance."
"We address the problem of sharing risk among agents with preferences modelled by a general class of comonotonic additive and law-based functionals that need not be either monotone or convex. Such functionals are called distortion riskmetrics, which include many statistical measures of risk and variability used in portfolio optimization and insurance."
"Considering the proliferation of articles in this field, and the potential for the use of ML, we propose a review of the academic literature to assess how ML is enabling climate finance to scale up. The main contribution of this paper is to provide a structure of application domains in a highly fragmented research field, aiming to spur further innovative work from ML experts."
"The purpose of this article is to highlight the importance of taking a holistic approach to cyber. In particular, we argue that actuarial modelling should not be viewed stand-alone, but rather as an integral part of an interconnected value chain with other processes such as cyber-risk assessment and cyber-claims settlement."
"This architecture will improve board of directors’ decision-making, strengthen compliance and risk management protocols, empower gatekeepers such as lawyers and accountants to better monitor, and enhance the social contract between business and society. "
"We address the problem of sharing risk among agents with preferences modelled by a general class of comonotonic additive and law-based functionals that need not be either monotone or convex. Such functionals are called distortion riskmetrics, which include many statistical measures of risk and variability used in portfolio optimization and insurance."
Proposes a set of novel modeling mechanisms to regulate the size of banks' macroprudential capital buffers by using market-based estimates of systemic risk combined with a structural framework for credit risk assessment. It applies the model to the European banking sector and finds differences with the capital buffers currently assigned by national regulators, which have substantial implications for systemic risk in the EEA.
Proposes a new framework for regulating operational threats such as damage to physical assets, business disruption, and system failures. It suggests replacing rwa regulation with simple buffers of equity and outlines what a "macro-operational" approach to banking supervision might look like. It also acknowledges the limitations of macro-operational supervision and considers what new types of operations-specific emergency tools might need to be devised in response.
Monograph on accounting disclosure by banking institutions explores banking specificities, presents workhorse models, and illustrates specific applications of the models to inform policy.