154 résultats
pour « riskmanagement »
"This document explains the enterprise risk management framework in a flow chart form."
"This document is showing the flow chart of life insurance risk"
"We portray the distributions that are fundamental for enterprise risk management and describe when they can be used. These include the Bernoulli distribution, the binomial distribution, the Poisson distribution, the uniform distribution, the triangular distribution, the PERT distribution, the modified PERT distribution, the trapezoidal distribution, the custom distribution, the normal distribution, the lognormal distribution, the Weibull distribution and the compound distribution."
"Neural networks are suggested for learning a map from d-dimensional samples with any underlying dependence structure to multivariate uniformity in d′ dimensions."
"Neural networks are suggested for learning a map from d' dimensional samples with any underlying dependence structure to multivariate uniformity in d′ dimensions."
"We find that depending on the capitalisation of the network, a holding structure can be beneficial as compared to smaller separated entities. In other instances it can be harmful and actually increase contagion. We illustrate our results in a numerical case study and also determine the optimal level of holding support from a regulator perspective."
"... results are applied in a wide range of actuarial problems including multivariate risk measures, aggregate loss, large claims reinsurance, weighted premium calculations and risk capital allocation. "
"From a supervisory perspective, the use of AI can be expected to decrease regulatory enforcement costs while providing technology-advanced players with opportunities to game the regulatory system."
"Financial supervisors as well as financial intermediaries increasingly rely on AI. However, little remains known about the scope and pervasiveness of this evolution."
"We extend the scope of risk measures for which backtesting models are available by proposing a multinomial backtesting method for general distortion risk measures. The method relies on a stratification and randomization of risk levels. We illustrate the performance of our methods in numerical case studies."