Description: The article provides a high-level, non-technical, introduction to artificial neural networks (ANNs) and deep learning with an application to risk management. The method relies on typical ANN components such as nodes, activation functions, and optimization through gradient descent.

Description: The article provides a high-level, non-technical, introduction to artificial neural networks (ANNs) and deep learning with an application to risk management. The method relies on typical ANN components such as nodes, activation functions, and optimization through gradient descent.

Description: The article is based on a study of causes of insolvency and decisions made by management, regulators, and policyholders over the life cycle of the insolvency.

Description: The author suggests ways to strengthen a company's enterprise risk management process, including the development of an "effective resilience factor," a risk metric that reflects an organization’s exposure and response to an adverse event, and measures the ability of the organization to mitigate the reduction in its operating level.

Description: The costly, time-consuming and complicated process of enterprise risk management (ERM) can be improved in many companies and made less tedious for managers by using reasonable data and templates obtained from peer group entities. The models used to calculate economic capital (EC) often underestimate its value because they do not consider decision-maker perception about risk. We assume here that managers, as the decision-makers, have appropriate business understanding and they can provide substantial information about risk characteristics regarding all business processes. Therefore we are focused, in this paper, on collecting data from managers across the different businesses to derive the appropriate knowledge about risky events, the importance of particular types of risk, the relationship between the risk outcomes and the level of risk control in a particular industry. We conclude that the collected data has a high potential for use as a benc hmarking reference and analysis for improving ERM models for individual businesses.

Description: Risk management techniques do not include system science. System science requires that the uncertainty of the world is incorporated into the results. The articles explains the difference between risk and uncertainty. Learn how risk practices create an overoptimistic view of future outcomes.

Description: An exploration of Canada’s federal regulator of financial institutions (OSFI) and its more formal assessment of the actuarial function of insurers.

Description: Summary of recent surveys to life actuaries regarding assumptions surrounding policyholder behavior in the tail for universal life with secondary guarantees and minimum guarantees on variable annuities. This information is intended to examine and ultimately give guidance to actuaries on how to set policyholder assumptions in extreme scenarios.

Description: This paper presents actuarial (mathematical) models for cyber breach probability as function of the level and allocations of security spending by a firm.

Description: To deal with future correlation crises, the author suggests the implementation of ‘’quanlitative analysts’’ (‘Quanls’) in the enterprise risk management (ERM) process: risk managers who are able to lead interdisciplinary ERM studies from a jointly qualitative and quantitative point of view, with an emphasis on dynamics.