Description: 2011 SOA Enterprise Risk Management Symposium, Chicago. In this paper, a multivariate quasi-negative binomial distribution is proposed to model frequency dependence among different risk types. The operational risk diversification effect is illustrated through frequency dependency modeled by the bivariate quasi-negative binomial distribution under a framework of Monte Carlo simulation.

Description: This paper explores areas where fuzzy logic models may be applied to improve risk assessment and risk decision-making. It discusses the methodology, framework and process of using fuzzy logic systems for risk management. With the help of practical examples, it is hoped that it will encourage wise application of fuzzy logic models to risk modeling.

Description: This risk bulletin, published by the Society of Actuaries, provides insights and expertise on critical business issues from industry leading enterprise risk management actuaries.

Description: 2021 ImpACT Conference - Session 5A: Pandemic Rewind: Risk Management and Scenario Modeling Learnings 10.26.21 Recording

Description: After more than a decade of a prolonged low interest rate environment, long-term Treasury rates have started to increase with higher volatility. While it is generally agreed that a modest increase in interest rates and inflation is beneficial to the life insurance industry, interest rate risk remains a significant challenge for life insurance industry to manage its long duration liabilities, especially under volatile interest rate environments. Learn how to proactively manage interest rate risk and improve capital efficiency through the cash flow based strategic asset allocation (SAA) framework. Discover practical examples of how to combine asset allocation with derivatives to manage tail risk and liability convexity.

Description: This is the first of a two-part article introducing and elaborating an “Adaptor” strategy for ERM. Such a strategy is intended to fulfil two purposes: first, switching among four styles of risk-coping strategies in order to track qualitative changes in a business’s risk environment; and, second, to support the business in navigating with resilience through all the seasons of a business-economic cycle, i.e., of boom, bust, moderate, uncertain. This latter requires careful study of the nature of resilience, the familiar idea of bounce back, and the less familiar idea of bounce forward. Part I of our article is underpinned therefore by a supplementary document (available from https://riskviews.wordpress.com/adaptor-exceptionalism/), which addresses the issue of structural change in a business or economy. It draws heavily on ideas taken from the discipline of control engineering, as well as some from ecology, social anthropology, and economics. The entire two-part article is thus an exercise in cross-disciplinary Systems Thinking.

Description: Presented at September 1995 Valuation Actuary Symposium. This sessions talks about financial projections as a management tool and tough issues which may have to be addresses in making such projections.

Description: We find the necessary and sufficient conditions for fitting five given moments by a triatomic distribution. We consider three examples drawn from fire large spread, individual life medium spread and group life small spread insurance data, fit them with triatomics, and compute the ruin probabilities using well known formulas for discrete and for combination of exponentials claim amounts. We then compare our approximations with the exact values that appeared in the literature.

Description: Easy access computing power is harnessed to approximate ruin probabilities. The dynamics of the traditional insurance model are stated in the form of period to period constraints. This allows the development of a life-table with the survival probabilities for a given set of parameters. Given the spreadsheet approach of the model, sensitivity analysis to study the impact of different parameter values and loss variable distributions can be easily implemented.

Description: Come discuss modeling costs and its governance, as well as introduce some platforms for more granular asset modeling.