Description: Advanced Topics in Corporate Finance and Enterprise Risk Management (ERM) covers a broad range of corporate finance concepts. As part of a 10-year strategic plan exercise, you'll apply opportunity engineering to help guide senior management in introducing a new product to market. You'll also focus on three applications of Extreme Value Theory (EVT), which are covered and tested in a business context.

Description: This report looks at identifying drivers of systemic risk in China’s insurance industry and develops a measurement method for systemic risk as well as systemic risk dependence between the insurance industry and other industries.

Description: The direct and indirect effects of the pandemic have impacted many actuaries’ work since the spring of 2020. This article addresses three considerations actuaries should account for when using risk evaluation models which are focused on projecting remote, highly unlikely losses: model effectiveness, asset risk, and insurance (mortality and mortality) risk.

Description: Article discussing the benefits of the Chartered Enterprise Risk Analyst, CERA, credential.

Description: The CIA, SOA and Joint Risk Management Section of the CAS, CIA, and the SOA sponsored a whitepaper on the application of ERM at a federal government level.

Description: Pricing is a central activity of actuaries to assure solvency and to manage risk. Life insurance is also a social good, not just a product, and the US population is massively underinsured. Pricing must strike a balance. Unlike a simple 4x4 matrix to produce pricing, today's technology offers the ability to evaluate literally thousands of variables, enabling a kind of precision pricing. It also heightens the possibility of introducing bias and discrimination through the use of unregulated third-party data.

Description: Insurers are increasingly using advanced analytics to model expected outcomes. Two well-known examples in the life insurance industry are models for predicting policyholder behavior and to manage risk selection. The presenters will explore the various types of advanced analytics being considered in models and how the associated risks of these models can be incorporated into an enterprise's risk framework.

Description: Analyze the market volatility behavior in context with historical extreme events during this webcast. There will be a focus on understanding volatility clustering and relationships, both contemporary and temporal, in addition to key economic and capital market variables. You'll also learn from a comprehensive attribution analysis, which uses economic data, asset data, retail investor data and event data as explanatory variables. Dive into investment-related Reddit comments used to capture features of retail investors and tree-based models, including Random Forests and Gradient Boosting Machines to justify changes in volatility modeling. Expect this webcast to end with an example of liability-driven investment optimization that illustrates the potential impact of increased volatility assumption, how to adopt stochastic volatility models, how to reflect volatility clustering and return jumps.

Description: An introductory article describing how Bayesian statistics has evolved over the past 20 years and why it offers the actuarial discipline powerful tools to better understand and manage risk. Compared with traditional (frequentist) and black-box (machine learning) approaches, Bayesian analysis provides explainable models focused on distributions of estimates instad of simply point estimates.

Description: Gather with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, pension, investment, product strategy, and more.