Description: The academy generator is widely applied in actuarial practice. Initially confined to regulatory reserving, companies are increasingly using the AAA/SOA generator over an ever widening range of applications testing the limits of the academy generator's intended function. The session will give a brief overview of the academy generator and the asset classes it can be used to model. It will also analyze the statistical properties of the academy scenarios and discuss the scenarios relative to standard validation criterion. Some of the challenges that actuaries face in using this framework will be reviewed and options for addressing these challenges will be offered.

Description: Today's actuarial teams dedicate substantial time and resources to maintain strong frameworks for risk management and control. Current practices typically endure this as a sunken cost, yielding minimal value beyond SOX/MAR/COSO compliance and basic error prevention. With a small up-front time investment, and a willingness to approach these activities with an open mind, the functionality of existing compliance activities can be completely transformed. Compliance activities, once a sunken time cost, can be elevated to deliver more insightful analysis to stakeholders.

Description: Regulatory change and increased focus on internal risk management are driving a renewed interest in model efficiency. In this session, we will review several new and existing tools, that show significant promise for advanced modeling of equity linked products. These include: • Clustering • Use of unique--and potentially a different number of--scenarios for each policy • Semi Monte Carlo (SMC) – this is a proprietary technique that is similar to a combination of Monte Carlo and numeric integration • Using a neural network approach to optimize some of the more complex and manual aspects of clustering and improve the fit of the clustered model • Combining SMC with the use of unique scenarios per policy

Description: Insurance is a technically demanding, risk-based, capital intensive business. It is therefore not surprising that the industry is fertile ground for the development of technical models used to measure and price risk and manage capital. This session presents the forces which have significantly influenced the evolution of risk and capital management techniques and organization in the insurance industry, including regulatory changes, financial market instability, enlightened self-interest and ultimately a focus on shareholder value creation. Combining over 20 years in the industry in risk and finance roles with a rigorous academic approach, the presenter will provide insights into the most important business questions which insurers face today and the technical tools and frameworks used to answer them.

Description: Read the French language version of the March 2017 issue of Risk Management published by the Joint Risk Management Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Read the March 2017 issue of Risk Management published by the Joint Risk Management Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: The author uses football to demonstrate the axiom of downside risk, and how it can be applied in business situations when considering whether to use a conservative or aggressive approach.

Description: There are many factors involved with managing the financial condition of an insurance company and the factors usually fall into on of three categories: earnings management, capital management and risk management. Transfer pricing involves assigning a price for the use of funds that are transferred within the company.

Description: We analyze how volatility management techniques in VAs affected policyholders and insurance companies

Description: Findings from EY Insurance Risk Management Team's 2016 (annual) Insurance Chief Risk Officer Survey.