Description: Project portfolio risk management and risk analysis form one of the critical components of enterprise risk management. Organizations measure and analyze risks associated with projects, project portfolios, and programs. The important step of the process is quantitative risk analysis of project schedules using event chain methodology (ECM). ECM is a stochastic modeling technique for schedule risk analysis. All risks, including schedule and nonschedule-related risks, are assigned to a particular project and within this project to the particular activity or resource. Further, ECM allows one to model the relationship between project risks by defining risks that cause or trigger other risks. All risks and relationships between them will be presented on the project or portfolio Gantt charts using event chain diagrams. After risks are assigned to project and portfolio schedules, Monte Carlo simulation of the project schedule is performed. ECM simplifies complex risk analysis process.

Description: In order to better develop skill in predictive analytics, the author suggests looking to professionals who design innovative predictive models and, more importantly, find effective ways to communicate their findings to a large audience.

Description: Industry briefings and SOA news

Description: This paper examines a differential equation model, whose solutions have yield curve shapes. The paper also examines the relevance of the model with historical monthly U. S. Treasury nominal rates. From the Actuarial Research Clearing House 1992 Vol. 1 .

Description: A new wave of life insurance buyers is finally here - but are we ready? In this article, Richard De Sousa shares proprietary research about the Millenial generation, its beliefs related to life insurance, and its preferences when it comes to learning about, purchasing, and engaging with life insurance products, advisors and companies. Also explored is the foundational role that technology and wellness play in driving the kind of experience that will attract millenial buyers. After reading this article, you will better understand the characteristics of this new generation as well as the innovative companies that are targeting them, and learn about different and novel ways to better engage with customers and enhance the value of your own products and services.

Description: Data is an essential component of financial analysis. In this session, the presenters will discuss data governance/management framework and how it can be applied to US GAAP LDTI and VM-51 regulations. This session will also discuss the important relationship between actuaries and IT and how they can work together towards best practices for extracting, managing and using data needed for various actuarial models. Real life case studies relevant for valuation actuaries (e.g. data needs for LDTI and VM-51) will also be presented and examined, highlighting best practices as well as challenges and pitfalls for setting up and governing data processes along with areas for where good communication and strong relationships are important to success.

Description: An analysis of health insurance cost and benefit trends using January 1, 2011 data from state employee medical plan renewals.

Description: This paper outlines a framework for assisting a STARS manager in implementing a quantitative approach to prioritize stars measures for targeted intervention

Description: This abstract describes a paper that presents new data that accounts for the confounding park factor variable in Minor League Baseball.

Description: Why small insurance companies should act now to enhance their reporting and analytical capabilities -How to start -Critical factors of success