Description: Presented at June 1986 Spring Meeting. This session discussion is about the National Association Of Insurance Commissioners' Early Warning System, A.M. Best Company ratios, Conning and Company solvency ratios, and California Department of Insurance Empirical ratios.

Description: Abstract: 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: Maintaining solid financial performance is a KPI for senior management. With the advancement of technology, the management can leverage new techniques to improve their decision making and focus on higher value activities in a timely manner. This presentation sets out the use of 1. correlation analysis to draw relationship between financial metrics and 2. smart analytics techniques, including text mining and analytics, to identify trends and drivers that impact the valuation of a company. We will also assess how the results of a comprehensive financial analysis could influence risk management considerations, including business steering and risk strategy.

Description: By disinformation we mean the inclusion of data that should not be considered in a study. In this paper we discuss a case in which the presence of disinformation was clear, but it was not possible to determine with certainly which records were extraneous.

Description: Predictive modeling continues to gain traction in the life insurance industry with the rapid growth of available data and maturity of open source tools. New methods and technology in predictive analytics have enabled the evaluation of extremely large data more quickly and allow us to incorporate features previously not considered. The presenters will provide background on predictive modeling tools and algorithms utilized by actuaries and data scientists for life insurance, highlighting applications from marketing to underwriting.

Description: Here we break down deep learning into its various conceptual sets so as to have a better intuitive understanding of deep learning.

Description: This article shares our experience of using the cloud to do large-scale parallel processing and discusses some background regarding the cloud.

Description: Letter fron the Chairman.