Description: This article discusses how to get data into and out of R, an open source language for statistical computing.

Description: Presented at May 1996 Spring Meeting. This session offers a retrospective and prospective look at the development of actuarial pricing models and technology tools.

Description: Most actuaries deal with model development at some point in their career. However, very few of us have proper training in programming, software engineering or software shop operations. Explore topics, techniques, and practices from the FinTech and IT industries that can be applied to building robust, high-quality actuarial models. This session will be of particular interest to actuaries engaged in 'in-house' model development, managers of modeling teams, and actuaries interested in software development.

Description: Data science, predictive analytics and AI are certainly the buzzwords these days. They are heavily used and developed in underwriting and marketing but for most actuaries, they might/may as well be science fiction. The presenters will demonstrate how a normal actuary can utilize data science techniques in their daily job function without forming an official data science team within a company. It can be done in a gradual fashion so that normal business is not disrupted and improvements are made over time. The usage of data science techniques will include demonstrations of the following areas: - Regression analysis - Economic scenario generator - Experience study - Data quality checks - Inforce compression for explicit hedging

Description: Stochastic modeling requirements are resulting in more 'run time' and less 'analysis time'. An expensive solution is leveraging cloud infrastructures and robust computing grids. The presenters will explore the use of cluster modeling and present case studies showcasing this automatable and robust technique, which could allow actuaries to recover the time lost to 'run time'. Developing automatable and clustered models requires robust governance practices to ensure credibility of results.

Description: Opinion piece about when, how, and why actuaries need approximations.

Description: The complex world of life insurance, historically the domain of those gifted in integral calculus and probabilistic and present value mathematics, is explored using Excel spreadsheets and the Solver macro. The cash flow approach to learning life insurance examines how the cash flows through an insurance company without using higher math.

Description: A disscussion of actuar R, an R package for actuarial science, and its facilities in the fields of loss distribution modeling, risk theory and credibility theory.

Description: This presentation is a concurrent session from the 1991 Meeting of the Society of Actuaries, held April 18-19 in New Orleans. The panel will discuss the approaches and techniques used for pricing and modeling insurance products, including commercial software, internal systems, maintenance issues, staff training, and asset/liability systems. Discussion from participants is included. From the Record of Society of Actuaries, Volume 17, No. 1.

Description: Discusses the RAND function in Excel and alternatives for generating random numbers.