Description: Presented at May 2005 Spring Meeting. Panelists discuss currently available data standards, forecasts about the future uses of data standards, and standards being adopted by Information Technology departments.

Description: The study of Employee Benefits has always been aided by using financial algorithms. During recent semesters, the Lotus 1-2-3 package Lotus has been introduced to students due to the explosion of its use in the business community. This paper will show how our students use Lotus to design a spreadsheet for computing minimum annual distributions from tax-sheltered plans.

Description: Although rate structures where low-cost cohorts subsidize high cost cohorts may be justified from a actuarial, marketing, or legal standpoint, the subsidization creates risks which must be understood and monitored. This article presents the concept of subsidization signature to measure and interpret the effects of rate subsidization, and to assess the sustainability of rating structures and the sensitivity of business mix assumptions.

Description: It has been twenty years since DeWit 1982 first applied fuzzy logic FL to insurance. That article sought to quantify the fuzziness in underwriting. Since then, the universe of discourse has expanded considerably and now the FL methodologies include used fuzzy set theory, fuzzy numbers and fuzzy arithmetic, fuzzy inference systems, fuzzy clustering algorithms, fuzzy linear programming, fuzzy regression, and hybrids involving other soft computing technologies. This article presents an overview of these studies.

Description: The guest editorial details some valuable lessons during the author’s career as an employee benefits (mostly retirement) consultant, turned P&C predictive modeling, reporting and data warehousing lead, turned an analytic strategist and independent consultant.

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: The Society of Actuaries (SOA) is pleased to bring you information about the actuarial career path in life insurance and predictive analytics. We’ll continue to share more about actuaries who are tackling some of the industry's biggest challenges and top employers in life insurance.

Description: Meet Christine Hofbeck. Christine is pushing the boundaries of traditional life and general insurance by finding problems and fixing them with new technology, modeling methods and sources of data. Most recently, she built a predictive analytics team at one of the world's largest financial services institutions to support the pricing team for a $5 billion portfolio covering life, disability, critical illness and more.

Description: Applying the new GDPR terms to Actuarial work, to secure private data in portfolios while using those for pricing and reserving modelling in all business lines.