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 April 2016 Issue of The Modeling Platform

Description: This panel discussion session reported on the status and content of the Actuarial Standards Board standard dealing with the selection of assumptions. The discussion covers what the effects would be on practitioners.

Description: Many top-performing businesses aren’t just risk aware, but rather risk intelligent. Such a posture helps prepare companies for a major event and can demonstrate to a regulator or auditor that an appropriately strong control framework is in place. Better still, companies gain real strategic value from a “risk adjusted” understanding not only of their threats and vulnerabilities, but also the upside opportunities associated with various risks. It starts with having both qualitative and quantitative information to identify, assess and manage risks. Strategic risk management, at its core, is about creating value by increasing transparency and accountability, and quality of information. More than a mere compliance exercise, effective risk management enables more informed strategic decision making, increased accountability and transparency, a greater likelihood of organizational success, and – ultimately – competitive advantage, as borne out by many studies that correlate risk management and financial results.

Description: 1987 Valuation Actuary Handbook: Chapter 1: Addresses life insurance company statutory reserve valuation.

Description: On October 30, 2015, the SOA Assumption Development and Governance Group, an informal discussion group consisting of nearly 200 interested actuaries with topics pertaining to actuarial assumption development and governance, organized an industry discussion call on end-to-end assumption documentation practices. The purpose of this call was to generate a large list of ideas for best-practice assumption documentation. More than thirty companies were represented in the call, including direct insurers, reinsurers and consulting firms. This article is the work product of the discussion written by Laurie Li and Alex Zaidlin.

Description: Many top-performing businesses aren’t just risk aware, but rather risk intelligent. Such a posture helps prepare companies for a major event and can demonstrate to a regulator or auditor that an appropriately strong control framework is in place. Better still, companies gain real strategic value from a “risk adjusted” understanding not only of their threats and vulnerabilities, but also the upside opportunities associated with various risks. It starts with having both qualitative and quantitative information to identify, assess and manage risks. Strategic risk management, at its core, is about creating value by increasing transparency and accountability, and quality of information. More than a mere compliance exercise, effective risk management enables more informed strategic decision making, increased accountability and transparency, a greater likelihood of organizational success, and – ultimately – competitive advantage, as borne out by many studies that correlate risk management and financial results.

Description: On October 30, 2015, the SOA Assumption Development and Governance Group, an informal discussion group consisting of nearly 200 interested actuaries with topics pertaining to actuarial assumption development and governance, organized an industry discussion call on end-to-end assumption documentation practices. The purpose of this call was to generate a large list of ideas for best-practice assumption documentation. More than thirty companies were represented in the call, including direct insurers, reinsurers and consulting firms. This article is the work product of the discussion written by Laurie Li and Alex Zaidlin.

Description: Following up on recent articles on claim reserves and retrospective testing, this article examines some data quality and methodology issues related to calculating LTCI claim reserves.