Description: Brief comment from the Editor about the 17th Actuarial Research Conference in 1982.

Description: Up to now, the main aim of credibility theory has been to provide statistical models which allow for estimating [net] risk premiums appropriately. In this note, a simple credibility model based on the percentile principle is introduced. It turns out that there are close connections between the resulting credibility premiums and statistical tolerance limits.

Description: This paper shows that credibilty theory and Parametric Empirical Bayes [PEB] theory are closely related and applies PEB theory to credibility applications for normal and other familiar probability distributions.

Description: This paper uses the power series expansions in relation to the annuity coefficients presented in the 1987 Actuarial Mathematics textbook. From the Actuarial Research Clearing House ARCH 1987 Vol. 1.

Description: This paper proposes a model for the incurred but not reported - IBNR- claims of an insurance company. This model will be fit to third party automobile bodily injury claims for which the months and years of occurrence of the accident are available. From the Actuarial Research Clearing House 1990 VOL. 1

Description: The method in this paper is to derive expressions for mortality between integral values of age underlying the typical approximations employed, and to compare such expressions. Annuity and life reserve formulas are compared. Discussions of the paper are included.

Description: The purpose of this paper is to set forth a mathematical technique which in the author's experience has proved useful in testing the tax implications of various management actions.

Description: Different mortality projection methodologies are utilized by actuaries across applications and practice areas. As a result, the MIM Advisory Group developed a single framework to serve as a consistent base for practitioners in projecting mortality improvement.

Description: Discussion of Capital Market Modeling techniques

Description: 1) Vision of the applications and development of data analytics in life insurance industry in Asia; 2) How big is the pie and what are the current obstacles insurers are facing; 3) Utilization of data and analytics target operating models as a competitive advantage, with focus on future readiness, controls, efficiency and effectiveness; 4) Potential roadmap ahead: a) Assessment of the current state of maturity levels of data and analytics initiatives; b) Identification of technology and competency gaps; c) Establishment of data integration and management process within BUs, alignment of advanced analytics tools across departments, with centralized data governance, technology structure and decision making framework; d) Definition of criteria and metrics to measure key outcomes and business value added. 5) Case study on agency behavior management: a practical example on how data analytics is being used in practice: (a) key business objectives: improve agent behaviors and maximize productivity with the lowest possible compensation costs; (b) data collection and current state assessment; (c) detailed predictive modeling process, modeling outcomes, and business implications; (d) implementation and monitoring process.