Description: With many complex regulatory changes on the horizon as well as pressures to ensure model accuracy from auditors, regulatory requirements and new actuarial standards of practice, the importance of robust model validation is coming to the forefront of actuaries’ minds. What was previously a day-two task for many companies is becoming just as important as model development! In this session, you will hear from those that have been deeply involved in building model validation frameworks and tools in responses to regulatory changes GAAP Long Duration Targeted Improvements (“LDTI”) and Principles Based Reserves (“PBR”).

Description: Claims are insurers deepest and richest transactional data – yet we rarely unleash the full potential of this data. In this session, we will discuss potential sources and attributes of claims data, traditional approaches alongside new analytic techniques and how to integrate models into existing claims management processes. During this session, the presenters will discuss different areas of how machine learning can drive significant value unleashing the potential in claims data, these include data capture, claims management and workflow design as well as behaviour prediction. In addition, the audiences will also have opportunity to learn different use cases of how claims models taking advantage of machine learning, such as foreign death fraud detection and critical illness triage.

Description: The author describes how his company was able to benefit from an application of risk theory.

Description: Authored by a MIB Solutions team of Tom Rhodes, Stuart Klugman, Marianne Purushotham and Stacy Gill, the report summarizes the results of a study on the application and adoption of credibility theory within the life insurance and annuity industry. In addition to the report, numerical examples related to the application of credibility to company mortality and lapse data are provided in the four Excel files. This excel spreadsheet is a numerical example relating to the application of Credibility for lapses by policy for limited fluctuation. Please see the SOA website research section for the full report on Credibility Theory Practices.

Description: Authored by a MIB Solutions team of Tom Rhodes, Stuart Klugman, Marianne Purushotham and Stacy Gill, the report summarizes the results of a study on the application and adoption of credibility theory within the life insurance and annuity industry. In addition to the report, numerical examples related to the application of credibility to company mortality and lapse data are provided in the four Excel files. This excel spreadsheet is a numerical example relating to the application of Credibility for mortality - Limited Fluctuation Method. Please see the SOA website research section for the full report on Credibity Theory Practices.

Description: Article Society Seminars by Adams in The Actuary, February 1979, Volume 13, Number 2

Description: 1996 Valuation Actuary Symposium. In this teaching session on liability modeling, the panelists discussed the key aspects of identifying and gathering the data required to construct models, the model building process including objectives and considerations, and the modeling process from the standpoint of policyholder and company behaviors.

Description: The problem of estimation of a tabular survival model from complete samples is considered from a Bayesian approach. If a life test involves a large cohort group, then data is typically given as a grouped data set. The survival function St is usually estimated by the moment estimator. We approximate the joint prior distribution of the unknown unconditional failure probabilities by a Dirichlet distribution, and then use a linear relationship between St and the conditional survival probabilities to obtain a Bayes estimator of St.

Description: This paper is written totally under present Indian conditions, but keeping an eye on the future, when there will be number of insurers, and this model can be applied to any condition where a number of insurers already exist. The purpose of this paper is to attempt to measure, from the point of view of a potential life insurance policyholder, the quality of the insurers and the variability between them so that it will be helpful for potential policyholders to choose their insurers according to their requirements.

Description: This paper develops a theory for the valuation of some kinds of interest sensitive cash flows. A process is derived which takes as input, assumptions about the capital markets and policy holder behaviour, and produces as output interest and decrement assumptions which can be used for conventional actuarial discounting. The methodology is illustrated using some idealized, but tractable, models of conventional non-par whole life insurance. The method is also applied to a simple Universal Life plan. The paper concludes by considering some of the problems encountered when applying the ideas to more practical problems.