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: 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: 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”).