Description: Actuarial tools now include both open and closed source software; both need a strong model governance framework to mitigate potential sources of model risk and external threats. This presentation will discuss how to develop, install and monitor a model governance framework to safeguard company modeling assets and intellectual capital.

Description: An introduction of predictive modeling techniques that are applicable to insurance industry, including generalized linear model (GLM) and classification and regression tree model(CART). Other models such as data clustering, neural network, and support vector machine (SVM), are also briefly discussed.

Description: A discussion on using the Cox Proportional Hazards Model in developing a predictive underwriting model that produces a mortality multiplier for each individual.

Description: A discussion about how many models can address the over fitting issues caused by too many variables by regularization, variable selection is still meaningful.

Description: Data analytics is changing insurance industry and will fundamentally change how we run insurance business. Actuaries could and should be on top of it and lead the change. This practical session would provide a technical overview about GLM and describe how GLM can be applied as a business tool in life insurance. The session would also focus on case-studies across different functional areas like pricing, fraud detection, underwriting and product development.

Description: Toward a Predictive Analytics Framework files

Description: Crop insurance plays an important role in mitigating food production disasters and keeping a robust food production system in the United States. Crop insurance increases stability in food and fiber production, smoothing variability which would otherwise occur because of weather patterns and changes in international trade regulations and markets. Stability increases the ability of farmers to make long-term investments that increase production efficiency and keep productive land in agriculture.

Description: Reflection on three years on the PAF section council and where we're headed next.

Description: Data used for HAT at 2020 PA 4.0 event.

Description: This article provides an overview of activities that should be considered by an actuary when validating a predictive model. It describes several components to consider when validating a predictive model and provides an examination of various methodologies that can be implemented in the validation process.