Description: Virtual - Session 8D: An Application of Clustering Approaches in Value-Based Care

Description: As health insurance self-funding becomes more popular among smaller group sizes, risk is evolving for the MGUs, stop loss writers, and reinsurers that cover them. Assessing more small groups at lower attachment points means rethinking traditional stop loss underwriting techniques.

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: Toward a Predictive Analytics Framework files

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: This practical session would provide a technical overview about GLM techniques and describe how GLM can be applied as a business tool in solving business problems in life insurance. The session would also focus on recent real-world case-studies across different functional areas like pricing, fraud detection, underwriting and product development.

Description: This practical session would provide a technical overview about Generalized Linear Model (GLM) and describe how GLM can be applied as a business tool in life insurance. The session would also focus on case-studies sharing across different functional areas such as pricing, fraud detection, underwriting, product development and other real-world applications.

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: Data used for HAT at 2020 PA 4.0 event.

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.