Technical Skills & Analytical Problem Solving
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Quantum Actuary：Reshaping Insurance Cognition
This article will mainly explore the quantum characteristics in some insurance phenomena. By using the quantum theory, this article will aim to revolutionize traditional insurance thinking, reshape the insurance cognition, and explore the new paths for modern actuarial science. -
Comparison of Risk Adjustment Programs—California Medicaid Managed Care Versus CMS Medicare Advantage, PART II
Risk Adjustment (RA) is a key component for CMS Medicare Advantage program and California Medicaid Managed Care program. While both RA programs follow generally accepted basic principles, their underlying methodologies and assumptions are quite different. Due to recent events, such as COVID-19 Public Health Emergency and Medicaid redetermination delay and restart, it adds complexity to Risk Adjustment. This is a hot topic in the industry and has significant impact to health plans. Keeping current with Risk Adjustment program changes and understanding the commonalities and differences of these two government Risk Adjustment programs is important to our health actuaries. This article compares and contracts these two risk adjustment programs’ methodology and assumptions as well as special considerations due to serving different populations. This is Part II of the two articles on this topic. -
Comparison of Risk Adjustment Programs—California Medicaid Managed Care Versus CMS Medicare Advantage, PART I
Risk Adjustment (RA) is a key component for CMS Medicare Advantage program and California Medicaid Managed Care program. While both RA programs follow generally accepted basic principles, their underlying methodologies and assumptions are quite different. Recent events, such as COVID-19 Public Health Emergency and Medicaid redetermination delay and restart, have added complexity to Risk Adjustment. This is a hot topic in the industry and has significant impact to health plans. Keeping current with Risk Adjustment program changes and understanding the commonalities and differences of these two government Risk Adjustment programs is important to our health actuaries. This article compares and contrasts these two risk adjustment programs’ methodology and assumptions as well as special considerations due to serving different populations. -
Emerging Topics Community Update
The article contains a description of the Emerging Topics Community. The focus of the article is what is a community, what makes the Emerging Topics Community special, and benefits of the Community. Included after the discussion on the community are ways to get involved and be a part of the community. -
Meet Hybrid Data: A Blend of Alternative and Traditional Data. A Case Study to Construct an Improved Inflation Index
In the following article, I introduce the concept of “hybrid data,” a combination of alternative and traditional data, which I illustrate through an example on inflation, to be of better value than considering purely a traditional data or alternative data source alone. We present a case where we use alternative data from Zillow, to improve upon the Consumer Price Index (CPI), and thus create an index that is more pertinent to consumers and investors alike. -
Reproducible Research
This article summarizes use of programming collaboration tools and source and version control (SVC) to make research products reproducible. -
Deep Learning in Segregated Fund Valuation: Part 2
This article is the second part of an article that appeared in April 2022 on the Emerging Topics Community webpage. It will discuss the data preparation, hyperparameter tuning and selection, and the training and testing process of the deep learning models. To reach the final conclusions, the article will continue to compare the projected cash flow results from LSTM and LSTM-Attn with those from the traditional method, and evaluate the time series generations of interest rates and equity returns by WGAN and TCN-GAN -
The Probability Principle of Group Testing: The Full-Scale Nucleic Acid Testing in Tianjin
On January 9 2022, a full-scale nucleic acid testing in Tianjin was launched. Over 10 millions of people were tested with the results announced within 2 days. The speedy efficiency was partly due to group testing with 10 persons per group. With this background, the aim of this article is to explain the probabilistic principle underlying group testing. To make the expository vivid, some numerical results and figures were provided using R language, a popular software in actuarial science and statistics. -
Deep Learning in Segregated Fund Valuation: Part I
Segregated Fund is a special investment fund to provide capital appreciation with embedded insurance features. The traditional methodology to estimate the capital reserve and pricing of contracts goes to Monte-Carlo based stochastic models due to its complexity. Recent research has introduced a deep learning model, Long Short-Term Memory (LSTM), to help cash flow projection for a Segregated Fund in its whole lifetime horizon. In this paper three new deep learning models are presented: Long Short-Term Memory with attention (LSTM-ATTN) to estimate the liability reserve and pricing Segregated Fund contracts, Wasserstein Generative Adversarial Network (WGAN) for stock return forecasting and Temporal Convolutional Network on GAN (TCN-GAN) for interest rate time series generation. As an example, the cash flow projection and Economic Capital for Segregated Fund portfolio are used to compare deep learning models against traditional models in terms of accuracy and computation efficiency. -
Transforming Group Underwriting Using Artificial Intelligence and Machine Learning
A review of opportunities for using machine learning and artificial intelligence in group health underwriting including cost predictors and predicting behavior and decisions.
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