Ranging over different lines of business and applications, these are some of my topics of interest for independent research projects:
- Analyses on personal health data gathered by wearables; what indicators and variables are missing to construct a better understanding of the user?
- How can actuarial practices (such as generalized linear models or loss triangles) be extended to other data-science and machine learning motivations such as predictive modeling for sales and subscription to music or entertainment services? Surely, the analyses an actuary performs on geographical regions can be applicable to defining the granularity and data organization for a study on consumption of a service like Netflix based on geographical region, time of day, and characterization and profiling of the user. Motivations from this may extend to catering suggestions for relevant content, and providing better data for machine learning methods.
- What models can we apply to "free-to-play" game purchases, player interaction, and retention? In what ways, qualitatively and quantitatively, does retention and game culture integrity translate to estimated vs. actual profits? Primarily, I'm interested in the emergence of "free-to-play" games and how some turn incredible profits by sticking to the social integrity of the game (i.e. inability to pay for a competitive advantage within the game; aka "not pay-to-win"). The potency of this business model is that it encourages players to make multiple, continued purchases. Consumers hate to be forced to subscribe, but somehow removing that requirement and making it optional, along with game economy balance, gives players enough incentive to commit to those purchases.
- Seasonality/cyclic pattern of the flu. Severity and Frequency analyses, as well as geographic categorization. Data from the CDC. Development to ultimate based on my idea that everyone or most people get the flu once per season, if no flu immunization shot.
- Prediction analytics for sports outcomes or similar phenomena.
- Stock market applications of actuarial methods.
- More to be added to this list as ideas come to mind.