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- All Subjects: Actuarial
- All Subjects: COVID
- All Subjects: group insurance
- Creators: Zicarelli, John
- Creators: Gilkey, Gina
- Creators: Grimaldi, Lisa
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Status: Published
Since the beginning of the COVID-19 pandemic, telemedicine usage in America has experienced extreme peaks as a method of maintaining social distancing for medical staff and patients. While there have been numerous significant positive effects from increasing this practice, there are also significant risks to be explored. Patients and physicians have been navigating new technology, new protocols, and new dynamics at a high rate. Doctors using telemedicine are required to rely more heavily on their judgment with less data than usual to support their hypotheses. This results in a wide variety of potential complications that can be detrimental to patients and physicians alike. Though negative outcomes are not nearly the majority, it is clear that for telemedicine to function at its fullest capacity, the limitations of its technology must be defined and communicated. A survey was distributed to physicians currently practicing telemedicine to understand more about the usage increase in telemedicine and the incidence rates of telemedicine-related complications. The results showed that although the impact of telemedicine has been largely positive, there certainly are risks that must be considered and prepared for. Thus, it is the responsibility of healthcare systems to ensure that their policies are current and appropriate in proportion to their usage of telemedicine to better protect and prepare patients and doctors for this new frontier of medicine.
The objective of this study is to build a model using R and RStudio that automates ratemaking procedures for Company XYZ’s actuaries in their commercial general liability pricing department. The purpose and importance of this objective is to allow actuaries to work more efficiently and effectively by using this model that outputs the results they otherwise would have had to code and calculate on their own. Instead of spending time working towards these results, the actuaries can analyze the findings, strategize accordingly, and communicate with business partners. The model was built from R code that was later transformed to Shiny, a package within RStudio that allows for the build-up of interactive web applications. The final result is a Shiny app that first takes in multiple datasets from Company XYZ’s data warehouse and displays different views of the data in order for actuaries to make selections on development and trend methods. The app outputs the re-created ratemaking exhibits showing the resulting developed and trended loss and premium as well as the experience-based indicated rate level change based on prior selections. The ratemaking process and Shiny app functionality will be detailed in this report.