Matching Items (8)
Filtering by

Clear all filters

133403-Thumbnail Image.png
Description
The use of generalized linear models in loss reserving is not new; many statistical models have been developed to fit the loss data gathered by various insurance companies. The most popular models belong to what Glen Barnett and Ben Zehnwirth in "Best Estimates for Reserves" call the "extended link ratio

The use of generalized linear models in loss reserving is not new; many statistical models have been developed to fit the loss data gathered by various insurance companies. The most popular models belong to what Glen Barnett and Ben Zehnwirth in "Best Estimates for Reserves" call the "extended link ratio family (ELRF)," as they are developed from the chain ladder algorithm used by actuaries to estimate unpaid claims. Although these models are intuitive and easy to implement, they are nevertheless flawed because many of the assumptions behind the models do not hold true when fitted with real-world data. Even more problematically, the ELRF cannot account for environmental changes like inflation which are often observed in the status quo. Barnett and Zehnwirth conclude that a new set of models that contain parameters for not only accident year and development period trends but also payment year trends would be a more accurate predictor of loss development. This research applies the paper's ideas to data gathered by Company XYZ. The data was fitted with an adapted version of Barnett and Zehnwirth's new model in R, and a trend selection algorithm was developed to accompany the regression code. The final forecasts were compared to Company XYZ's booked reserves to evaluate the predictive power of the model.
ContributorsZhang, Zhihan Jennifer (Author) / Milovanovic, Jelena (Thesis director) / Tomita, Melissa (Committee member) / Zicarelli, John (Committee member) / W.P. Carey School of Business (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This expository thesis explores the financial health and actuarial analysis of a particular solution for those seeking stability and security in their golden years: the CCRC industry. A continuing care retirement community, or CCRC, is a comprehensive project and campus that offers its residents a full spectrum of care from

This expository thesis explores the financial health and actuarial analysis of a particular solution for those seeking stability and security in their golden years: the CCRC industry. A continuing care retirement community, or CCRC, is a comprehensive project and campus that offers its residents a full spectrum of care from independent living, to assisted living, to skilled nursing. After reading this paper, any person with no prior knowledge of a continuing care retirement community should gain a firm understanding of the background, risks and benefits, and legislative safeguards of this complex industry. Financially, a CCRC operates in some aspects similar to long-term care (LTC) insurance. However, CCRCs provide multiple levels of care operations while maintaining a pleasant, engaging community environment where seniors can have all their lifestyle needs met. The expensive and complex operations of a CCRC are not without risk: the industry has seen marked periods of bankruptcy followed by increasing and changing regulatory oversight. Thus, CCRCs require a periodic actuarial analysis and report, among array of other legislative safeguards against bankruptcy. A CCRC's insolvency or inability to meet its obligations can be catastrophic and inflict suffering and damages not only to its residents but also their friends and families. With seniors historically being one of the most vulnerable demographic groups, it is absolutely essential that an all-encompassing care facility continues to exist and fulfill its contractual promises by maintaining sound actuarial practices and financial health. This thesis, in addition to providing an exposition of the background and functions of the CCRC, describes the existing actuarial and financial studies and audits in practice to ensure sound governance and the quality of life of CCRC residents.
ContributorsTang, Julie (Author) / Milovanovic, Jelena (Thesis director) / Hassett, Matthew J. (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
148076-Thumbnail Image.png
Description

Through research, interviews, and analysis, our paper provides the local community with a resource that offers a comprehensive collection of insight into the Mirabella at ASU Life Plan Community and the projected impact it will have on the City of Tempe and Arizona State University.

ContributorsStephens, Corey Christopher (Co-author) / Dicke, George (Co-author) / Anand, Rohan (Co-author) / Sadusky, Brian (Thesis director) / Schiller, Christoph (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Sandra Day O'Connor College of Law (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
148008-Thumbnail Image.png
Description

Through research, interviews, and analysis, our paper provides the local community with a resource that offers a comprehensive collection of insight into the Mirabella at ASU Life Plan Community and the projected impact it will have on the City of Tempe and Arizona State University.

ContributorsAnand, Rohan (Co-author) / Dicke, George (Co-author) / Stephens, Corey (Co-author) / Sadusky, Brian (Thesis director) / Schiller, Christoph (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

An examination of various reserving methods and their application in commercial auto insurance. Seeks to answer two questions: Which is the best model, out of the Chain Ladder, Mack Chain Ladder, Munich Chain Ladder, Clark's LDF and Clark's Cape Cod methods? Which loss basis, paid or incurred, yields better reserves?

ContributorsLindgren, Connor (Author) / Zicarelli, John (Thesis director) / Milovanovic, Jelena (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-12
165134-Thumbnail Image.png
Description
A factor accounting for the COVID-19 pandemic was added to a generalized linear model to more accurately predict unpaid claims. COVID-19 has affected not just healthcare, but all sectors of the economy. Because of this, whether or not an automobile insurance claim is filed during the pandemic needs to be

A factor accounting for the COVID-19 pandemic was added to a generalized linear model to more accurately predict unpaid claims. COVID-19 has affected not just healthcare, but all sectors of the economy. Because of this, whether or not an automobile insurance claim is filed during the pandemic needs to be taken into account while estimating unpaid claims. Reserve-estimating functions such as glmReserve from the “ChainLadder” package in the statistical software R were experimented with to produce their own results. Because of their insufficiency, a manual approach to building the model turned out to be the most proficient method. Utilizing the GLM function, a model was built that emulated linear regression with a factor for COVID-19. The effects of such a model are analyzed based on effectiveness and interpretablility. A model such as this would prove useful for future calculations, especially as society is now returning to a “normal” state.
ContributorsKossler, Patrick (Author) / Zicarelli, John (Thesis director) / Milovanovic, Jelena (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05
165923-Thumbnail Image.png
Description

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

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.

ContributorsGilkey, Gina (Author) / Zicarelli, John (Thesis director) / Milovanovic, Jelena (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05
Description
This report describes the technology, benefits, and deployment of autonomous vehicles and how they are expected to impact the insurance industry, specifically collision coverage policies. A pure premium trend analysis is done to come up with a realistic prediction of how the frequency and severity of vehicle collisions will change

This report describes the technology, benefits, and deployment of autonomous vehicles and how they are expected to impact the insurance industry, specifically collision coverage policies. A pure premium trend analysis is done to come up with a realistic prediction of how the frequency and severity of vehicle collisions will change over time. Two additional scenarios are done to address the fact that there is still uncertainty surrounding the timing of the implementation of AVs. Lastly, the risks that come with AVs are discussed along with potential risk mitigation strategies.
ContributorsMullenmeister, Morgan (Author) / Zhou, Hongjuan (Thesis director) / Milovanovic, Jelena (Committee member) / Zicarelli, John (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of International Letters and Cultures (Contributor)
Created2022-12