Matching Items (6)
Filtering by
- All Subjects: Actuarial
- All Subjects: Entrepreneurship
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 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
Catastrophe events occur rather infrequently, but upon their occurrence, can lead to colossal losses for insurance companies. Due to their size and volatility, catastrophe losses are often treated separately from other insurance losses. In fact, many property and casualty insurance companies feature a department or team which focuses solely on modeling catastrophes. Setting reserves for catastrophe losses is difficult due to their unpredictable and often long-tailed nature. Determining loss development factors (LDFs) to estimate the ultimate loss amounts for catastrophe events is one method for setting reserves. In an attempt to aid Company XYZ set more accurate reserves, the research conducted focuses on estimating LDFs for catastrophes which have already occurred and have been settled. Furthermore, the research describes the process used to build a linear model in R to estimate LDFs for Company XYZ's closed catastrophe claims from 2001 \u2014 2016. This linear model was used to predict a catastrophe's LDFs based on the age in weeks of the catastrophe during the first year. Back testing was also performed, as was the comparison between the estimated ultimate losses and actual losses. Future research consideration was proposed.
ContributorsSwoverland, Robert Bo (Author) / Milovanovic, Jelena (Thesis director) / Zicarelli, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The goal of this project is to gain market research insight into the handcrafted goods industry and apply this knowledge towards a business plan for a small crafts business: Creations by Songbird. We accomplish this goal by conducting primary and secondary research on the crafts selling industry to see who the target customer is and what their habits are. First, we conduct a literature review looking into the background of some known crafts sales platforms. We discover several consistent trends in product differentiation, retail price calculation, and search engine optimization that we will apply to our business plan. Next, we conduct primary market research in the form of observations, customer and business owner interviews, and surveys. We learn that Instagram is a widely used marketing tool and that Etsy and crafts shows are popular sales channels. Using the results of our research we conclude that the our target customers are women ages 18-24 and 50-59 who attend crafts shows several times per year and occasionally browse Etsy. Many of these women enjoy objects that are vintage style and on average they spend less than $50 per item. Applying the industry and market knowledge gleaned from our research we create a business plan that outlines a price/cost breakdown, marketing plan, and sales plan for Creations by Songbird. We plan to utilize Instagram as our main marketing tool and will sell records via crafts shows and Etsy. Based on our estimates, we conclude that Creations by Songbird will be a profitable business.
ContributorsWood, Sara (Co-author) / Ehmann, Victoria (Co-author) / Gray, Nancy (Thesis director) / Trujillo, Rhett (Committee member) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor) / W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
After having worked in the legal field for two years, I began to notice a pattern with clients. Several clients had an unrealistic view of the court system regarding trial proceedings. Oftentimes, I would come across clients that were perplexed by the idea of disclosing witnesses and exhibits to the opposing party before trial. They seemed to believe that evidence was only meant to be disclosed at the time of trial, so as to surprise the opposing side. This is just one of the many distorted ideas that several people have come to me with. I can see that clients feel upset and overwhelmed by how the reality of court differs from the court that they had been imagining. These patterns in client questions and realizations began my thinking of how to better raise awareness to Americans regarding realistic dealings in the courtroom. My desire to find a means to help people unfamiliar with the legal system better understand the rules of the court, paired with my love for card games, led me to create Judge and Jury, a card game about the legal system. Judge and Jury is a game that is meant to simplify concepts of the legal system through playing cards. Each rule in the game corresponds with real-life court rules and is meant to allow people to play out "court trials' through each round of the game. The correlations between the game rules and real-life court rules are subtle to keep players engaged and entertained. The subtleness allows players to grasp legal concepts without feeling overwhelmed. Game Website: https://judgeandjurygame.weebly.com/
ContributorsHomewood, Alexa (Author) / Eaton, John (Thesis director) / Wood, Robert (Committee member) / Department of Management and Entrepreneurship (Contributor) / W.P. Carey School of Business (Contributor) / Sandra Day O'Connor College of Law (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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 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
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 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