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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

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
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Description

The insurance industry is a multibillion-dollar industry, yet it lags far behind other industries like banking and big tech in its adaptation of automation. I experienced this first-hand as an intern at State Farm. I completed a project that was a massive data entry job and made it into a

The insurance industry is a multibillion-dollar industry, yet it lags far behind other industries like banking and big tech in its adaptation of automation. I experienced this first-hand as an intern at State Farm. I completed a project that was a massive data entry job and made it into a process that took clicking three buttons to finish. Although just one example, it was clear that State Farm as well as the insurance industry in general are not utilizing automation and machine learning. The adaptation of automation and machine learning will have internal and external benefits for insurance companies like increased efficiencies in business processes and increased customer satisfaction. However, to realize these external and internal benefits, companies, like State Farm, must implement an adhocratic culture where risk taking is incentivized, and companies must invest resources into their underwriting processes, rather through internal investment or an acquisition, to automate the process.

ContributorsKindopp, Archer Orvin (Author) / Bryne, Jared (Thesis director) / Schiller, Christoph (Committee member) / Department of Finance (Contributor) / School of Accountancy (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Through findings from interviews, a survey, and personally learning automation software we think automation will continue to grow in the accounting industry in the coming years. Accountants see software as something that makes them more efficient and firms are doing a good job training their employees on how to use

Through findings from interviews, a survey, and personally learning automation software we think automation will continue to grow in the accounting industry in the coming years. Accountants see software as something that makes them more efficient and firms are doing a good job training their employees on how to use these new software tools. Our interviewed accountants say that automation saves them time that can be used to work on other things. By learning Alteryx, an automation tool, we saw these time savings firsthand.

ContributorsShillingburg, Alec (Author) / DiNuto, Michael (Co-author) / Dawson, Greg (Thesis director) / Garverick, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Accountancy (Contributor)
Created2022-05
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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
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Description

Through findings from interviews, a survey, and personally learning automation software we think automation will continue to grow in the accounting industry in the coming years. Accountants see software as something that makes them more efficient and firms are doing a good job training their employees on how to use

Through findings from interviews, a survey, and personally learning automation software we think automation will continue to grow in the accounting industry in the coming years. Accountants see software as something that makes them more efficient and firms are doing a good job training their employees on how to use these new software tools. Our interviewed accountants say that automation saves them time that can be used to work on other things. By learning Alteryx, an automation tool, we saw these time savings firsthand.

ContributorsDiNuto, Michael (Author) / Shillingburg, Alec (Co-author) / Dawson, Greg (Thesis director) / Garverick, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Accountancy (Contributor) / Department of Information Systems (Contributor)
Created2022-05