Challenge and Reward

The Actuarial Case Competition is Bruin Actuarial Society's largest event of Winter Quarter. Teams of students work together on a case provided by a sponsor of the Society and present their findings and recommendations. The cases are representative of professional actuaries' real-life work and provide a valuable experience for students to use their mathematical knowledge and technical skills beyond the classroom. Teams that advance to the final round have the opportunity to present in front of a panel of judges from firms throughout the region and compete for recognition and a cash prize.

Case Competition 2020

In the 2020 Case Competition, students served as actuaries at a group dental insurance provider founded in 2012. As the company was growing rapidly, they are concerned about their loss ratio. Teams were asked to develop a retention probability model and to utilize it to develop a strategy to meet the company's loss ratio goals. An excerpt from the assignment is as follows:

"You are an actuary at Block Dental. Block Dental was founded in 2012 and has been aggressive with trying to win new business in order to get their name in the industry. Currently, they feel comfortable with their position, but are now worried about their loss ratio. Upper management would like to try to decrease that loss ratio from around 88% to 70% in three years. Your manager wants you to focus on reducing the in-force business’ loss ratio by enforcing a stricter renewal policy. You are to determine the rate increases for the different types of groups in order to reach that lower loss ratio."

You can find the case files here.

First-Place Winners
Team 28 (UCLA)
Wilson Yu
Yunqi Shi
Boyang Wan
Hengyuan Qi
Team 25 (UCLA) Team 19 (UCSB) Team 11 (UCSB)
Bryan Le Joshua Chen Justin Wang
Joey Pai Michael Kwok John Tran
Priscilla Tsai Max Reedy Christina Chyi
Yuka Kozakai Ian Low Kumann Liu
Presentation Presentation Presentation
Memorandum Memorandum Memorandum

Past Competitions

In the 2019 Case Competition, students served as P&C pricing actuaries, developing a auto insurance rater in Excel and evaluating the results of the output of a generalized linear model (GLM) based on historical data. An excerpt from the assignment follows:

"You are an actuarial analyst at Bruins Mutual, a mid-sized insurance company writing automobile and homeowners insurance in 20 states. Currently, all policy rating is done on the system, but the company would also like to set up an Excel rater to accommodate premium audits. Since the existing rating algorithm was developed few years ago and relatively simple, the company would like to re-evaluate the effectiveness of the rating structure. Your team is responsible for running a Generalized Linear Model on selected rating variables for each coverage."

You can find the case files here.

First-Place Winners
Team 19 (UCLA)
Sri Chavva
Gabby Ignacio
Jazz Laosirichon
Eva Mars
Team 18 (UCLA) Team 08 (UCSB) Team 10 (UCSB)
Elisa Bong Kimmy Bao Ethan Chiu
Yupeng Chen Wenjing Li Simon Huang
Kelvin Christian Ming Yi Jordan Jang
Jiahao Huang Sam Zhang Huaiyu Zhang
Presentation Presentation Presentation
Memorandum Memorandum Memorandum

In the 2018 Case Competition, students took on the role of retirement actuary, performing an experience study to revise a pension plan's outdated retirement rate assumptions based on employee data from 2012 to 2017. An excerpt from the assignment follows:

"You are an up and coming actuarial student at AOFF Consulting, Inc. and part of the consulting team for Climate Enterprises (CliEnt), an important local client who manages a medium sized pension plan. The pension plan was started decades ago, but has been closed to new entrants since before 2012. The pension plan provisions are included in the Appendix.

Over the last few years, the pension plan has experienced some unexpected demographic movement. Your superiors suspect this may be due to the assumptions being outdated, and have asked you to perform an experience study."

You can find the case files here.

First-Place Winners
Team 5
Kristi Intara
Ellen Mortensen
Sarah Peña
Cassandra Tai
Team 6 Team Cal Team UCI
Austin Hunt Annie Chen Cavan Donohoe
Natalie Joseph Joan Dai Melissa Licari
Jianzhen Wang Daniel He Elina Liu
Jiahui Zhou Roy Kim Umar Shafi
Presentation Presentation Presentation
Memorandum Memorandum Memorandum

The 2017 Case Competition tasked students with pricing 2018 health insurance premiums based on historical membership and claims data. An excerpt from the assignment follows:

"You are an actuary at BruinCare, a health insurance company, and need to price individual health insurance premiums for 2018. BruinCare has been a part of the ACA exchanges for the past three years, providing healthcare coverage and services in regions 1 through 3 in California. The state government intends to rebrand these rating regions in order to create renewed interest in healthcare enrollment. Please provide and refer to your new region names throughout the case study.

Your job will be to use historical 2016 data to project for 2018. You will need to use your company’s 2016 base data to calculate a set of premiums by projecting 2018 membership and claims to generate a representative single claims PMPM (Per-Member-Per-Month). This value will be used to calculate the Index Rate, Market Adjusted Index Rate, and Plan Adjusted Index Rate. Once you have your Plan Adjusted Index Rate, you will apply area factors, age calibration, and the age curve to arrive at your final individual premiums by region. [An attached] Excel workbook ... is the pricing model in which you will complete all of your calculations."

You can find the case file here and the pricing model here.

First-Place Winners
Team 5
Timothy Hinh
Brian Hsu
Alisa Nguyen
Luna Xu
Team 6 Team UCSB
Trace Bechter Stephanie Lee
Henry Han Daniel Rodon
Jerry He Conor Shannon
Tianxiang Yuan Johnny Trinh
Presentation Presentation
Memorandum Memorandum

Kaiser Permanente's 2016 Bruin Actuarial Society Case Competition asked students to develop rating models and forecast rate increases, loss ratios, and financial results for various segments of a health insurer's business as the Affordable Care Act took hold. An excerpt follows:

"You are an Actuary at The University of California Health Insurance Company (“UCHIC” or “UC” for short).Your company is domiciled in Westwood, California. UC is a large health insurance company providing health insurance to large group employers, i.e., employers with more than 50 employees...

Your Actuarial analysis, at a minimum, should show the following:

  1. Develop large group rating models and forecast rate increases, loss ratios and financial results for UC’s large group business considering the early renewals of UC’s small-large groups and then the remaining large groups that did not renew early. Do not forget that you promised Leadership a financial review of extending the offer that groups “could not refuse” to all small-large group renewals in 2016.
  2. Develop small group rating models from the consultant’s assumptions and then calculating loss ratios and financial results considering the existing UC groups that will become small groups and the new business UC can expect from entering the small group market
  3. Develop individual rating models from the consultant’s assumptions and then calculating loss ratios and financial results
  4. For each of the new business lines, consider different membership assumptions based on the consultant’s advice
  5. Summarize the projected financial results from the time periods 2016 and 2017 and from each business line"

You can find the full case file here and a workbook of supporting assumptions here.

First-Place Winners
Team 2
Annie Thornton
Serena Wang
Greta Xiong
James Xu
Team 14 Team UCSB Team Cal
Brian Hsu Miriam Hickman James Han
Jenny Hu Ryan Shen Karen Kan
Deborah Kim Daniel Pon Wendy Tan
Brandon Yu Gary Wang Alex Xiao
Presentation Presentation Presentation
Memorandum Memorandum Memorandum

The Third Annual Bruin Actuarial Society Case Competition tasked students with determining whether a public entity operating an aging fleet of vehicles should buy the newest optional safety features for its automobiles. An excerpt follows:

"Your actuarial firm, The Bruinators, provides property/casualty actuarial consulting services to UCLA. UCLA has a large fleet of aging autos, half of which will need to be replaced next year. UCLA is aware that over the past several years there has been a lot of innovation related to auto safety, and they have asked the Bruinators to investigate whether the new cars they purchase should include some of these features and also whether they should add safety devices to the half of their fleet that will not be replaced...

UCLA is self-insured for auto and workers’ compensation exposures. This means that rather than purchasing coverage from an insurance company UCLA directly pays for costs associated with auto accidents and work-related injuries to employees...

You will be expected to give a presentation that makes recommendations regarding what safety features UCLA should add to existing vehicles and should be purchased for the half of the fleet that is being replaced. You should address what you think will be the key concerns of the evaluators from each department. There may be some issues that you are not able to quantify to your satisfaction. That’s okay. Make an educated guess, and state any additional assumptions you needed to make. You are expected to be factual and unbiased; you have no investment in whether or not UCLA purchases any of the auto safety features.

At a minimum you will need to forecast ultimate costs associated with auto claims under two scenarios, one in which UCLA does not purchase any of the potential safety features and one in which they purchase the features you are recommending. If you recommend not purchasing any of the potential safety features, then you should explain why. You do not need to be concerned with the basic cost of each new car, only the incremental cost associated with any safety features you are recommending."

You can find the case file here, background information here, and the data file here.

First-Place Winners
Team 13
Marshall Dong
Colin Ji
Ryan Kim
Brian Tat
Serena Wang
Team 9 Team 6 Team 8
Christian Ciabattoni Brandon Chioy Lilian Lee
Jonathan Wang Jing Feng Calvin Liu
Vince Yang Will Griffith Ying Liu
Tianxiang Yuan Xuemin He John Yang
Vincent Yang Rachel Yang