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William & Mary Students Win CSBS Data Analytics Competition

A student team from William & Mary has won the 2023 Data Analytics Competition, the Conference of State Bank Supervisors announced today.  

The annual Data Analytics Competition engages CSBS with the academic community. This year’s competition, held virtually on May 4, challenged students to develop a data analytics model that examines the potential impact on banks from the recent rapidly rising interest rate environment and to provide insights on how they should prepare. 

“The CSBS Data Analytics Competition is a great way for college students to apply data analytics solutions to real-world banking questions,” said Tom Siems, CSBS chief economist and creator of the annual competition. “The competition effectively combines both research on banking with data analytics and introduces students to potential careers in banking and financial regulation.”

CSBS selected William & Mary students Jamie Kim, Andrew Lagattuta, Clay McCollum and Fei Wu as the top team. Led by faculty advisor Dr. Rachel Chung, the team used an Artificial Intelligence neural network model to analyze the historical relationships between the Federal Funds Rate with banks’ earnings and predict the impact of earnings during periods of rising interest rates. As the first-place winners, the William & Mary team will collect $5,000.

Students from Kennesaw State University placed second. Led by faculty advisor Dr. Sherry Ni, team members Namazbai Ishmakhametov, Askhat Yktybaev and Mohammad Naser tested several hypotheses using multivariate panel regression models to conduct stress tests on the banking system and evaluate resilience to interest rate shocks. The team will collect $2,500.  

A team from Carnegie Mellon University, led by Dr. Gabriela Gongora-Svartzman and comprised of students Cleon Demiao Sun, Manikandan Palaniappan, Niharika Patil, Yilin Lyu and Zeinab Yasmine Soumahoro, placed third. The team used elastic net regression and penalized logistic regression to select features and then a generalized linear model for performance outcomes to predict bank failure. The team will receive $1,500.

Yunhan Zhang, Yihan (Nathen) Bian and Qiaojuan (Tina) Tu represented a Georgetown University team led by faculty advisor Dr. Nakul R. Padalkar and used logistic regression, decision trees, random forest and gradient boosting models to investigate the resilience of banks in a rapidly rising interest rate environment. The team will receive $1,000. 

CSBS’s Data Analytics Task Force provides oversight and direction for the annual CSBS Data Analytics Competitions, which began in 2019. More information can be found on the CSBS website:

For more information on CSBS visit

Media Contact: Susanna Barnett, [email protected], 202.407.7156 

Twitter: @CSBSNews 

The Conference of State Bank Supervisors (CSBS) is the national organization of bank regulators from all 50 states, American Samoa, District of Columbia, Guam, Puerto Rico and U.S. Virgin Islands. State regulators supervise roughly three-quarters of all U.S. banks and a variety of non-depository financial services. CSBS, on behalf of state regulators, also operates the Nationwide Multistate Licensing System to license and register non-depository financial service providers in the mortgage, money services businesses, consumer finance and debt industries. 

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