The Central Bank of Russia has revoked 20% of all bank licenses since 2012. This project sought to determine a computational method for forecasting the probability of license revocation. To do this, we compared two classification algorithms, logistic regression and random forest. Using a Random Forest classifier produced higher F1 scores than logistic regression. We recommend that Deloitte continues the development of a random forest model by investigating clustering and additional features to improve the model’s performance.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Bortell, Jacob A
• Patias, Parmenion
• Giancola, Michael Joseph
• Harding, Everett Jackson

Subject

• Industry
• Computing

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-101716-093448

Parola chiave

• Risk management
• Financial services industry--Technological innovations

Advisor

• Pavlov, Oleg V
• Balistrieri, Thomas J.

Year

• 2016

Center

• Moscow, Russia Project Center - IQP

Sponsor

• Deloitte

Date created

• 2016-10-17

luogo

• Moscow

Resource type

• Interactive Qualifying Project

Rights statement

• In Copyright