Student Work

Predicting Bank License Revocation

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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.
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  • E-project-101716-093448
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Year
  • 2016
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Date created
  • 2016-10-17
Location
  • Moscow
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