Fraud Detection: Using Artificial Intelligence to Identify Suspicious Persons Over the Phone

Aksman, Daniel Vladimir; Fitzgibbon, Zackary R.; Kneedler, Alec Tallmadge

Student Work

Fraud Detection: Using Artificial Intelligence to Identify Suspicious Persons Over the Phone Public

Banks in Russia have experienced a rise in client complaints regarding fraudulent monetary transfers made under the influence of social engineering. In collaboration with students at the Financial University in Moscow, the team used artificial intelligence to identify a speaker’s emotional state using acoustic markers. Three models were developed and tested with eleven datasets to enhance accurate identification. Based on the results, the authors provide recommendations on the most salient vocal features and classification models to aid with fraud detection.

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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