Wells Fargo Bank, N.a.

Eliza Fain

Prasanth Nandanuru

Jimmy Wang

Paramdeep Singh

Dilip Menon

Examples described herein relate to apparatuses and methods of detecting fraudulent activity at an automated teller machine (ATM) using a machine learning model. A method includes receiving ATM activity data indicative of one or more withdrawal transactions at one or more ATMs using a transaction card, receiving transaction data and ATM data, ingesting the transaction data and the ATM data, analyzing the ingested transaction data and the ingested ATM data using a machine learning model, determining that the ingested transaction data and the ingested ATM data indicate a likelihood of fraudulent activity using the machine learning model, and performing, using the machine learning model, one or more remedial actions based on the determined likelihood of fraudulent activity.

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San Francisco, CA, United States of America

Eliza Fain