Bank of America Corporation

Prabhakar Rao Bolleddu

Carl Parziale

Jessica Boettner

Kenneth M Fischer

Lakshmipriya Varada

Ashok Kumar

Aspects of the disclosure relate to monitoring an automatic teller machine (ATM) network and determining anomalous fault behavior in the ATM network. A system may determine historical fault volumes in the ATM network and generate a time-series model of the fault volumes. The system may predict future fault volumes based on the generated time-series model. Based on the predicted future fault volumes and actual future fault volumes, the system may determine anomalous fault behavior and perform a remedial action associated with the ATM fault code determined from anomalous observed fault volumes.

Identification of anomalies in an automatic teller machine (ATM) network

Aspects of the disclosure relate to monitoring an automatic teller machine (ATM) network and determining anomalous fault behavior in the ATM network. A computing device may determine historical fault volumes in the ATM network and generate a time-series model of the fault volumes. The computing platform may predict future fault volumes based on the generated time-series model. Based on the predicted future fault volumes and actual future fault volumes, the computing platform may determine anomalous fault behavior. The time-series model may be based on exogenous factors associated with ATM network operations.

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Plano, TX, United States of America

Prabhakar Rao Bolleddu