Bank of America Corporation

Paul Mattison

Matthew Edward Williams

Jennifer Ann Raley

Arrangements for using generative artificial intelligence models for ATM operations control are provided. In some examples, a computing platform may receive, from a plurality of ATMs, operation data. The operation data may be analyzed using a first generative artificial intelligence (AI) model to identify one or more potential issues. If an issue is identified, additional data related to the issue may be retrieved from an impacted ATM. A second generative AI model associated with the particular identified issue may be identified. The model may be executed using the additional data as inputs to identify or output a corrective action. The corrective action may be transmitted to the ATM for execution. The one or more generative AI models may be updated to continuously improve accuracy.

Generative artifical intelligence-based automated teller machine operation control

Arrangements for using generative artificial intelligence models for ATM process generation are provided. In some examples, a computing platform may receive, from at least one image or measurement capture device, dimension data associated with an ATM. The ATM may have a plurality of components arranged on a face of the ATM. The dimension data may be input to a generative artificial intelligence model and the model may be executed to output, based on the dimension data, a position or location of each ATM component relative to a reference point on the ATM. In some examples, the model may further output at least one audio script describing the location of each component. The model may output one or more translations of the at least one audio script. The computing platform may transmit or send the at least one audio script to the ATM for presentation during user interaction with the ATM.

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Charlotte, NC, United States of America

Paul Mattison