Abstract: Aspects of the disclosure relate to using machine learning to simulate an interactive voice response system. A computing platform may establish a virtual assistant session with a mobile banking application executing on a mobile device, which may include authenticating at least one authentication credential associated with an online banking account. The computing platform may receive an assistance message from the mobile device requesting assistance. Using a machine learning model, the computing platform may identify an intent of the assistance message. The computing platform may generate a response message based on the intent of the assistance message. The computing platform may send the response message and one or more commands directing the mobile device to output an audio response file based on the response message to the mobile device, which may cause the mobile device to convert the response message into the audio response file and output the audio response file.

Abstract: Aspects of the disclosure relate to using machine learning to simulate an interactive voice response system. A computing platform may establish a virtual assistant session with a mobile banking application executing on a mobile device, which may include authenticating at least one authentication credential associated with an online banking account. The computing platform may receive an assistance message from the mobile device requesting assistance. Using a machine learning model, the computing platform may identify an intent of the assistance message. The computing platform may generate a response message based on the intent of the assistance message. The computing platform may send the response message and one or more commands directing the mobile device to output an audio response file based on the response message to the mobile device, which may cause the mobile device to convert the response message into the audio response file and output the audio response file.

Abstract: Aspects of the disclosure relate to using machine learning to simulate an interactive voice response system. A computing platform may receive user interaction information corresponding to interactions between a user and enterprise computing devices. Based on the user interaction information, the computing platform may identify predicted intents for the user, and may generate hotkey information based on the predicted intents. The computing platform may send the hotkey information and commands directing the mobile device to output the hotkey information. The computing platform may receive hotkey input information from the mobile device. Based on the hotkey input information, the computing platform may generate a hotkey response message. The computing platform may send, to the mobile device, the hotkey response message and commands directing the mobile device to convert the hotkey response message to an audio output and to output the audio output.

Abstract: Aspects of the disclosure relate to using machine learning to simulate an interactive voice response system. A computing platform may receive user interaction information corresponding to interactions between a user and enterprise computing devices. Based on the user interaction information, the computing platform may identify predicted intents for the user, and may generate hotkey information based on the predicted intents. The computing platform may send the hotkey information and commands directing the mobile device to output the hotkey information. The computing platform may receive hotkey input information from the mobile device. Based on the hotkey input information, the computing platform may generate a hotkey response message. The computing platform may send, to the mobile device, the hotkey response message and commands directing the mobile device to convert the hotkey response message to an audio output and to output the audio output.

Abstract: Aspects of the disclosure relate to using machine learning to simulate an interactive voice response system. A computing platform may establish a virtual assistant session with a mobile banking application executing on a mobile device, which may include authenticating at least one authentication credential associated with an online banking account. The computing platform may receive an assistance message from the mobile device requesting assistance. Using a machine learning model, the computing platform may identify an intent of the assistance message. The computing platform may generate a response message based on the intent of the assistance message. The computing platform may send the response message and one or more commands directing the mobile device to output an audio response file based on the response message to the mobile device, which may cause the mobile device to convert the response message into the audio response file and output the audio response file.

Abstract: An apparatus for electronic transmission via a virtual persona is provided. The apparatus may include a receiver. The receiver may be located at a first entity's mobile device. The receiver may be configured to receive a request to transmit an electronic transmission. The apparatus may include a processor. The processor may be located at the first entity's mobile device. The processor may be configured to identify a plurality of visible virtual personas. The plurality of visible virtual personas may be associated with a plurality of other mobile devices. Each of the plurality of virtual personas may be associated with a displayable image and/or characteristic set. The identification may be based on information received from a third party fraud detection network. The information may include location information associated with the plurality of other devices. The location information may be currently exploited by the third party fraud detection network.

Abstract: Tools for photograph billpay tagging of a digital image are provided. The digital image may correspond to a portion of text positioned upon a medium. The text may correspond to billpay information. The tool may define a graphical reference frame for the digital image. The tool may identify a set of glyphs within the text. The tool may translate a portion of the digital image into an estimated group of characters. The translated portion of the digital image may correspond to at least a part of the set of glyphs. The tool may tag the portion of the digital image with a tag. The tag may be coupled with a billpay input field. The billpay input field may be populated. The billpay input field may be populated with the group of estimated characters. The bill input field may be populated based on the coupling.