GENERATING VALIDITY CLASSIFICATIONS FOR DIGITAL COMMUNICATIONS UTILIZING A MACHINE LEARNING MODEL
The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating validity notifications including validity classifications utilizing a communication validation machine learning model. In particular, in one or more embodiments, the disclosed systems receive a digital image including a digital communication. Further, in some embodiments, the communication validation system utilizes a communication validation machine learning model to analyze the digital image and determine a validity classification. In one or more embodiments, the communication validation system also generates and provides a notification including the validity classification to a client device.
1 . A method comprising:
receiving, via a client device, a digital image comprising a digital communication;
utilizing a communication validation machine learning model to analyze the digital communication and generate a validity classification for the digital communication; and
providing a notification to the client device indicating the validity classification.
2 . The method of claim 1 , wherein the validity classification indicates a categorization of genuine communication or fraudulent communication.
3 . The method of claim 1 , wherein the validity classification indicates a certification that the digital communication originated from a specific institution.
4 . The method of claim 1 , wherein the validity classification of the digital communication indicates that the digital communication is fraudulent, further comprising:
utilizing the communication validation machine learning model to determine one or more indications of invalidity in the digital image;
generating instructions for addressing the digital communication based on the digital image; and
providing the one or more indications of invalidity and the instructions for addressing the digital communication in the notification to the client device.
5 . The method of claim 1 , further comprising:
extracting one or more user features corresponding to the client device; and
utilizing the communication validation machine learning model to further analyze the one or more user features to determine the validity classification of the digital communication.
6 . The method of claim 1 , further comprising:
receiving user input indicating a phone number associated with the digital communication or an email address associated with the digital communication; and
utilizing the communication validation machine learning model to further analyze the phone number associated with the digital communication or the email address associated with the digital communication to determine the validity classification of the digital communication.
7 . The method of claim 1 , further comprising iteratively training the communication validation machine learning model to utilizing a loss function and a ground-truth dataset of digital images of communications and corresponding ground-truth validity classifications.
8 . A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:
receiving, via a client device, a digital image comprising a digital communication;
utilizing a communication validation machine learning model to analyze the digital communication and generate a validity classification for the digital communication; and
providing a notification to the client device indicating the validity classification.
9 . The non-transitory computer-readable medium of claim 8 , wherein the validity classification indicates a categorization of genuine communication or fraudulent communication.
10 . The non-transitory computer-readable medium of claim 8 , wherein the validity classification indicates a certification that the digital communication originated from a specific institution.
11 . The non-transitory computer-readable medium of claim 8 , wherein the validity classification of the digital communication indicates that the digital communication is fraudulent, wherein the operations further comprise:
utilizing the communication validation machine learning model to determine one or more indications of invalidity in the digital image;
generating instructions for addressing the digital communication based on the digital image; and
providing the one or more indications of invalidity and the instructions for addressing the digital communication in the notification to the client device.
12 . The non-transitory computer-readable medium of claim 8 , wherein the operations further comprise:
extracting one or more user features corresponding to the client device; and
utilizing the communication validation machine learning model to further analyze the one or more user features to determine the validity classification of the digital communication.
13 . The non-transitory computer-readable medium of claim 8 , wherein the operations further comprise:
receiving user input indicating a phone number associated with the digital communication or an email address associated with the digital communication; and
utilizing the communication validation machine learning model to further analyze the phone number associated with the digital communication or the email address associated with the digital communication to determine the validity classification of the digital communication.
14 . The non-transitory computer-readable medium of claim 8 , wherein the operations further comprise iteratively training the communication validation machine learning model to utilizing a loss function and a ground-truth dataset of digital images of communications and corresponding ground-truth validity classifications.
15 . A system comprising:
at least one processor; and
at least one non-transitory computer-readable storage medium storing instructions that, when executed by the at least one processor, cause the system to:
receive, via a client device, a digital image comprising a digital communication;
utilize a communication validation machine learning model to analyze the digital communication and generate a validity classification for the digital communication; and
provide a notification to the client device indicating the validity classification.
16 . The system of claim 15 , wherein the validity classification indicates a categorization of genuine communication or fraudulent communication.
17 . The system of claim 15 , wherein the validity classification indicates a certification that the digital communication originated from a specific institution.
18 . The system of claim 15 , wherein the validity classification of the digital communication indicates that the digital communication is fraudulent, further comprising instructions that, when executed by the at least one processor, cause the system to:
utilizing the communication validation machine learning model to determine one or more indications of invalidity in the digital image;
generating instructions for addressing the digital communication based on the digital image; and
providing the one or more indications of invalidity and the instructions for addressing the digital communication in the notification to the client device.
19 . The system of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the system to:
extracting one or more user features corresponding to the client device; and
utilizing the communication validation machine learning model to further analyze the one or more user features to determine the validity classification of the digital communication.
20 . The system of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the system to:
receiving user input indicating a phone number associated with the digital communication or an email address associated with the digital communication; and
utilizing the communication validation machine learning model to further analyze the phone number associated with the digital communication or the email address associated with the digital communication to determine the validity classification of the digital communication.