Utilizing machine-learning models to determine take-over scores and intelligently secure digital account features
The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing machine-learning models to determine take-over scores and intelligently provide or limit access to account features. In particular, in one or more embodiments, the disclosed systems can train and utilize digital security machine-learning models to generate a take-over score indicating a likelihood that the request to access the secure digital account is unauthorized activity. Based on the determining that the take-over score satisfies a take-over threshold, the disclosed systems can allow access to the secure digital account by providing secure account information but prohibit access to a subset of account features.
1 . A computer-implemented method comprising:
receiving, via a client device, a request to access a secure digital account;
determining one or more extracted features associated with the client device;
generating, utilizing a digital security machine-learning model, a take-over score based on the one or more extracted features;
upon determining that the take-over score satisfies a take-over threshold, allowing access to the secure digital account by providing, for display via the client device, a first selectable option for a first feature, and a second selectable option for a second feature;
in response to receiving, from the client device, a first selection of the first selectable option, executing the first feature based on the take-over score and based on the first feature being a first type;
in response to receiving, from the client device, a second selection of the second selectable option, prohibiting execution of the second feature based on the take-over score and the second feature being a second type; and
providing, on the client device, a notification that the second feature is unavailable.
2 . The computer-implemented method of claim 1 , wherein determining the one or more extracted features associated with the client device comprises:
identifying an IP address associated with the client device; and
determining a time zone associated with a location corresponding to the IP address.
3 . The computer-implemented method of claim 1 , wherein determining the one or more extracted features associated with the client device comprises:
determining a number of secure accounts the client device attempted to access; or
determining a number of failed logins from an IP address associated with the client device.
4 . The computer-implemented method of claim 1 , wherein:
the first feature is a balance inquiry feature, and executing the first feature based on the take-over score comprises providing an account balance for display on the client device; and
the second feature is a transfer feature, and prohibiting executing of the second feature based on the take-over score comprises prohibiting the client device from accessing the transfer feature.
5 . The computer-implemented method of claim 1 , further comprising:
identifying a first threshold based on the first feature being the first type, and wherein executing the first feature based on the take-over score comprises comparing the take-over score to the first threshold; and
identifying a second threshold based on the second feature being the second type, and wherein prohibiting executing of the second feature based on the take-over score comprises comparing the take-over score to the second threshold.
6 . The computer-implemented method of claim 1 , further comprising:
determining one or more historical client device features associated with the secure digital account;
determining one or more device comparison features by comparing the one or more historical client device features with the one or more extracted features associated with the client device; and
wherein the take-over score is based at least in part on the one or more device comparison features.
7 . The computer-implemented method of claim 6 , wherein:
at least one historical client device feature comprises a historical IP address associated with the secure digital account:
at least one extracted feature associated with the client device comprises a current IP address associated with the client device; and
at least one device comparison feature comprises a distance between a first location associated with the historical IP address and a second location associated with the current IP address.
8 . A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause a computer system to:
receive, from a client device, a request to access a secure digital account;
determine one or more extracted features associated with the client device;
generate, utilizing a digital security machine-learning model, a take-over score based on the one or more extracted features;
upon determining that the take-over score satisfies a take-over threshold, allowing access to the secure digital account by providing, for display via the client device, a first selectable option for a first feature, and a second selectable option for a second feature;
in response to receiving, from the client device, a first selection of the first selectable option, execute the first feature based on the take-over score and based on the first feature being a first type;
in response to receiving, from the client device, a second selection of the second selectable option, prohibit execution of the second feature based on the take-over score and the second feature being a second type; and
provide, on the client device, a notification that the second feature is unavailable.
9 . The non-transitory computer-readable medium of claim 8 , wherein determining the one or more extracted features associated with the client device comprises:
identifying an IP address associated with the client device; and
determining a time zone associated with a location corresponding to the IP address.
10 . The non-transitory computer-readable medium of claim 8 , wherein determining the one or more extracted features associated with the client device comprises:
determining a number of secure accounts the client device attempted to access; or
determining a number of failed logins from an IP address associated with the client device.
11 . The non-transitory computer-readable medium of claim 8 , wherein:
the first feature is a balance inquiry feature, and executing the first feature based on the take-over score comprises providing an account balance for display on the client device; and
the second feature is a transfer feature, and prohibiting executing of the second feature based on the take-over score comprises prohibiting the client device from accessing the transfer feature.
12 . The non-transitory computer-readable medium of claim 8 , further comprising instructions that, when executed by the at least one processor, cause the computer system to:
identify a first threshold based on the first feature being the first type, and wherein executing the first feature based on the take-over score comprises comparing the take-over score to the first threshold; and
identify a second threshold based on the second feature being the second type, and wherein prohibiting executing of the second feature based on the take-over score comprises comparing the take-over score to the second threshold.
13 . The non-transitory computer-readable medium of claim 8 , further comprising instructions that, when executed by the at least one processor, cause the computer system to:
determine one or more historical client device features associated with the secure digital account;
determine one or more device comparison features by comparing the one or more historical client device features with the one or more extracted features associated with the client device; and
wherein the take-over score is based at least in part on the one or more device comparison features.
14 . The non-transitory computer-readable medium of claim 13 , wherein:
at least one historical client device feature comprises a historical IP address associated with the secure digital account:
at least one extracted feature associated with the client device comprises a current IP address associated with the client device; and
at least one device comparison feature comprises a distance between a first location associated with the historical IP address and a second location associated with the current IP address.
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, from a client device, a request to access a secure digital account;
determine one or more extracted features associated with the client device;
generate, utilizing a digital security machine-learning model, a take-over score based on the one or more extracted features;
upon determining that the take-over score satisfies a take-over threshold, allowing access to the secure digital account by providing, for display via the client device, a first selectable option for a first feature, and a second selectable option for a second feature;
in response to receiving, from the client device, a first selection of the first selectable option, execute the first feature based on the take-over score and based on the first feature being a first type;
in response to receiving, from the client device, a second selection of the second selectable option, prohibit execution of the second feature based on the take-over score and the second feature being a second type; and
provide, on the client device, a notification that the second feature is unavailable.
16 . The system of claim 15 , wherein determining the one or more extracted features associated with the client device comprises:
identifying an IP address associated with the client device; and
determining a time zone associated with a location corresponding to the IP address.
17 . The system of claim 15 , wherein determining the one or more extracted features associated with the client device comprises:
determining a number of secure accounts the client device attempted to access; or
determining a number of failed logins from an IP address associated with the client device.
18 . The system of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the system to:
identify a first threshold based on the first feature being the first type, and wherein executing the first feature based on the take-over score comprises comparing the take-over score to the first threshold; and
identify a second threshold based on the second feature being the second type, and wherein prohibiting executing of the second feature based on the take-over score comprises comparing the take-over score to the second threshold.
19 . The system of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the system to:
determine one or more historical client device features associated with the secure digital account;
determine one or more device comparison features by comparing the one or more historical client device features with the one or more extracted features associated with the client device; and
wherein the take-over score is based at least in part on the one or more device comparison features.
20 . The system of claim 19 , wherein:
at least one historical client device feature comprises a historical IP address associated with the secure digital account:
at least one extracted feature associated with the client device comprises a current IP address associated with the client device; and
at least one device comparison feature comprises a distance between a first location associated with the historical IP address and a second location associated with the current IP address.