Abstract: Disclosed embodiments may include a system for determining trusted devices. The system may receive data corresponding to a plurality of users. The system may receive, via a plurality of user devices associated with the plurality of users, a respective request to conduct a plurality of transactions. The system may generate, via an MLM and based on the data, trust scores associated with the plurality of users and the plurality of user devices, wherein each trust score indicates a probability that a user device, of the plurality of user devices, is associated with a user of the plurality of users. The system may determine whether each trust score of a plurality of trust scores exceeds a predetermined threshold. Responsive to determining a trust score of the plurality of trust scores exceeds the predetermined threshold, the system may conduct fraud prevention action(s) with respect to a corresponding user device and user.

Abstract: Disclosed embodiments may include a system for determining trusted devices. The system may receive data corresponding to a plurality of users. The system may receive, via a plurality of user devices associated with the plurality of users, a respective request to conduct a plurality of transactions. The system may generate, via an MLM and based on the data, trust scores associated with the plurality of users and the plurality of user devices, wherein each trust score indicates a probability that a user device, of the plurality of user devices, is associated with a user of the plurality of users. The system may determine whether each trust score of a plurality of trust scores exceeds a predetermined threshold. Responsive to determining a trust score of the plurality of trust scores exceeds the predetermined threshold, the system may conduct fraud prevention action(s) with respect to a corresponding user device and user.

Abstract: A device may receive a merchant query including first merchant data associated with a first merchant. The first merchant data may be provided, as input, to a merchant matching model associated with a merchant data structure, the merchant matching model having been trained to determine a measure of confidence that input merchant data corresponds to an existing merchant in the merchant data structure. The device may receive, as output from the merchant matching model, a measure of confidence that the first merchant data corresponds to a second merchant, the second merchant being associated with second merchant data stored in the merchant data structure. The device may also determine, based on the measure of confidence, that the first merchant corresponds to the second merchant. Based on the determination, the device may obtain the second merchant data from the merchant data structure and perform an action based on the second merchant data.

Abstract: The disclosed embodiments provide systems and methods for providing real-time warnings to merchants for data breaches. For example, the system may include one or more memory devices storing instructions and one or more processors configured to perform operations consistent with this disclosure. The operations may include collecting and storing transaction authorization requests from one or more merchants. The transaction authorization requests may include a virtual account number associated with an account, the virtual account number being previously bound to a merchant and reusable only for the bound merchant. The operations may further include detecting an event at the bound merchant based on, for example, a transaction authorization request having a mismatch between a transacting merchant and the bound merchant. The operations my further include communicating notification of the event through a communication interface with the bound merchant.

Abstract: Disclosed embodiments may include a system for determining trusted devices. The system may receive data corresponding to a plurality of users. The system may receive, via a plurality of user devices associated with the plurality of users, a respective request to conduct a plurality of transactions. The system may generate, via an MLM and based on the data, trust scores associated with the plurality of users and the plurality of user devices, wherein each trust score indicates a probability that a user device, of the plurality of user devices, is associated with a user of the plurality of users. The system may determine whether each trust score of a plurality of trust scores exceeds a predetermined threshold. Responsive to determining a trust score of the plurality of trust scores exceeds the predetermined threshold, the system may conduct fraud prevention action(s) with respect to a corresponding user device and user.

Abstract: A device may receive a merchant query including first merchant data associated with a first merchant. The first merchant data may be provided, as input, to a merchant matching model associated with a merchant data structure, the merchant matching model having been trained to determine a measure of confidence that input merchant data corresponds to an existing merchant in the merchant data structure. The device may receive, as output from the merchant matching model, a measure of confidence that the first merchant data corresponds to a second merchant, the second merchant being associated with second merchant data stored in the merchant data structure. The device may also determine, based on the measure of confidence, that the first merchant corresponds to the second merchant. Based on the determination, the device may obtain the second merchant data from the merchant data structure and perform an action based on the second merchant data.

Abstract: The disclosed embodiments provide systems and methods for providing real-time warnings to merchants for data breaches. For example, the system may include one or more memory devices storing instructions and one or more processors configured to perform operations consistent with this disclosure. The operations may include collecting and storing transaction authorization requests from one or more merchants. The transaction authorization requests may include a virtual account number associated with an account, the virtual account number being previously bound to a merchant and reusable only for the bound merchant. The operations may further include detecting an event at the bound merchant based on, for example, a transaction authorization request having a mismatch between a transacting merchant and the bound merchant. The operations my further include communicating notification of the event through a communication interface with the bound merchant.

Abstract: A device may receive a merchant query including first merchant data associated with a first merchant. The first merchant data may be provided, as input, to a merchant matching model associated with a merchant data structure, the merchant matching model having been trained to determine a measure of confidence that input merchant data corresponds to an existing merchant in the merchant data structure. The device may receive, as output from the merchant matching model, a measure of confidence that the first merchant data corresponds to a second merchant, the second merchant being associated with second merchant data stored in the merchant data structure. The device may also determine, based on the measure of confidence, that the first merchant corresponds to the second merchant. Based on the determination, the device may obtain the second merchant data from the merchant data structure and perform an action based on the second merchant data.

Abstract: The disclosed embodiments provide systems and methods for providing real-time warnings to merchants for data breaches. For example, the system may include one or more memory devices storing instructions and one or more processors configured to perform operations consistent with this disclosure. The operations may include collecting and storing transaction authorization requests from one or more merchants. The transaction authorization requests may include a virtual account number associated with an account, the virtual account number being previously bound to a merchant and reusable only for the bound merchant. The operations may further include detecting an event at the bound merchant based on, for example, a transaction authorization request having a mismatch between a transacting merchant and the bound merchant. The operations my further include communicating notification of the event through a communication interface with the bound merchant.

Abstract: The disclosed embodiments provide systems and methods for providing real-time warnings to merchants for data breaches. For example, the system may include one or more memory devices storing instructions and one or more processors configured to perform operations consistent with this disclosure. The operations may include collecting and storing transaction authorization requests from one or more merchants. The transaction authorization requests may include a virtual account number associated with an account, the virtual account number being previously bound to a merchant and reusable only for the bound merchant. The operations may further include detecting an event at the bound merchant based on, for example, a transaction authorization request having a mismatch between a transacting merchant and the bound merchant. The operations my further include communicating notification of the event through a communication interface with the bound merchant.

Abstract: A device may receive a merchant query including first merchant data associated with a first merchant. The first merchant data may be provided, as input, to a merchant matching model associated with a merchant data structure, the merchant matching model having been trained to determine a measure of confidence that input merchant data corresponds to an existing merchant in the merchant data structure. The device may receive, as output from the merchant matching model, a measure of confidence that the first merchant data corresponds to a second merchant, the second merchant being associated with second merchant data stored in the merchant data structure. The device may also determine, based on the measure of confidence, that the first merchant corresponds to the second merchant. Based on the determination, the device may obtain the second merchant data from the merchant data structure and perform an action based on the second merchant data.

Abstract: A device may receive a merchant query including first merchant data associated with a first merchant. The first merchant data may be provided, as input, to a merchant matching model associated with a merchant data structure, the merchant matching model having been trained to determine a measure of confidence that input merchant data corresponds to an existing merchant in the merchant data structure. The device may receive, as output from the merchant matching model, a measure of confidence that the first merchant data corresponds to a second merchant, the second merchant being associated with second merchant data stored in the merchant data structure. The device may also determine, based on the measure of confidence, that the first merchant corresponds to the second merchant. Based on the determination, the device may obtain the second merchant data from the merchant data structure and perform an action based on the second merchant data.

Abstract: A device may receive a merchant query including first merchant data associated with a first merchant. The first merchant data may be provided, as input, to a merchant matching model associated with a merchant data structure, the merchant matching model having been trained to determine a measure of confidence that input merchant data corresponds to an existing merchant in the merchant data structure. The device may receive, as output from the merchant matching model, a measure of confidence that the first merchant data corresponds to a second merchant, the second merchant being associated with second merchant data stored in the merchant data structure. The device may also determine, based on the measure of confidence, that the first merchant corresponds to the second merchant. Based on the determination, the device may obtain the second merchant data from the merchant data structure and perform an action based on the second merchant data.