Computer systems and methods are provided for receiving a first authentication request that includes an image of an identification document. A risk value is determined using one or more information factors that correspond to the authentication request. A validation user interface that includes the image of the identification document is displayed. A risk category that corresponds to the risk value is determined using at least a first risk threshold. In accordance with a determination that the risk value corresponds to a first risk category, a visual indication that corresponds to the first risk category is displayed. In accordance with a determination that the risk value corresponds to a second risk category, a visual indication that corresponds to the second risk category is displayed.

Systems and methods for scalable biometric authentication are disclosed. In one embodiment, a method for scalable biometric authentication may include: (1) receiving, by a biometric authentication computer program executed by a computer processor, a transaction request for a transaction comprising a received biometric; (2) identifying, by the biometric authentication computer program, a subset of likely customers from a set of customers for the transaction; (3) retrieving, by the biometric authentication computer program, stored biometrics for the subset of customers; (4) identifying, by the biometric authentication computer program, one of the stored biometrics for the subset of customers that matches the received biometric; and (5) retrieving, by the biometric authentication computer program, a stored payment method for the identified stored biometric.

Disclosed are various approaches for performing biometric authentication of users using an application running on a client device. A biometric model can be trained using biometric data from a population of users. The biometric model can be used by the client application to authenticate users and can be separate from system-level biometric authentication capabilities of the client device.

A VPN servers request is transmitted from a user device to a central server. A first VPN server is received from the central server at the user device. Responsive to the user device failing to establish a first encrypted tunnel with the first VPN server, a request for another VPN server is transmitted from the user device to the central server. A second VPN server is received from the central server. A second encrypted tunnel is established with the second VPN server. An encrypted communication is obtained by encrypting a communication directed to a network server. The encrypted communication is transmitted from the user device to the VPN second server.

A biometric token is generated for a user and provided to a user-operated device. A pre-staged transaction is defined by a user and the user supplies the token for association with the pre-staged transaction. Subsequently, a user visits a transaction terminal and a new candidate token is generated from biometric attributes of the user. The candidate token is matched to the token associated with pre-staged transaction to authenticate the user and the pre-staged transaction is processed at the transaction terminal as a completed transaction.

The present disclosure generally relates to managing access to credentials. In some examples, an electronic device authorizes release of credentials for use in an operation for which authorization is required. In some examples, an electronic device causes display of one or more steps to be taken to enable an input device for user input. In some examples, an electronic device disambiguates between commands to change the account that is actively logged-in on the device and commands to cause credentials to be released from the secure element.

Computer implemented biometric methods and systems incorporate sensing biophysical phenomena, translating the phenomena into digital data and transmitting the data to a series of servers operating in an open feedback loop to generate a module. A biometric networking system can include a biometric monitoring cloud computing platform with AI/machine learning augmented models are generated to make user assessments, programs and confidence scores to the healthcare provider systems. The AI/machine learning models can be used by the biometric monitoring network to generate health-related AI processes that analyze relationships treatment techniques and outcomes. AI techniques can be used to calculate movement modeling and confidence scoring including support vector machines, neural networks, and decision trees. The biophysical phenomena may include biometric parameters based on data, such as medical history, exertion, sleep, temperature, cardiovascular events, respiratory events, and muscle and blood pH.

Apparatus and methods for proactively and preemptively communicating with a user interacting with a software application are provided. The apparatus and methods may include an artificial intelligence/machine learning communication engine monitoring and tracking a user's interactions. The apparatus and methods may include the communication engine determining if the user requires further training, if the interaction is fraudulent, and pre-empting requests for information the user may commence. The apparatus and methods may include the communication engine creating and displaying training materials for the user to complete, revoking access if fraud is present, and proactively providing information before the user requests the information.

Methods and systems for creating a verifiable digital identity are provided. The method includes obtaining a first user-generated item comprising an identifiable feature. The method also includes digitally signing the first user-generated item to generate a secure digital artifact. The method also includes uploading the secure digital artifact and the first user-generated item to an auditable chain of a public ledger. The method also includes verifying a digital identity of the user by auditing the auditable chain. The method also includes obtaining a second user-generated item generated comprising the identifiable feature. The method also includes comparing the first and second user-generated items. The method also includes uploading the second user-generated item to the public ledger when the comparing is within a threshold.

Authentication is performed based on a user narrative. A narrative, such as a personal story, can be requested during a setup process. Content, voice signature, and emotion can be determined or inferred from analyzing the narrative. Subsequently, a user can provide vocal input associated with the narrative, such as by retelling the narrative or answering questions regarding the narrative. The vocal input can be analyzed for content, voice signature and emotion, and compared with the initial narrative. An authentication score can then generated based on the comparison.