Abstract: Example embodiments of systems and methods for data transmission system between transmitting and receiving devices are provided. In an embodiment, each of the transmitting and receiving devices can contain a master key. The transmitting device can generate a diversified key using the master key, protect a counter value and encrypt data prior to transmitting to the receiving device, which can generate the diversified key based on the master key and can decrypt the data and validate the protected counter value using the diversified key.

Abstract: Techniques for verifying employment of a user are provided. A financial product or service may be requested by a user. Work schedule information for the user may be determined that may identify an expected work location of the user and expected work times for the user. Location data associated with the user may be obtained and compared to the expected work location and times for the user. A confidence score of the user may be generated based on the comparison. The requested financial product or service may be provided to the user if the confidence score meets or exceeds a predetermined threshold. In this manner, employment and/or reliability may be determined for a user having no credit history.

Abstract: A card for storing both emergency information and payment information is disclosed. The card can be used by an emergency responder to retrieve emergency information for the user. The emergency information can enable the emergency responder to better render aid to the user. The card can have one or more processors, a sensor, and a memory in communication with the one or more processors and storing an application thereon. The application can cause the card to receive a request from a user device (e.g., from an emergency medical technician, or EMT) to access emergency information stored in the memory, transmit a security challenge to the user device, authenticate a received response to the security challenge from the user device, and transmit the emergency information to the user device.

Abstract: In some implementations, a system may receive, at a front-end device and from an augmented reality (AR) device associated with a user, a request to use the front-end device. The system may transmit, to the AR device, a request to access an optical sensor of the AR device. The system may receive, from the AR device, an output, from the optical sensor, that indicates a hand gesture performed by the user of the AR device. Accordingly, the system may determine, based on the hand gesture, a corresponding input key of the front-end device. The system may perform an action based on the corresponding input key.

Abstract: Systems and methods of the present disclosure include computer systems for improving data security. To do so, an authorization request associated with a user profile is received, including a time-stamp for a profile activity, a profile identifier, and a value. Application analytics data for a software application on a user device associated with the user profile is accessed, including an open event indicator indicating a time of a loading, and a close event indicator indicating a time of a termination. An open period of the software application at the time-stamp is determined based on the application open event indicator and the application close event indicator. A reduced set of fraud checks is selected and executed when the time-stamp associated with the profile activity is within the open period of the software application. A fraud determination is generated, and an authorization notification is generated based on the fraud determination.

Abstract: Embodiments of systems, methods, and devices for protecting service personnel by deploying a physical barrier are described. Further embodiments describe additional security features such as lights, sirens, cameras, electronic locks, timers, and/or notifying security personnel or local law enforcement when the system is activated.

Abstract: Methods and systems are described for verifying an identity of a user through contextual knowledge-based authentication. The system described uses contextual knowledge-based authentication. By verifying an identity of a user through contextual knowledge-based authentication, the verification is both more secure and more intuitive to the user. For example, by relying on confidential and/or proprietary information, the system may generate verification questions, the answers to which are known only by the user.

Abstract: A system may include processor(s), and memory in communication with the processor(s) and storing instructions configured to cause the system to correct ASR errors. The system may receive a transcription comprising transcribed word(s) and may determine whether the transcribed word(s) exceed associated predefined confidence level(s). Responsive to determining a transcribed word does not exceed a predefined confidence level, the system may generate a predicted word. The system may calculate a distance between numerical representations of the transcribed word and the predicted word and may determine whether the distance exceeds a predefined threshold. Responsive to determining the distance exceeds the predefined threshold, the system may determine whether at least one red flag word of a list of red flag words corresponds to a context of the transcription, and, responsive to making that determination, may classify the transcription as associated with a first category.

Abstract: An automated teller machine (ATM) may include an input component and one or more processors. The input component may be configured to detect multi-factor input associated with an account. The multi-factor input may include at least two of: a sequence of characters input via the input component, a force with which at least one character, of the sequence of characters, is input via the input component, a length of time over which at least one character, of the sequence of characters, is input via the input component, or a combination of at least two characters, of the sequence of characters, that are input concurrently via the input component. The ATM may receive the multi-factor input, validate the multi-factor input in association with the account, and selectively permit or deny access to one or more actions associated with the account based on validating the multi-factor input.

Abstract: In some implementations, a device may obtain event data relating to events involving one or more entities and one or more individuals, where the one or more entities are associated with entity categories. The device may determine, based on origin locations of the one or more individuals and locations of the one or more entities, distances between the origin locations of the one or more individuals and the locations of the one or more entities, the distances indicating travel distances of the one or more individuals to perform exchanges in the entity categories associated with the one or more entities. The device may determine, based on the event data and the distances, that a geographic area is associated with an opportunity for an entity category. The device may transmit a notification indicating the opportunity for the entity category in the geographic area.

Abstract: In some embodiments, validation of network operations related to use of a token via a token request based on entity characteristics may be facilitated. In some embodiments, a token request indicating use of a token to access an item associated with an entity may be detected, where the token is bound to one or more entity characteristics. Based on the token request, an entity identifier associated with the entity may be obtained. Using the entity identifier, one or more item characteristics of items available via the entity may be determined. Determining whether the entity satisfies the one or more entity characteristic to which the token is bound may be determined based on the one or more item characteristics. Access to the item associated with the entity may be validated based on the determination indicating that the entity satisfies the one or more entity characteristics to which the token is bound.

Abstract: Disclosed embodiments may include a system for managing assets. The system may establish a connection with a drone comprising Light Detection and Ranging (LiDAR) sensors and an image capture device. The system may receive, via the drone, image data via the LiDAR sensors and the image capture device. The system may identify, from the image data via computer vision, one or more assets, a condition of the one or more assets, and a location associated with the one or more assets. The system may generate a dynamic report comprising the one or more assets, the condition of the one or more assets, and the location associated with the one or more assets.

Abstract: The present disclosure relates to systems and method for securely entering a confidential access code into a user device. A system for allowing secure entry of a confidential access code into a user device may include one or more memories storing instructions and one or more processors configured to execute instruction to perform operations. The operations may include receiving a request for confidential access, prompting the user, via the user interface, to enter a group of inputs into a single-entry field, receiving a dummy sequence of inputs, receiving or providing an indicator signal, receiving an access sequence of inputs, parsing the group of inputs received to identify the access sequence of inputs based on the location of the indicator signal, comparing the access sequence of inputs to the confidential access code associated with the user, and granting or denying access to the confidential information based on the results.

Abstract: In some implementations, a credit decision platform may receive a credit request from an applicant and obtain domestic historical data associated with the applicant from a credit bureau device. The credit decision platform may obtain access to an email account associated with the applicant based on determining that the domestic historical data associated with the applicant is insufficient to process the credit request. The credit decision platform may identify, using one or more machine learning models, a set of email messages included in the email account that are relevant to the credit request and may analyze content included in the set of email messages to generate non-domestic historical data associated with the applicant. The credit decision platform may generate a decision on the credit request based on an estimated creditworthiness of the applicant, which may be determined based on the non-domestic historical data.

Abstract: A method may include receiving activity data associated with a user, wherein the activity data relates to online activity involving a product type, identifying the product type associated with the activity data, and predicting, based on the activity data, that the user is likely to purchase a product of the product type. The method may include generating, based on predicting that the user is likely interested in purchasing the product of the product type, an annotation to indicate that a potential transaction to purchase the product is forthcoming, and storing the annotation in a profile associated with an account of the user. The method may include detecting a transaction to purchase the product, wherein the transaction involves a payment from the account, and performing an action associated with a fraud analysis of the transaction based on the annotation.

Abstract: In some implementations, a regression prediction platform may obtain one or more feature sets related to an impending code change, wherein the one or more feature sets may include one or more features related to historical code quality for a developer associated with the impending code change or a quality of a development session associated with the impending code change. The regression prediction platform may provide the one or more feature sets to a machine learning model trained to predict a risk associated with deploying the impending code change based on a probability that deploying the impending code change will cause breakage after deployment and/or a probability that the impending code change will cause support issues after deployment. The regression prediction platform may generate one or more recommended actions related to the impending code change based on the risk associated with deploying the impending code change.

Abstract: Disclosed embodiments accelerate web form completion based on email address analytics. An email address can be input with respect to a web form and identified. The email address can be parsed into a username and a domain name and analyzed. A value of a web form field can be determined based on data extracted from the username, domain name, or both. The determined value can then be employed to automatically complete a corresponding web form field Values for additional fields can be computed based on the determined value alone or combined with data from other sources. User input and interaction with a web form can be monitored and used as a basis to dynamically complete additional fields, alter fields, or clear field values.

Abstract: Systems and methods for reducing network traffic associated with a service. In some aspects, the systems and methods provide for using a first machine learning model to process a data stream for a communication with a user and generate a confidence score regarding whether to assign a communication suppression flag to the user account. Based on the confidence score not exceeding a first threshold, a communication suppression flag is not assigned to the user account. Based on the confidence score being between first and second thresholds, at least a portion of the data stream is extracted based on temporal proximity to a time stamp of an intent of the user to not receive further communications. Using a second machine learning model, the extracted portion of the data stream is processed to generate a prediction regarding whether to assign a communication suppression flag to the user account.

Abstract: A device may provide a verification indicator to a device associated with a website. The verification indicator may be associated with verifying access to the website. The device may detect that the verification indicator has been associated with code associated with the website based on processing the code. The device may provide a script to the device. The script may be included in the code. The script may be associated with monitoring operations of the website. The device may receive data related to the operations. The device may analyze the data using a model. The model may be associated with making a prediction related to at least one of: a value to be received via the website, or traffic associated with the website. The device may perform one or more actions related to the website based on a result of the analyzing.

Abstract: A computer vision card reader and/or point of sale device is described. The device is configured to sense when a user inserts a card into a card reader and to determine when a user departs or is about to depart from the device without retrieving the card. The device may issue an audible or visible alert to the user, reminding the user to retrieve the card. The device may additionally send a notification to a mobile device associated with the user that reminds the user that he has left a card at the point of sale. In some embodiments, message sent to the user contains a code and, upon entry of the code, the point of sale or card reader device returns the card to the user.