Abstract: Various embodiments described herein are generally directed to techniques for managing fraud rules and generating authentication directions according to location data from one or more client devices. Embodiments may include using a payment server informed by a client device application to manage and/or apply fraud rules for transactions. In embodiments, fraud rules may be managed based on location data provided by a client device application and/or location data associated with at least one transaction system. In some embodiments, fraud rules may be managed based on location data provided by multiple client device applications and/or location data associated with at least one transaction system. In some embodiments, rules may be managed for an individual authorization request according to information from at least one client device application and location data for a transaction system associated with the authorization request.

Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of receiving input data from at least one external data aggregator; utilizing a trained machine learning algorithm to generate a database of known queries; receiving subsequent input data from the at least one external aggregator; automatically updating the database of known queries associated with the plurality of users; utilizing the trained machine learning algorithm to perform a cross-reference analysis to determine a presence of a data record within the database of known queries; dynamically removing the data record from the database of known queries; utilizing the trained machine learning algorithm to predict a trigger associated with the presence of the at least one data record; and instructing a computing device to initiate a verification of the presence of the at least one data record.

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: Aspects discussed herein may relate to techniques for authenticating a user using transaction-based authentication questions. The transaction-based authentication questions may be provided to the user. The user may provide audible responses to the transaction-based authentication questions that may be captured by a smart device, such as an always on listening device. Authentication of the user may be based on voice analysis of the audible responses to the transaction-based authentication questions and/or based on the answers to the transaction-based authentication questions.

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: A device may receive an authorization request, associated with a transaction made by a user device as part of a checkout procedure of a website, that includes a virtual transaction card identifier of a virtual transaction card that is being used for the transaction, and a first merchant identifier for a merchant associated with the website. The device may perform a first authorization procedure to determine whether the first merchant identifier, included in the authorization request, satisfies a threshold level of similarity with a second merchant identifier associated with a request to generate the virtual transaction card that occurred prior to receiving the authorization request. The device may determine whether to forego a second authorization procedure based on a result of the first authorization procedure, and cause an authorization response, that includes an indication of whether the transaction is approved, to be provided to another device associated with the merchant.

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, the present disclosure provides an exemplary method that may include steps of obtaining a permission to monitor a plurality of activities executed within the second computing device; continuously monitoring the plurality of activities executed within the second computing device for a predetermined period of time; receiving an indication of an incoming interaction session within the predetermined period of time; automatically verifying at least one session interaction parameter associated with the incoming interaction session to identify the incoming interaction session as a suspect interaction session; determining when a duration of time associated with the suspect interaction session meets or exceeds a predetermined duration threshold; utilizing a trained detection machine learning model to model a confidence value associated with the suspect interaction session; identifying at least one future activity subsequent to the suspect interaction session; and automatically instructing the firs

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: A fraud detection system may identify a suspected fraudulent transaction based on one or more criteria. The transaction may be associated with a user. Based on identifying a suspected fraudulent transaction, the fraud detection system may receive augmented reality data from an augmented reality device of the user. The fraud detection system may determine, based on the augmented reality data, whether the transaction is fraudulent, and may take an action based on the determination.

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: 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: An exemplary system, method, and computer-accessible medium for providing a financial account recommendation to person(s) can include receiving a transaction history for the person(s) associated with a first financial account, determining first rewards information based on the transaction history, accessing database(s) containing rewards rates for a plurality of second financial accounts, determining second rewards information for a particular second financial account of the plurality of second financial accounts based on the transaction history, and providing the financial account recommendation to the person(s) to one of (i) keep the first financial account or (ii) switch to the second financial account based on a comparison of the first rewards information to the second rewards information.

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 system includes an application programming interface, a database, and a server. The application programming interface can make recommendations to a user at a point of sale to display a recommended payment method from a set of payment methods associated with the user. The database can store past transactions for each payment method in the set of payment methods. The server can generate payment analytics by analyzing the past transactions in the database for each payment method. The server can determine potential benefits available to the user. The server can determine the recommended payment method by using the payment analytics and maximizing the potential benefits available to the user.

Abstract: A method includes obtaining a first dataset associated with a first set of classes and a second dataset associated with a second set of classes, where the first and second datasets share features. The method also includes creating an aggregated dataset having a quality score for the second set of classes that satisfy a first threshold. Creating the aggregated dataset includes determining a first and second set of clusters based on the first and second datasets. The method includes determining a distance based on a record of the first set of clusters and a second record of the second set of clusters in a feature space. The method further includes determining a set of analysis scores based on the distance and generating an indication for a set of records associated with the set of analysis scores based on the set of analysis scores satisfying a second threshold.

Abstract: Methods and systems disclosed herein describe customizing searching. Search queries may be customized according to a user's preferences. A user may emphasize or indicate that additional weight should be given to one or more terms in a search query. Terms that are weighted higher may have a larger impact on the results that are returned in response to the search query. In addition to changing the terms in a search query, a user may provide a weight for each term. Each term in a search query may be weighted to varying degrees, giving a user more control over the results that are returned. The weights may be used with machine learning techniques to generate a vector representation of a search query. The vector representation of the search query may be compared with vector representations of search objects to determine results that match the search query.

Abstract: Aspects described herein may allow transactions to be authenticated based on images taken at the transaction site. For example, a computing device may decline a transaction request based on a first category of the transaction indicated in the category information violates a transaction category restriction of the user account. The computing device may send, to a user device associated with the user account, an instruction to upload one or more photos that depict a physical environment where the transaction is requested. If the photos indicate the requested transaction belongs to another category that does not violate the transaction category restriction, the system may approve the transaction based on the photos.

Abstract: Methods, systems, and apparatuses are described herein for authenticating access to an account using questions which allow users to provide textual information about transactions conducted by an account. A machine learning model may be trained to predict the guessability of merchants. A request for access to an account may be received, and transaction data for that account may be received. An authentication question may be presented. For example, a user may be prompted to list places they have shopped recently. A user response comprising text data may be received. The text data may be processed to identify one or more merchants. If the one or more merchant(s) are represented in the transaction data, the machine learning model may be used to determine the guessability of the one or more merchants. An authentication score may be determined based on the guessability, and access to the account may be provided.

Abstract: Methods, systems, and apparatuses are described herein for improving the accuracy of authentication questions using transaction limitations provided by users. A request for access to an account associated with a user may be received from a user device. An account restrictions database may be queried to determine one or more transaction rules associated with the account. The one or more transaction rules may have been created by the user and indicate limitations on financial transactions that may be performed via the account. An authentication question may be generated that is associated with a violation of the one or more transaction rules. The authentication question may be provided to the user device, and a response to the authentication question may be received. Access to the account may be provided to the user device based on the response.