Abstract: In various embodiments, a system, method, and computer readable medium (collectively, the “System”) for authenticating a mobile device configured to initiate payments is provided. The System may be configured to perform operations and/or steps comprising receiving, by the processor and in a secure environment, a secret element. The secret element may be transmitted to the processor (e.g., the issuer system) via a payment terminal. The System may further comprise comparing, by the processor and in the secured environment, the secret element to an issuer element. The issuer element may be linked with a flag that is associated with the transaction account. Moreover, the issuer element may be a data module that corresponds to be is not equal to the secret element. The System may also comprise authorizing, by the processor, a transaction initiated by the mobile device in response to the comparing being a satisfactory comparison.

Abstract: Transaction account holders are able to attach additional data to a transaction in concert with the transaction being initiated, prior to the merchant posting the transaction. Transaction account holders do not have to wait and/or opt for an external service provider to assist with the compiling and/or attaching of data at a later point in time (e.g., after the merchant posts the transaction). Transaction account holders may upload and access electronic receipts associated with a transaction authorization almost immediately after the sale and/or authorization of the transaction.

Abstract: At least some embodiments are directed to an entity classification system receives informational data associated with an entity. The informational data includes sentences associated with the entity. The entity classification system utilizes a first machine learning model to determine a first contextual meaning among words of a sentence associated with the entity based on a first word embedding technique, and determines at least one category associated with the entity based at least in part on the first contextual meaning. The entity classification system utilizes a second machine learning model to determine a second contextual meaning shared by a set of sentences based on a second embedding technique, and determines a subcategory of the category associated with the entity based at least in part on the second contextual meaning. The entity classification system generates an output including the category and subcategory associated with the entity.

Abstract: A system may identify a purchase transaction request from a merchant application and generate an in-app payment cryptogram for the purchase transaction request based on a limited use payment credential (LUPC). The in-app payment cryptogram may be provided to the merchant application. The merchant application may transmit the in-app payment cryptogram to a merchant computing device. A request may be received from a payment network to update the LUPC. A security library may be executed to determine that the client device is secure. The execution of the security library may generate a device attestation response, and the device attestation response is transmitted to the payment network. An updated LUPC may be received from the payment network.

Abstract: A system may receive a request for access to a first variable. The request may include a requested action and a variable identifier for the first variable. The request may also have a syntax that is incompatible with first data storage format. The system may parse the request to capture the variable identifier from the request. The system may also look up a location of the first variable in a catalog using the variable identifier. The location of the first variable may include the first data storage format. The system may generate a query to access the first variable. The syntax of the query may be compatible with the first data storage format. The system may then submit the query to access the first data storage format. The query may be configured to complete the requested action.

Abstract: The system comprises approving a credit application during a single http session, transmitting an encoded secure token to a web-client participating in the http session, receiving from the mobile communications device the secure token, and transmitting the transaction account data to the mobile communications device, in response to the receiving the secure token. The system may further comprise the mobile communications device decoding the secure token.

Abstract: At least some embodiments are directed to a prediction system of software objects. The prediction system predicts a first aspect of a user profile utilizing a categorization machine learning model and a user activity profile, the user profile and the user activity profile are associated with a user. The user activity profile comprises a plurality of values associated with demographics and historical activity data of the user. The prediction system predicts a software object associated with the user profile utilizing an optimization machine learning model, the first aspect of the user profile, and a second aspect of the user profile. The software object is optimized with respect to at least one competitive interest between the user associated with the user profile and an entity associated with the software object. The prediction system outputs the software object to a client computing device of the user.

Abstract: Systems and methods of improving the operation of a transaction network and transaction network devices are disclosed. An online purchase autofill plugin includes various modules and engines. The fields of online forms may be identified and the fields of online forms may be automatically filled. The user experience may be improved, and data security enhanced so that the transaction network more properly functions according to approved parameters, such as protecting the integrity of sensitive data.

Abstract: A system for instant qualification cross channel offer targeting is disclosed. The system may receive a plurality of personally identifiable information (PII) elements from at least one of a customer device or an affiliate system. The system may determine a credit authorization state in response to the PII element. The system may receive a first request to generate an offer from at least one of the customer device or the affiliate system. The system may generate the offer in response to an offer optimization model, the credit authorization state, and the first request to generate an offer. The system may hash the plurality of PII elements and determine a unique hash based on the plurality of PII elements. The system may associate the unique hash to the offer and store the offer as offer data.

Abstract: The method includes receiving historical data from a first data source; analyzing the historical data for a desired characteristic; determining a representative value for the desired characteristic of the historical data; determining a first data expectation for the historical data based on the representative value; transmitting the first data expectation to a first data recipient; receiving first incoming data from the first data source; analyzing the desired characteristic of the first incoming data; determining a first incoming data value for the desired characteristic for the first incoming data; comparing the first incoming data value and the representative value; determining a first difference between the first incoming data value and the representative value; and/or comparing the first difference to a difference threshold which indicates whether a difference between an incoming data value and the representative value is significant.

Abstract: Disclosed are various embodiments for detecting security breaches using watchdog transaction accounts. A security agent can initiate a purchase with a first electronic commerce system and provide a watchdog transaction account as payment for the purchase. The security agent can then store a record of the purchase which includes a merchant identifier for the merchant and the watchdog transaction account. Subsequently, a transaction authorization system can determine that authorization for a transaction with second electronic commerce system failed. If the transaction authorization system determines that the account used in the transaction with the second electronic commerce system, then the transaction authorization system can determine that the first electronic commerce system has suffered a security breach.

Abstract: Disclosed are various embodiments for establishing a connection between a client device and a third-party entity device and providing services associated with a third-party entity to the client device according to user-defined access permissions. A context environment can be determined according to user data and third-party entity data. Services available to the user device can be selected according to the context environment, the user-defined access permissions and third-party defined instructions. Upon selecting the services, the services are provided to the client device and a connection between the client device and a third-party entity device can be established.

Abstract: The systems and methods disclosed herein comprise computer-based platforms configured for automated early-stage application security monitoring for allowing users (e.g., application developers) to make decisions at the early stage of the application development.

Abstract: Disclosed are various embodiments for tracking the flow of data through a network environment. A monitor can detect that a data transaction event has occurred. Then, the monitor can identify data involved in the data transaction event. Next, a trace identifier can be assigned to the data involved in the data transaction event. Subsequently, a transaction data subset representing a subset of the data involved in the data transaction event that is subject to a common data processing event can be identified. Then, a span identifier can be assigned to the transaction data subset. Next, a correlation identifier can be link to a combination of the span identifier and the trace identifier. Finally, a transaction event record can be written to a distributed ledger, the transaction event record comprising the span identifier and the transaction data subset.

Abstract: The systems may include dividing a digital map provided by a mapping system into a matrix having a plurality of cells; assigning a cell of the plurality of cells to encompass a geographic region of the digital map; calculating a number of sites of interest in the cell; creating a marker comprising a first count number representing the number of sites of interest in the cell; and sharing the marker with a browser for display on the digital map.

Abstract: Disclosed are various embodiments for issuing virtual cards to client devices. Also disclosed are embodiments for provisioning a transaction terminal to process transactions with virtual cards. A zero-knowledge proof algorithm can be utilized to validate the transactions. A virtual card can be based upon a public key of a client device that is managed by a hardware security module.

Abstract: At least some embodiments are directed to an entity matching detection system. The entity matching detection system includes a latent similarity identification machine learning model that receives one or more data records and generates a final similarity score indicative of a latent similarity between the one or more data records and a second data record. The entity matching detection system can identify lexical and semantic similarities between attribute values and can analyze and compute similarity scores for direct-linked attribute values and cross-linked attribute values extracted from different data records.

Abstract: Systems and methods for identifying data of interest are disclosed. The system may retrieve unstructured data from an internet data source via an alert system or RSS feed. The system may input the unstructured data into various models and scoring systems to determine whether the data is of interest. The models and scoring systems may be executed in order or in parallel. For example, the system may input the unstructured data into a Naive Bayes machine learning model, a long short-term memory (LSTM) machine learning model, a named entity recognition (NER) model, a semantic role labeling (SRL) model, a sentiment scoring algorithm, and/or a gradient boosted regression tree (GBRT) machine learning model. Based on determining that the unstructured data is of interest, a data alert may be generated and transmitted for manual review or as part of an automated decisioning process.

Abstract: At least some embodiments are directed to an entity classification system receives informational data associated with an entity. The informational data includes sentences associated with the entity. The entity classification system utilizes a first machine learning model to determine a first contextual meaning among words of a sentence associated with the entity based on a first word embedding technique, and determines at least one category associated with the entity based at least in part on the first contextual meaning. The entity classification system utilizes a second machine learning model to determine a second contextual meaning shared by a set of sentences based on a second embedding technique, and determines a subcategory of the category associated with the entity based at least in part on the second contextual meaning. The entity classification system generates an output including the category and subcategory associated with the entity.

Abstract: At least some embodiments are directed to a system that receives a profile values associated from new user profiles of a computer network or system. A machine learning system determines a set of existing profiles that share at least one common profile value with the new user profile. A second machine learning model determines a set of existing user entitlements associated with the set of existing profiles. The new user profile is processed by a natural language processing engine to determine a set of new user entitlements from the set of existing user entitlements. The system provides the new user with access to electronic resources of the computer network. The system tracks the new user computer network or system activities and updates the new user profile based on the set of new user entitlements and the new user activity on the computer network or system.