A machine-learning algorithm is trained with features relevant to basket data for items of transactions. The trained algorithm is trained to predict whether a given transaction is more or less likely to be associated with theft being engaged in by a transaction operator for the transaction. The trained algorithm is then provided basket data for a given transaction and produces as output a theft prediction value. When the theft prediction value exceeds a configured threshold value, the transaction is flagged for manual intervention or the transaction is flagged for subsequent manual verification.

Systems and methods associated with providing an automated portal to migrate one or more relationships with one entity to another entity are disclosed. In one embodiment, an exemplary method may comprise: providing a portal enabling automated migration of existing relationships from existing entities to a first entity; generating a first UI configured for identifying and providing access information regarding existing relationships for potential migration; generating a second UI to display information regarding the existing relationships and provide UI elements enabling the user to receive migration offers; determining terms of replacement relationships that the first entity can offer the user; generating a third UI to (i) compare terms between the existing and new relationships, and (ii) enable the user to authorize the relationship migration; performing an automated generation process to create the new relationship(s); and performing an automated transfer process to transfer all objects to the new relationship.

Computer-implemented methods and systems are provided for locally freezing a user account in a geographic or digital space. Consistent with disclosed embodiments, locally freezing a user account in a geographic or digital space includes receiving fraud data associated with the user account, the fraud data including a location where a fraud associated with the user account has occurred, wherein the fraud location includes at least one of a digital location or a geographical location; receiving account data associated with the user account, the account data including non-fraudulent account transaction information; generating a pattern of fraud based on the fraud data; generating a pattern of use associated with the user account based on the account data; determining a geodigital area for a localized account freeze based on the pattern of fraud and the pattern of use; and performing a localized account freeze on the user account based on the determined geodigital area.

Systems, apparatuses, methods, and computer-readable media are provided for detecting security attacks based on transaction flow graphs. Other embodiments may be described and/or claimed.

The present disclosure relates to system and methods for predicting performance caused by software code changes. For this purpose, an augmented machine learning model predicts a latency of software module with updated code executed in a production environment. In some aspects, the latency is predicted based on a change of deviation that is determined by comparing the latency of the software module with updated code and the latency of the software module without updated code, whereas the software modules are executed in environments different from the production environment.

A method begins by monitoring exchange item transactions occurring in an exchange item marketplace network. The method continues with generating trend information based on the monitored exchange item transactions and determining attributes for a targeted marketing program based on the trend information. The method continues with identifying a subset of buyer computing devices based on the attributes. The method continues by generating offer information based on the targeted marketing program and sending the offer information to the subset of buyer computing devices. When receiving a purchase request from a buyer computing device, the method continues by generating an exchange item request regarding an exchange item and sending the exchange item request to a branded server associated with the exchange item. The method includes receiving offer exchange item information from the branded server and sending at least a portion of the offer exchange item information to the buyer computing device.

A method for execution by a marketplace server includes detecting fraudulent acquisition of an exchange item by a first computing device, where the exchange item has a static identifier (ID) and a dynamic ID that is generated based on exchange item security parameters associated with the exchange item. The method further includes deactivating the dynamic ID and the exchange item security parameters in response to the detecting fraudulent acquisition, where the static ID of the exchange item remains active and valid. The method further includes generating second exchange item security parameters for the exchange item. The method further includes generating a second dynamic ID based on the second exchange item security parameters, where the second dynamic ID establishes the exchange item for utilization in an exchange item marketplace network. The method further includes updating a record in a marketplace database to include the second dynamic ID.

A network data analytics function, which may be implemented as a service, is disclosed which provides a new and improved network data analytics capability in 5G core networks.

Certain aspects involve building segment-specific executable program code. In one example, a code-building service can execute segmentation logic that assigns different target entity records to different segments based on differences between sets of attribute values among the target entity records. The code-building service can select, for each segment, a set of data assets that is specific to the assigned segment and a set of source code portions that is specific to the selected data assets. The code-building service can order each set of the source code portions based on an identified modeling output type for the target entity records. The code-building service can generate, from the ordered source code portions, a set of program code referencing the selected subset of the data assets. For instance, the generated program code, if executed, can generate and transmit different modeling outputs for different target entity records.

A method includes: processing a request to execute a transaction of a virtual asset of a video game; responsive to the request, accessing a blockchain to perform an anti-fraud verification, including analyzing data of a prior transaction involving the virtual asset; responsive to the anti-fraud verification providing a result that does not indicate fraudulent activity, then generating transaction data based on an identifier for the first user account, an identifier for the second user account, an identifier for the virtual asset, and state data of the virtual asset, and submitting the transaction data to a node network, to write the transaction data to a block of the blockchain; receiving confirmation of the writing of the transaction data; responsive to receiving the confirmation, then updating a registry of virtual assets to transfer ownership of the virtual asset from the first user account to the second user account.