A method for detecting abnormal transactional behavior in a financial account is provided. The method includes: accessing first information that includes a textual description of a first transaction of a plurality of transactions associated with a first account; analyzing the text by applying tags thereto; assigning, based on a result of the analyzing, the first transaction to a respective cluster of the plurality of transactions; and designating each respective cluster as corresponding to one from among a normal transactional behavior group, an abnormal transactional behavior group, and an anomalous transactional behavior group. When a proportion of abnormal and anomalous transactions exceeds a threshold, the account may be flagged for further investigation.

An apparatus and a method of operating a data processing apparatus, and simulators thereof, are disclosed. Data processing circuitry performs data processing operations in response to instructions, where some sets of instructions may be defined as a transaction which are to be performed atomically with respect to other operations performed by the data processing circuitry. When a synchronous exception occurs during a transaction the transaction is aborted and an exception counter is incremented. When the counter reaches a threshold value a transaction failure signal is generated, allowing, if appropriate a response to this number of exceptions causing transaction aborts to be carried out.

Aspects described herein may relate to a transaction exchange platform using a streaming data platform (SDP) and microservices to process transactions according to review and approval workflows. The transaction exchange platform may receive transactions from origination sources, which may be added to the SDP as transaction objects. Microservices on the transaction exchange platform may interact with the transaction objects based on configured workflows associated with the transactions. Processing on the transaction exchange platform may facilitate clearing and settlement of transactions. Some aspects may provide for dynamic and flexible reconfiguration of workflows and/or microservices. Other aspects may provide for data snapshots and workflow tracking, allowing for monitoring, quality control, and auditability of transactions on the transaction exchange platform.

Techniques are disclosed relating to reporting for network events within a computer network. A computer system may access a set of data corresponding to a particular network event within a computer network, where the set of data includes captured attributes of the particular network event. The computer system may then calculate, using the set of data, a security score indicative of suspiciousness of the event and an actionability score that is based on an extent to which of a particular group of attributes are missing from the set of data. The computer system may determine, based on the two scores, a combined score for the event. The computer system may then report a notification for the event, based on the combined score. Such techniques may decrease a number of reported events for a network, which may advantageously allow resources to be focused on a smaller set of events.

Exemplary aspects for a specific example concern a radar system having sensor circuitry including multiple radar sensors to provide sensor data via multiple virtual channels and multiple data types, a memory circuit with memory buffers, and a bus-interface circuit to control bus interconnects for bus communications involving a radar signal transmitter and the memory circuit. Radar signals are received and processed, via data acquisition path circuitry in multiple circuit paths and via streams of data in response to and to accommodate the operations of the sensor circuitry. A master controller conveys data, via the bus-interface circuit, to the buffers for the sensor data, and generates selectable-type transactions to be linked in selected ones of the buffers, in response to the data provided from the sensor circuitry and based on the sensor data being provided via different ones of the multiple virtual channels and of the multiple data types.

Example methods and systems for software bug reproduction. One example method may comprise obtaining log information associated with multiple transactions processed by a control-plane node to configure a set of data-plane nodes and transform an initial network state to a first network state; and configuring a replay environment that is initialized to the initial network state, and includes a mock control-plane node and a set of mock data-plane nodes. The method may also comprise, based on the log information, replaying the multiple transactions using the mock control-plane node to configure the set of mock data-plane nodes and transform the replay environment from the initial network state to a second network state. Based on a comparison between the first network state and the second network state, a determination may be made as to whether a software bug is successfully reproduced in the replay environment.

System and methods are provided for detecting, tracking, and managing outages of transaction processors. An indication is received indicating a potential outage associated with a transaction processor computer configured to process transactions of an online retail website. The indication can be received from a threshold monitoring service and/or from a machine-learning detection system. A computing service can be initiated to confirm and track the outage over time. An outage may include a number of situations in which the transaction processor fails to process transactions according to a set of predefined processing parameters. If the outage spans a particular time period, the service can perform a number of remedial actions (e.g., notifying an administrator of the outage, etc.).

A method including receiving, from a user device, a user request to access data associated with a web page; generating, by a processor, a first transaction identification; collecting transaction information, the transaction information comprising server-side metrics; integrating, by the processor, the first transaction identification with the transaction information; transmitting, by the processor, the first transaction identification to the user device; receiving, from the user device, client-side data associated with a second transaction identification; integrating, by the processor, the server-side metrics and the client-side data; and analyzing, by the processor, the integrated server-side metrics and the client-side data.

Described are a system, method, and computer program product for operating dynamic shadow testing environments for machine-learning models. The method includes storing a testing policy including an identifier of a machine-learning model and an identifier of a transaction service. The method includes generating a shadow testing environment operating the transaction service using the machine-learning model. The method also includes receiving, at a transaction service provider system, a transaction authorization request including transaction data of a transaction associated with a payment device. The method further includes identifying the machine-learning model associated with the transaction based on a parameter of the transaction data. The method further includes determining, based on the identifier of the machine-learning model, the testing policy and the shadow testing environment. The method further includes replicating the transaction data in the shadow testing environment as input for testing the transaction service using the machine-learning model.

An electronic device, comprising: a first component configured to transmit a first set of data to a second component by providing a first memory request specifying the first set of data for and an input memory address, and a transaction tracking unit coupled to a first transport interface, the transaction tracking unit configured to: receive the first memory request; transmit a second memory request that specifies at least a first portion of the first set of data, via the first transport interface, to the second component; receive a response to the second memory request from the second component; determine that the response corresponds to the second memory request; and provide, to the first component, an output response based on the received response to the second memory request.