Abstract: Systems and methods to identify blockchain anomalies include an AI tool comprising a processor, a GPU, and a GNN model to extract graph parameters from a block transactions graph of a blockchain block, generate statistical approximations of the graph based on the graph parameters, compare the statistical approximations to at least one anomaly threshold, detect an irregular graph pattern in the graph when the statistical approximations exceed the at least one anomaly threshold, identify via the GNN model an anomaly within the block transactions graph based on the irregular graph pattern, generate via the GPU an address graph based on the block transactions graph when the anomaly is identified to display one or more addresses associated with the anomaly, and generate an alert when the anomaly is identified.

Abstract: Systems and methods to identify blockchain anomalies include an artificial intelligence (AI) tool comprising a processor and an AI model, a memory communicatively coupled to the processor, and machine-readable instructions stored in the memory. Upon execution by the processor, the machine-readable instructions cause the processor to: extract block parameters from a block of a blockchain, generate one or more statistical approximations of the block based on the block parameters, compare the one or more statistical approximations of the block to at least one anomaly threshold, detect an irregular block pattern in the block when the one or more statistical approximations exceed the at least one anomaly threshold, via the AI model, identify an anomaly within the block based on the irregular block pattern in the block, and generate an alert when the anomaly is identified.

Abstract: A method and a system for performing stochastic sequential assignment of jobs with random arrival times is provided. The method includes receiving a first plurality of jobs in a sequence; and sequentially applying, to each respective job from among the first plurality of jobs, a non-parametric sequential allocation algorithm in order to determine whether to accept the respective job or to decline the respective job. The application of the non-parametric sequential allocation algorithm includes calculating, for each respective job, a corresponding reward value that relates to a reward that is gained when the respective job is accepted; and maximizing an expected cumulative reward value based on the calculated reward values.

Abstract: Systems and methods for multi-agent based fraud detection are disclosed. A method may include: providing a generator configuration file comprising a plurality of transaction behaviors and a number or proportion of generator agents to act in accordance with each transaction behavior; providing a detector configuration file comprising a detector parameter for a plurality of detector agents to use; generating a first set of test data using the generator agents based on the transaction behavior, wherein the first set of generated test data may include a first set of generated test transactions, and each generated test transactions may include a fraud indicator based on the transaction behavior; training a plurality of detector agents using the first set of generated test data and the detector configuration file, wherein each detector agent outputs a first trained model object; and outputting a first trained detection model based on the first trained model objects.

Abstract: Systems and methods for generating synthetic data using a learned copula are disclosed.

Abstract: Systems and methods for applying game theory for fraud detection. Rather than inspecting every transaction record, embodiments are directed to limiting incoming suspicious transaction records according to a schedule. The schedule may define time windows for various clients and transactions. These time windows may filter down the stream of incoming transaction records to a subset. As a result, fraud may be detected by strategically allocating resources in an optimal way rather than attempting to inspect each and every instance of transaction.