Abstract: Systems, methods, devices, and computer readable media related to fraud detection. Fraud detection is achieved using a flexible scripting language and syntax that simplifies the generation of fraud detection rules. The rules are structured as conditional IF-THEN statements that include data objects referred to as Anchors and Add-Ons. The Anchors and Add-Ons used to generate the rules also correspond to a distinct data path for the retrieval data from any of a variety of data sources. The retrieval of data from the various data sources is optimized based on data dependencies within the rules. By knowing the data dependencies of each rule and utilizing parallelization of rule execution, the retrievals of data from the data sources is achieved efficiently so the rules can be executed quickly.

Abstract: Systems, methods, devices, and computer readable media related to fraud detection. Fraud detection is achieved using a flexible scripting language and syntax that simplifies the generation of fraud detection rules. The rules are structured as conditional IF-THEN statements that include data objects referred to as Anchors and Add-Ons. The Anchors and Add-Ons used to generate the rules also correspond to a distinct data path for the retrieval data from any of a variety of data sources. The generated rules with distinct data paths are then converted using a transpiler from the scripting language into native language source code (e.g., PHP, Java, etc.) for deployment in a particular environment. The rules are then executed in real-time in the environment to detect potential fraudulent activity.

Abstract: Systems, methods, devices, and computer readable media related to fraud detection. Fraud detection is achieved using a flexible scripting language and syntax that simplifies the generation of fraud detection rules. The rules are structured as conditional IF-THEN statements that include data objects referred to as Anchors and Add-Ons. The Anchors and Add-Ons used to generate the rules also correspond to a distinct data path for the retrieval data from any of a variety of data sources. The retrieval of data from the various data sources is optimized based on data dependencies within the rules. By knowing the data dependencies of each rule and utilizing parallelization of rule execution, the retrievals of data from the data sources is achieved efficiently so the rules can be executed quickly.

Abstract: Systems, methods, devices, and computer readable media related to fraud detection. Fraud detection is achieved using a flexible scripting language and syntax that simplifies the generation of fraud detection rules. The rules are structured as conditional IF-THEN statements that include data objects referred to as Anchors and Add-Ons. The Anchors and Add-Ons used to generate the rules also correspond to a distinct data path for the retrieval data from any of a variety of data sources. The generated rules with distinct data paths are then converted using a transpiler from the scripting language into native language source code (e.g., PHP, Java, etc.) for deployment in a particular environment. The rules are then executed in real-time in the environment to detect potential fraudulent activity.