Abstract: Systems and methods for evaluating risks for physical locations are disclosed. A request for risk evaluation of transactions associated with a physical location located within a predetermined region including a plurality of neighboring locations is received. A spatial model is implemented to generate a first risk score based on chargeback data associated with the physical location and chargeback data of the plurality of neighboring locations. A temporal model is implemented to generate a second risk score for the physical location. A final risk score for the physical location is generated based on the first risk score and the second risk score. The final risk score is transmitted to a computing device for detecting fraudulent transactions associated with the physical location in response to the request.

Abstract: This application relates to systems and methods for automatically generating fraud strategies. A system may comprise customer computing devices, a database, and retailer computing device(s). The retailer computing device(s) are configured to receive data related to customer transactions, calculate a negative reaction score, negative resolution score, anomaly score, and impact score for at least one value of the received data, determine whether the calculated scores are greater than or equal to respective thresholds, identify a value of the received data as a potentially fraudulent data value when one or more of the calculated scores is greater than or equal to its respective threshold, generate an output comprising a list of potentially fraudulent data value(s) and impact scores, identify area(s) of high impact leaks based on the output, and determine which customer computing devices are executing fraudulent transactions based on the identification of areas of high impact leaks.

Abstract: This application relates to systems and methods for automatically generating fraud strategies. A system may comprise customer computing devices, a database, and retailer computing device(s). The retailer computing device(s) are configured to receive data related to customer transactions, calculate a negative reaction score, negative resolution score, anomaly score, and impact score for at least one value of the received data, determine whether the calculated scores are greater than or equal to respective thresholds, identify a value of the received data as a potentially fraudulent data value when one or more of the calculated scores is greater than or equal to its respective threshold, generate an output comprising a list of potentially fraudulent data value(s) and impact scores, identify area(s) of high impact leaks based on the output, and determine which customer computing devices are executing fraudulent transactions based on the identification of areas of high impact leaks.