Abstract: A method of generating an input for a machine learning algorithm may include collecting data records. Each data record may include a plurality of categories of data. The method may include using vector quantization to partition the plurality of data records into a plurality of groupings. Each of the groupings may be based on one or more of the plurality of categories of data. The method may include generating a correlation score for each of the plurality of groupings. The correlation score may be indicative of whether a particular group is indicative of a given outcome.

Abstract: A payment and authentication network may include a communications interface, one or more processors, and a memory. The memory may have instructions stored thereon that, when executed by the one or more processors cause the one or more processors to receive, using the communications interface, transaction information associated with a transaction from a merchant system and generate a fraud risk score based on the transaction information. The instructions may cause the one or more processors to determine that the fraud risk score is indicative that the transaction is likely fraudulent and transmit an alert to a user device that informs a user of the user device that the transaction is likely fraudulent prior to generating an approval decision for the transaction.