Abstract: A method for detecting collusive transaction fraud includes: generating a merchant baseline including a transaction data baseline and a time series baseline; extracting time series data of the first merchant system; generating a first score and second score with a deep learning model; generating a first merchant risk score of the first merchant system based on the first and second scores; in response to determining that the first merchant risk score satisfies the threshold, determining a plurality of related entities related to the first merchant system; and classifying the first merchant system and at least one related entity of the plurality of related entities in a first group risk class based on at least one risk score of the at least one related entity.

Abstract: Provided is a computer-implemented method for detecting potential money laundering activities. The method may include determining an overall transaction product category risk score for each transaction product category of a plurality of transaction product categories, where the overall transaction product category risk score is based on transaction data, a transaction product category risk score associated with the at least one issuer institution for each transaction product category, an issuer institution risk score associated with the at least one issuer institution, and a geographic risk score associated with the at least one issuer institution, determining an overall issuer institution risk score associated with the at least one issuer institution, determining whether the overall issuer institution risk score satisfies a threshold value, generating a notification, and communicating the notification to a client device based on generating the notification.

Abstract: Provided is a computer-implemented method for detecting potential money laundering activities. The method may include determining an overall transaction product category risk score for each transaction product category of a plurality of transaction product categories, where the overall transaction product category risk score is based on transaction data, a transaction product category risk score associated with the at least one issuer institution for each transaction product category, an issuer institution risk score associated with the at least one issuer institution, and a geographic risk score associated with the at least one issuer institution, determining an overall issuer institution risk score associated with the at least one issuer institution, determining whether the overall issuer institution risk score satisfies a threshold value, generating a notification, and communicating the notification to a client device based on generating the notification.