Merchant specific machine learning model for fraud detection

A non-transitory computer readable storage medium storing instructions, which when executed by a computer processing system, causes the computer processing system to perform operations for detecting a fraudulent electronic transaction, the operations comprising:

• receiving, by the computer processing system, a transaction associated with a merchant;
• processing the transaction with a first machine learning model that is trained specific to the merchant, to obtain a first fraud detection;
• processing the transaction with a second machine learning model that is trained based on a plurality of merchants, to obtain a second fraud detection;
• detecting fraud associated with the transaction based on the first fraud detection and the second fraud detection;
• and
• blocking the transaction, in response to detecting the fraud that is associated with the transaction.

A server computer system for detecting a fraudulent electronic transaction, the server computer system comprising:

• a memory;
• and
• one or more processors coupled with the memory configured to perform operations, comprising:
• receiving, by the server computer system, a transaction associated with a merchant;
• processing the transaction with a first machine learning model that is trained specific to the merchant, to obtain a first fraud detection;
• processing the transaction with a second machine learning model that is trained based on a plurality of merchants, to obtain a second fraud detection;
• detecting fraud associated with the transaction based on the first fraud detection and the second fraud detection;
• and
• blocking the transaction, in response to detecting the fraud that is associated with the transaction.