Methods and arrangements to distribute a fraud detection model

A non-transitory machine-readable medium containing instructions, which when executed by a processor, cause the processor to perform operations, the operations to:

• associate customer identifications with models to assign the models to customers, each of the models to comprise a pretrained model to detect fraudulent transactions;
• identify one or more clusters to associate with the customers based on characteristics associated with the customers;
• assign each of the customers to the one or more clusters, each cluster to identify a group of customers based on the characteristics associated with the group of customers, and each group of customers having at least one different characteristic of the characteristics than other groups of the plurality of groups of customers;
• cause the models to transmit to customer devices, each of the customer devices associated with one of the customers;
• receive transaction data for a transaction for one customer, the one customer associated with a first cluster;
• modify the transaction data to create modified transaction data;
• communicate the modified transaction data to customer devices of customers associated with the first cluster;
• and
• receive responses from the customer devices based on application of a model of the customer devices of customers associated with the first cluster on the modified transaction data, the responses received to identify the modified transaction as a fraudulent transaction or a non-fraudulent transaction.

A computer-implemented method, comprising:

• assigning customer identifications to models to associate customers with the models, each of the models pretrained to detect fraudulent transactions;
• determining one or more clusters to associate with the customers based on characteristics associated with the customers;
• associating one or more cluster identifications with each of the customers, each cluster identification to identify one cluster of the one or more clusters, each cluster to identify a particular group of the customers of a plurality of groups of the customers, each group of customers having at least one different characteristic of the characteristics than other groups of the plurality of groups of customers;
• communicating the models, to cause the models to transmit to customer devices associated with the customers, each customer device associated with one of the customers;
• receiving transaction data for a transaction for one customer of the group of the customers, the one customer associated with a first cluster;
• modifying the transaction data to create modified transaction data;
• communicating the modified transaction data to customer devices of customers associated with the first cluster;
• and
• receiving responses from the customer devices based on application of models of the customer devices of customers associated with the first cluster on the modified transaction data, the responses received to identify the modified transaction as a fraudulent transaction or a non-fraudulent transaction.