View source for MASTERCARD INTERNATIONAL INCORPORATED (20240420146). PREDICTING FRAUDULENT TRANSACTIONS

=PREDICTING FRAUDULENT TRANSACTIONS=


==Organization Name==

[[:Category:MASTERCARD INTERNATIONAL INCORPORATED|MASTERCARD INTERNATIONAL INCORPORATED]]


[[Category:MASTERCARD INTERNATIONAL INCORPORATED]]

==Inventor(s)==

[[:Category:Mohit Taneja of Waterford (IE)|Mohit Taneja of Waterford (IE)]][[Category:Mohit Taneja of Waterford (IE)]]

[[:Category:Jack Nicholls of Dublin (IE)|Jack Nicholls of Dublin (IE)]][[Category:Jack Nicholls of Dublin (IE)]]

[[:Category:James Conway of Dublin (IE)|James Conway of Dublin (IE)]][[Category:James Conway of Dublin (IE)]]

[[:Category:Nitish Kothale of Dublin (IE)|Nitish Kothale of Dublin (IE)]][[Category:Nitish Kothale of Dublin (IE)]]

[[:Category:Shannon Holland of San Francisco CA (US)|Shannon Holland of San Francisco CA (US)]][[Category:Shannon Holland of San Francisco CA (US)]]

[[:Category:Weston Moran of Merrimack NH (US)|Weston Moran of Merrimack NH (US)]][[Category:Weston Moran of Merrimack NH (US)]]

==PREDICTING FRAUDULENT TRANSACTIONS==


This abstract first appeared for US patent application 20240420146 titled 'PREDICTING FRAUDULENT TRANSACTIONS




==Original Abstract Submitted==

a computer implemented method of training a model, using a machine learning process, to predict whether a transaction of a digital currency stored in a blockchain is fraudulent, comprises: unpacking () a block in the blockchain into a table comprising one or more rows of input and output data for a previous transaction stored in the block and aggregating () the one or more rows of input and output data to form an aggregated row of transaction data for the previous transaction. the method further comprises labelling () the aggregated row of transaction data for the previous transaction according to whether the previous transaction was fraudulent and using () the aggregated row of transaction data and the label as training data with which to train the model.



[[Category:G06Q20/40]]
[[Category:CPC_G06Q20/4016]]