A method, comprising: for each account of a plurality of accounts, determining a component blame score for each potential point of compromise, POC, of a plurality of potential points of compromise, wherein determining the component blame score includes: representing the determinations as at least a computer computational matrix operation, where rows of the computer computation matrix correspond to accounts and columns correspond to locations, dividing a matrix of the computer computational matrix operation into computational blocks, and distributing the blocks among a plurality of computational computer nodes for distributed computer computation; determining an overall compromise blame score for each potential point of compromise of the plurality of potential points of compromise based on the determined component blame score including by dividing a sum of the determined component blame scores by a number of accounts with which the potential POC interacted weighted by at least one past calculation of the overall compromise blame score; alternately updating a value of the determined component blame scores for each potential point of compromise of the plurality of potential points of compromise and a value of the determined overall compromise blame score for each potential point of compromise through successive iterations until the determined overall compromise blame scores have converged, wherein convergence includes determining whether values have stabilized; and in the event the determined overall compromise blame scores have converged, selecting at least one of the plurality of potential points of compromise as a likely point of compromise based at least on the corresponding overall compromise blame score of the selected likely point of compromise. for each account of a plurality of accounts, determining a component blame score for each potential point of compromise, POC, of a plurality of potential points of compromise, wherein determining the component blame score includes: representing the determinations as at least a computer computational matrix operation, where rows of the computer computation matrix correspond to accounts and columns correspond to locations, dividing a matrix of the computer computational matrix operation into computational blocks, and distributing the blocks among a plurality of computational computer nodes for distributed computer computation; representing the determinations as at least a computer computational matrix operation, where rows of the computer computation matrix correspond to accounts and columns correspond to locations, dividing a matrix of the computer computational matrix operation into computational blocks, and distributing the blocks among a plurality of computational computer nodes for distributed computer computation; determining an overall compromise blame score for each potential point of compromise of the plurality of potential points of compromise based on the determined component blame score including by dividing a sum of the determined component blame scores by a number of accounts with which the potential POC interacted weighted by at least one past calculation of the overall compromise blame score; alternately updating a value of the determined component blame scores for each potential point of compromise of the plurality of potential points of compromise and a value of the determined overall compromise blame score for each potential point of compromise through successive iterations until the determined overall compromise blame scores have converged, wherein convergence includes determining whether values have stabilized; and in the event the determined overall compromise blame scores have converged, selecting at least one of the plurality of potential points of compromise as a likely point of compromise based at least on the corresponding overall compromise blame score of the selected likely point of compromise. <EOS>