METHOD FOR DETECTING MERCHANT DATA BREACHES WITH A COMPUTER NETWORK SERVER

摘要

A method for minimizing merchant data breach damage depends on computers and financial networks to carry out its steps. Every payment card transaction witnessed each day by a network server is assessed by a “jury” of fraud classification algorithms and assigned a fraud-risk-verdict. Those payment transactions receiving a high-risk-fraud verdict are retained and sorted into a table according to transaction date, cardholder, and merchant. The raw verdicts are normalized and standardized according to merchant size groups, e.g., to even the comparisons that will be made. A daily tally is made for each merchant of the number of suspected-card-visits, the number of highly-probable-card-visits, and the number of total-card-visits. A merchant data-breach alert is issued if a final score and sum of the normalized verdicts exceeds a threshold.

主权项

1. A method for minimizing financial damage in merchant data breaches, and that depends on computers and financial networks to carry out its steps, comprising:
inputting payment authorization request records of real-time transactions received over a network from point-of-sale terminals; applying classification algorithms with a computer programmed for this purpose that depends on any data warehoused in preconditioned data structures or records; consulting a population of smart agents with a computer programmed for this purpose that depends on the data warehoused in said data structures or records; judging the weights and balances of a plurality of jurors in a jury panel of classification algorithms with a computer programmed for this purpose, and that depends on the data warehoused in said data structures or records; deciding each payment transaction request with a computer programmed for this purpose that depends on the data warehoused in said data structures or records; assessing all such records of payment card transactions witnessed each day through a network server executing a jury of fraud classification algorithms that then combine to allocate a fraud-risk-verdict for each payment card transaction; retaining those payment transactions having been allocated a high-risk-fraud verdict that exceeds a threshold value with a computer programmed for this purpose; sorting any retained payment transactions receiving a high-risk-fraud into a table according to transaction date, cardholder, and merchant with a computer programmed for this purpose; normalizing and standardizing said sorted and retained high-risk-fraud verdicts according to merchant size groups for evened comparisons using a multiplier with a computer programmed for this purpose; making a daily tally for each merchant of the number of suspected-card-visits, the number of highly-probable-card-visits, and the number of total-card-visits of normalized and standardized high-risk-fraud verdicts with a computer programmed for this purpose; and issuing a merchant data-breach alert with a computer programmed for this purpose if a final score and sum of normalized and standardized high-risk-fraud verdicts in a daily tally exceeds a threshold.