Identification and management of fraudulent credit/debit card purchases at merchant ecommerce sites
First Claim
Patent Images
1. A computer implemented method of processing an online transaction, the method comprising:
- generating from an online transaction of a purchaser, a plurality of keys from key fields of the transaction that individually do not reliably identify the purchaser;
for each key, retrieving a profile of historical transactions associated with the key;
weighting each profile with a weight indicating a degree to which the profile is associated with current purchaser; and
generating a fraud score indicative of the likelihood of fraud in the online transaction as a function of the weighted profiles and the current transaction.
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Abstract
Transaction processing of online transactions at merchant sites determines the likelihood that such transactions are fraudulent, accounting for unreliable fields of a transaction order, which fields do not reliably identify a purchaser. A scoring server using statistical model uses multiple profiles associated with key fields, along with weights to indicate the degree to which the profiles identify the purchaser of the transaction.
780 Citations
37 Claims
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1. A computer implemented method of processing an online transaction, the method comprising:
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generating from an online transaction of a purchaser, a plurality of keys from key fields of the transaction that individually do not reliably identify the purchaser;
for each key, retrieving a profile of historical transactions associated with the key;
weighting each profile with a weight indicating a degree to which the profile is associated with current purchaser; and
generating a fraud score indicative of the likelihood of fraud in the online transaction as a function of the weighted profiles and the current transaction. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 20, 21, 22, 23, 24, 25, 26, 27)
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15. A method of developing a statistical model of online transactions, the method comprising:
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storing from a plurality of different online merchants, transactions for a plurality of different purchasers, each transaction indicated as being fraudulent or non-fraudulent;
for each of a plurality of key fields of the transaction, including at least one key field for which all of the possible keys of the key field do not reliably identify a purchaser of the transaction, generating for each key of the key field, a profile for all of the transactions having a matching key for the key field, such that at least one profile summarizes the transactions of a plurality of different individuals;
generating a contrast measure comparing the summary variables of at least two of the profiles; and
training a statistical model generate a score for a transaction, the score indicative of a likelihood that the transaction is fraudulent, by using as training inputs to the statistical model selected transactions, the profiles associated with the keys of the key fields of each selected transaction, and the contrast measures associated with the profiles.
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19. A computer implemented method of processing an online transaction, the method comprising:
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generating from the online transaction of a purchaser, a plurality of keys from key fields of the transaction that individually do not reliably identify the purchaser;
for each key, retrieving a profile of historical transactions associated with the key, each profile including at least one summary variable;
computing at least one contrast measure for a summary variable included in the set of profiles; and
inputting the contrast measures, the online transaction data and the selected set of profiles into a predictive model to generate a fraud score indicative of the likelihood of fraud in the online transaction.
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28. A computer implemented method of processing transactions to statistically identify a current purchaser, the method comprising:
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receiving a transaction;
generating from the transaction a plurality of keys, including keys containing keys that individually do not reliably identify the purchaser;
for each key, retrieving a profile summarizing historical transactions by purchasers whose profiles match the key;
weighting each of the retrieved profiles by a weight indicating the degree to which the profile is associated with the current purchaser;
predicting the likelihood of fraud in the current transaction as a function of the weighted profiles and the current transaction.
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29. A computer implemented method of identifying a current purchaser of online transaction, the method comprising:
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receiving an online transaction from a current purchaser, the online transaction including purchaser identification information;
generating from the online transaction a plurality of keys that individually do not reliably identify the current purchaser;
for each key, retrieving a profile summarizing a plurality of historical transactions associated with the key, each profile including a plurality of summary variables derived from the associated historical transactions; and
selecting as the profiles of the current purchaser the profiles having the most similar summary variables.
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30. A system for processing online transactions, the system comprising:
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a rule engine that receives from a scoring system a fraud score associated with a transaction, the fraud score indicating the likelihood of fraud in the transaction, which applies a plurality of stored rules to the fraud score, each rule providing a condition and an action to perform in response to the transaction or the fraud score, to determine according to the rules whether to approve or decline the transaction, request more information from the purchaser, or hold the transaction for review by a human analyst;
an outsort management workstation that receives from the rule engine transactions to be held for review, stores the transactions in queues, and provides access to the queues to a human analyst in order to review transactions in the queues, the outsort management workstation further adapted to define for each queue at least one criteria for associating a transaction with the queue; and
a policy management workstation adapted to access the stored rules, and define rules for the rule engine to apply.
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31. A system for scoring a transaction, the system comprising:
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a plurality of stored profiles, each profile associated with a key for one of a plurality of key fields of a transaction, the key fields including at least one key field that does not reliably identify a purchaser of a transaction, each profile including summary variables summarizing all transactions having a same key for at least one of the key fields; and
a statistical model that receives as inputs a transaction, a plurality of profiles, each profile summarizing transactions associated with a key for a key field, and at least one contrast measure that weights selected pairs of the profiles, and that produces a fraud score indicating the likelihood of fraud in the transaction. - View Dependent Claims (32)
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33. A method of establishing a cutoff score for a transaction processing system that processes transactions of a merchant, the method comprising:
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providing a statistical model that generates a score categorizing a transaction, the score used by the merchant to accept or reject the transaction;
determining for each of a plurality of scores generated by the statistical model an actual transaction false positive rate;
determining a desired transaction false positive rate as a function of the merchant'"'"'s net margin; and
setting the cutoff score for rejecting transactions as a score having an actual transaction false positive rate approximating or equal to the desired transaction false positive rate. - View Dependent Claims (34)
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35. A computer implemented system of processing an online transaction, the method comprising:
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means for receiving an online transaction from a current purchaser, the online transaction including purchaser identification information, order information, and payment information;
means for generating from the online transaction a plurality of keys that individually do not reliably identify the current purchaser;
means for retrieving a profile summarizing a plurality of historical transactions associated with the each key;
means for weighting each profile with a weight indicating a degree to which the profile is associated with current purchaser; and
means for generating a fraud score indicative of the likelihood of fraud in the online transaction as a function of the weighted profiles and the current transaction.
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36. A system for developing a statistical model of online transactions, the method comprising:
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a database for storing transactions from a plurality of different online merchants, the transactions for a plurality of different purchasers, each transaction indicated as being fraudulent or non-fraudulent;
means for generating for each of a plurality of key fields of the transaction—
including at least one key field for which all of the possible keys of the key field do not reliably uniquely identify a purchaser of the transaction—
a profile for all of the transactions having a matching key for the key field, such that at least one profile summarizes the transactions of a plurality of different individuals;
means for generating a contrast measure comparing the summary variables of at least two of the profiles; and
means for training a statistical model generate a score for a transaction, the score indicative of a likelihood that the transaction is fraudulent, by using as training inputs to the statistical model selected transactions, the profiles associated with the keys of the key fields of each selected transaction, and the contrast measures associated with the profiles.
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37. A system for processing online transactions, the system comprising:
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a rule engine having a function of determining whether to approve a transaction, decline the transaction, request more information from the purchaser of the transaction, or hold the transaction for review by a human analyst by way of receiving a fraud score for the transaction from a scoring system and applying rules to the fraud score, wherein each rule defines a condition and an action to perform in response to the transaction or the fraud score, to produce a determination for handling the transaction;
an outsort management workstation having a function of queuing transactions to be held for review and providing access to the queues to a human analyst in order to review transactions in the queues by way of receiving from the rule engine transactions to be held for review and storing the transactions in queues, each queue having at least one criteria for storing a transaction in the queue, to produce a set of queues, each queue storing one or more transactions; and
a policy management workstation having a function of defining rules for the rule engine to apply, by way of providing access to the stored rules.
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Specification