Fair Isaac Corporation

Linyu Yang

Joseph P Milana

Gregory Gancarz

David Griegel

Bo Zhang

Zuohua Zhang

Danfeng Li

A computer-implemented method and system for detecting fraud in electronic commerce traffic are disclosed. A global conversion rate is defined that represents activity related to a purchase made or proxy activity executed during electronic commerce traffic to a commercial website that is indicative of non-fraud activity. Subsets of the electronic commerce traffic to a commercial website are monitored for clusters of activity having a conversion rate that is lower than a global conversion rate by a threshold margin. A number of user-initiated input signals from an input device to navigate from each of one or more affiliate websites to the commercial website, and a number of conversions generated from each of the one or more affiliate websites, are registered by a computer for analysis.

Auto adaptive anomaly detection system for streams

A merchant profile builder (MPB) is provided. The complete merchant profiling process is split into three pieces: Data Preprocessing, Weekly Summary Calculation, and Merchant Profile Calculation. In the Data Preprocessing stage, authorization data and daily fraud data are processed on a weekly basis to yield: an authorization extract file and fraud authorization data, each of which are sorted by a merchant key. In the Weekly Summary Calculation stage, the files output by the Data Preprocessing stage are used as input to compile basic statistics for each merchant based only on data for one week. There are separate weekly summaries for authorizations and fraud authorizations. In the Merchant Profile Calculation stage, the weekly summaries from the 16 most recent weeks are combined together and averages are calculated and output a set of merchant profiles and a set of default profiles.

Method and apparatus for a merchant profile builder

A method of generating a model for performing account-level fraud detection is disclosed, and includes obtaining a plurality of candidate rules for referrals of financial transactions, calculating a savings density for each of the plurality of rules, selecting a rule from the plurality of rules having the maximum savings density, iteratively rebalancing savings densities for the remaining rules of the plurality of rules and selecting a next rule until a volume constraint is satisfied, and applying the selected rules to one or more financial transactions.

Growing community of inventors

San Diego, CA, United States of America

Linyu Yang