Abstract: In an embodiment, a data processing method comprises obtaining a plurality of first transaction data items for a proposed online credit card purchase transaction that has been recommended for review; obtaining a plurality of second transaction data items for a set of similar past online credit card purchase transactions, wherein each member of the set has one or more transaction feature values that are similar to the transaction data items of the proposed online credit card purchase transaction, and a decision value specifying whether the member was accepted or rejected by a reviewer; obtaining a stored data model of features, feature values, transaction acceptance decisions and rejection decisions of the reviewer based at least in part on the set, determining, based on applying the first transaction data items to the stored data model and a subsequent query to the database among more recent transactions that were not included during model construction, a likelihood value of a particular decision of whether t

Abstract: Embodiments of the invention are directed to a fraud detection system that records an audit log of modifications made by a user to a selection of fraud detection rules in a merchant profile. The audit log contains details of the modifications and the user associated with the modifications. A search can be conducted on the audit log to determine details of modifications made to a merchant profile within the fraud detection system.

Abstract: Embodiments of the invention are directed to a fraud detection system that stores fraud detection rules and merchant profiles. The fraud detection system allows a user to designate fraud detection rules as core fraud detection rules, and the fraud detection system can automatically populate new merchant profiles with the user's core fraud detection rules.

Abstract: Modern technologies of signal processing and real-time feedback adaptive control are applied to a fraud screen model to enable the fraud screen model to adapt to changes in shopping behavior to effectively maintain the model's performance on a review rate score curve continuously. Multiple techniques disclosed herein integrate control technologies with modeling technology to control the review rate score curve in real time.

Abstract: In an embodiment, a data processing method comprises obtaining a plurality of first transaction data items for a proposed online credit card purchase transaction that has been recommended for review; obtaining a plurality of second transaction data items for a set of similar past online credit card purchase transactions, wherein each member of the set has one or more transaction feature values that are similar to the transaction data items of the proposed online credit card purchase transaction, and a decision value specifying whether the member was accepted or rejected by a reviewer; obtaining a stored data model of features, feature values, transaction acceptance decisions and rejection decisions of the reviewer based at least in part on the set, determining, based on applying the first transaction data items to the stored data model and a subsequent query to the database among more recent transactions that were not included during model construction, a likelihood value of a particular decision of whether t

Abstract: Modern technologies of signal processing and real-time feedback adaptive control are applied to a fraud screen model to enable the fraud screen model to adapt to changes in shopping behavior to effectively maintain the model's performance on a review rate score curve continuously. Multiple techniques disclosed herein integrate control technologies with modeling technology to control the review rate score curve in real time.