Visa International Service Association

Visa U.s.a. Inc.

Nancy Hilgers

Kevin Paul Siegel

Craig O'Connell

Mark Allen Nelsen

Patrick L Faith

Belva J Bruesewitz

Xiaoli Li

Frederick Liu

Thomas H Dwyer

Christopher Brown

Joe Bruce Scott

Kris Koganti

Melyssa Barrett

Kevin E Wong

Krishna Prasad Koganti

Methods, systems, and devices are disclosed for using a payment processing network as an authorization engine to access secure physical areas, such as college dormitories, office buildings. A keycard with a cryptogram generator is presented by a user to an access device, and the access device or associated computer sends an access request message formatted like a payment authentication request message to an aggregator/acquirer and payment processing network. The payment processing network validates the cryptogram and returns an access response message, again formatted like a payment authorization response message, indicating that the keycard is authentic. The gate, door, turnstile, or other barrier is then temporarily unlocked to let the user through.

System and method for authentication using payment protocol

A system for providing real-time risk mitigation for an authorization system. The system receives authorization requests from multiple merchants (or their respective acquirers) and processes such requests. Each processed request is then forwarded to its corresponding issuer for further authorization. Each processed request includes an authorization message. The authorization message can include a risk score, a number of reason codes, and a number of condition codes. The use of the risk score, reason codes and condition codes allows issuers to make better informed decisions with respect to providing authorizations.

Method and system for providing risk information in connection with transaction processing

Rules, applied to deny authorization of likely fraudulent transactions, are derived from a modified Patient Rule Induction Method algorithm that uses a target variable and a data set of past transactions each associated with a plurality of input variables and a hyper-rectangle enclosing a multi-dimensional space defined by a representation of the input variable values as points within the multi-dimensional space. While a count of the points within the hyper-rectangle is greater than a minimum support parameter, a first plurality of points proximal to edges of the hyper-rectangle are removed, where each such removing maximizes a mean value of the target variable, and then, while the mean value remains maximized, a second plurality of points proximal to the edges is added, where each adding maximizes or maintains the mean value. The hyper-rectangle is bounded within a minimum bounding box that defines the rules.

Risk assessment rule set application for fraud prevention

Systems and methods for determining and reporting aggregated transaction level data regarding a particular user are disclosed. Based on the requests of one or more information requesters, an aggregator server can request transaction level data for all accounts associated with a particular user or a group of users from a transaction database. The transaction database returns raw transaction level data for accounts associated with the particular user to the aggregator server. The aggregator server can then parse the raw transaction level data based on a number of transaction level data elements and information requester input. The parsed raw transaction level data can then be used to determine the number of predefined or information requester defined transaction level data aggregates. The resulting transaction level data aggregates can then be sent in a report to the one or more information requesters.

Transaction aggregator

Systems and methods for determining and reporting aggregated transaction level data regarding a particular user are disclosed. Based on the requests of one or more information requesters, an aggregator server can request transaction level data for all accounts associated with a particular user from a transaction database. The transaction database returns raw transaction level data for all accounts associated with the particular user to the aggregator server. The aggregator server can then parse the raw transaction level data based on a number of transaction level data elements and information requester input. The parsed raw transaction level data can then be used to determine the number of predefined or information requester defined transaction level data aggregates. The resulting transaction level data aggregates can then be sent in a report to the one or more information requesters.

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Danville, CA, United States of America

Nancy Hilgers