Visa International Service Association

Visa U.s.a. Inc.

Other

Kevin Paul Siegel

Patrick L Faith

Nancy Hilgers

Michelle Eng Winters

Charles Raymond Byce

Belva J Bruesewitz

Edward Winfield Fordyce, Iii

Leigh Amaro

Craig O'Connell

Nurtekin Savas

Thomas H Dwyer

Xiaoli Li

Christopher Brown

Zhongxiao Jiang

Ayman A Hammad

Theodore David Harris

Diane C Salmon

Mark Allen Nelsen

Karl Newland

Frederick Liu

James Alan VonDerheide

Sharon Rowberry

Brad Nightengale

Aoyu Chen

Kris Koganti

Theodore P Washburne

Charles Ding

Suyun Xu

Catherine A Basch

Krishna Prasad Koganti

Scott Edington

Laura DiGioacchino

Peter Ciurea

Kaushik Kaushi Subramanian

Robert L Grossman

Alfred William Griggs

Mayrose Kragas

Randi Annette Paynter

Chuck Byce

Zhongxiao (“Josh”) Jiang

Edward W Fordyce

James Alan Vonderheide

Methods and systems are presented for a fraud risk score to be given to a merchant for a proposed transaction with a consumer. The fraud risk score is generated by a payment account service provider, such as a credit card processor, using information from a pending transaction as well as information from other payment accounts that the consumer holds to which the payment account service provider is privy. Various factors, including indicators of elevated risk in other payment accounts, are custom-weighted by the merchant for the score.

Merchant fraud risk score

Embodiments of the invention relate in part to determining a testing model and providing a testing transaction score for transactions. The testing transaction score may indicate a likelihood that the transaction is a testing transaction. One embodiment of the invention discloses a method comprising receiving a first authorization message for a first transaction using an account, determining a testing transaction score for the first transaction using a testing model, and determining that the first transaction is a testing transaction based on the testing transaction score, wherein the testing transaction score for the first transaction is used for declining a second transaction using the same account conducted after the first transaction.

Systems and methods for large-scale testing activities discovery

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

Systems, apparatus, and methods are provided for efficiently authorizing a transaction initiated by a consumer. An authorization can be generated before the consumer actually initiates the transaction. For example, a future transaction can be predicted, and an authorization can be generated for the predicted transaction. In this manner, the authorization can be ready and quickly used when the consumer does initiate the transaction. Previous transactions made by the consumer can be used to predict when the future transaction is likely. In various examples, the authorization can be sent to a specific merchant or to the consumer for use when the consumer initiates the predicted transaction, or saved by an authorization server for use in response to an authorization request from the merchant.

Pre-authorization of a transaction using predictive modeling

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, apparatus, and methods for determining incentives based on consumer history. When, how, and to whom incentives are sent can be determined. For example, an incentive can be sent to a consumer to encourage a transaction at a time when the particular consumer is predisposed to initiate the transaction. Also, an incentive for a transaction can be sent to a consumer when that transaction has a high likelihood of leading to other transactions. An incentive can also be sent after a consumer initiates a transaction that is known to not have many subsequent transaction correlated to it.

Determining targeted incentives based on consumer transaction history

Improved real-time analytics systems are provided. An analytics system may be used to generate transaction scores for transactions. A method may comprise receiving a scoring request associated with a transaction, sending the scoring request to a plurality of scoring models including a production model, wherein each scoring model is operable to generate a transaction score in response to the scoring request, and wherein each scoring model may be implemented using a virtual machine, receiving a transaction score generated by the production model, and sending the transaction score to a server for approval or denial the transaction.

Real time analytics system

Methods, apparatus, and systems are provided for tracking and analyzing data of consumer activity. The tracked data can be organized (e.g. as stored in cache, RAM, hard drives) in certain types of tables, where the tables can be associated with certain tags (keys) for efficiently accessing the data. The organization and associations of the data can also provide simple mechanisms for manipulating the data to obtain results specifically relevant for a task, such as detection of fraud or prediction of consumer behavior to provide better customer service or new services. For example, the tables may contain counters that store the number of times that two correlated consumer events occur within specific time intervals of each other. Such time data can provide efficient determination of patterns of consumer activity.

Frequency-based transaction prediction and processing

A computing apparatus is configured to quantify consumer sentiment at an aggregated or micro level using transaction data that records the transactions processed by a transaction handler of a payment system. A quantification model is generated based on correlating transaction data with respective emotional content indices extracted from data sources, such as regional news, weather, stock markets, movie themes, local sports, employment, traffic conditions, etc. Using the quantification model, consumer sentiment can be evaluated at various granularity levels, based on the granularity of the user group and the time period of the transaction data used in the quantification model.

Systems and methods to quantify consumer sentiment based on transaction data

Growing community of inventors

Milpitas, CA, United States of America

Kevin Paul Siegel