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Timely access to rich payment transaction data is the key to effective fraud prevention. ACI ReD Fraud Xchange (RFX) connects merchants with other merchants and with issuers in a multi-way, real time and near real time exchange of information – for faster fraud detection.

There is no longer a need to wait days or even weeks before knowing that fraud is happening. With faster access to information, organizations can act more quickly to protect customers, reduce losses and lower the costs of chargeback management.

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Uniquely positioned to deliver real-time or near-real-time fraud detection

ACI is present in every part of the payments value chain, providing fraud solutions to issuers, acquirers, processors, switches and merchants. This enables us to support an information exchange that benefits all parties.

ACI ReD Fraud Xchange is the only multi-directional data sharing service, enabling issuers to both send information to, and receive information from, the online merchant community. Data can be exchanged many times a day, enabling a timely and effective response to suspicious transactions.

ReD Alerts
Benefits to Issuers
  • Reduces the resources and costs associated with managing chargebacks and handling account validation requests from merchants
  • Delivers a direct return on investment through the identification of fraudulent transactions
  • Enables the issuer to write rules on merchant data and further refine fraud strategies
  • Enables the issuer to be proactive in alerting cardholders and protecting them against fraud
  • Increases cardholder confidence and improves cardholder relationships.

Benefits to Merchants
  • Refund transactions associated with retrospectively identified fraud
  • Stop / suspend delivery of goods still within the fulfilment process, for orders now considered at risk
  • Remove a transaction from the chargeback process
  • Remove / suspend credit associated with accounts linked to fraud
  • Blacklist data associated with ‘at risk’ transactions, to improve future fraud detection
  • Spot trends on straight accept / deny models when manual reviews are not in scope
  • Identify fraud trends and provide evidence to support changes in fraud strategy
  • Improve the accuracy of chargeback forecasting