With decades worth of expertise in designing, implementing and optimizing fraud and risk management systems for many of the world’s largest financial services providers, our perspective provides insight into effective risk and fraud management strategies.
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Using Neural Networks to Decrease Losses
Artificial neural networks have become a key tool in combatting fraud for many institutions because of their ability to evaluate current transaction data within the context of a customer’s history for indications of fraud. This document discusses custom and consortium models.
Preventing Card Fraud is More Effective Than Curing It
Innovative banks have found that technology identifying the so-called "point of compromise" (POC) is an important consideration in the fight against card fraud. This article explains why POC identification must be more widely adopted and should be accorded greater importance.
Taking Risk Managment From the Silo Across the Enterprise
Although many institutions — particularly the large national and international financial institutions — have already adopted enterprise risk management approaches, others are still using reactive rather than proactive methods of risk monitoring and detection.
The Fall of the False Positive
Measuring the success of financial institutions’ fraud departments is anything but straightforward. The traditional method has been to aim for a reduction in losses and a low false-positive ratio. Learn how institutions came to depend on false-positives and how to put them in the proper context.
