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Can Adaptive Analytics Boost Debit Card Fraud Detection?

As frequent readers know, I'm a strong advocate for using adaptive analytics in credit card fraud detection. Some may wonder: Could the same analytic technology also boost fraud protection for debit cards? The answer: Absolutely!

First, a quick primer on adaptive analytics. These models continually "adapt" traditional neural network fraud models in response to real-time fraud tactics, some of which may have not been present during model training. This ability to learn from in-production fraud trends helps financial institutions recognize newer schemes and consequently catch more fraud.

We recently tested the value of using adaptive analytics on a FICO debit consortium model, specifically our recently released FICO® Falcon® Fraud Manager UK-Ireland Debit 12.0 model. Adaptive analytics detects 6% more fraud accounts at a 10:1 account false positive ratio (AFPR). By keeping the detection rate fixed, adaptive analytics reduces the model’s false positive ratio by more than 10%, up to a 40% account detection rate (ADR), as shown in the graphic below.

Given these performance improvements, not to mention the value adaptive analytics already brings to our Falcon credit models, FICO is introducing adaptive analytics to our Falcon debit models. Adaptive models are available today for clients of UK-Ireland Debit 12.0, and will be available later this year for our International Debit and US Debit clients. After singing the praises of adaptive analytics for years on this blog, I’m pleased that more of our clients will be able to take advantage of the benefits that these models bring.

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