Real-Time Fraud Detection

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What Does Real-Time Fraud Detection Mean?

Real-time fraud detection is the real-time execution of fraud-detection algorithms in order to detect fraudulent activities on credit cards and other financial payment systems. It makes use of real-time data analysis such as forensic analytics and predictive analytics to determine if an ongoing transaction is legitimate or not.


Though the system is not perfect, it has reduced fraud losses in the U.S. by 70 percent since 1992, when real-time fraud detection was introduced.

Techopedia Explains Real-Time Fraud Detection

Fraud detection in the simplest form is simply outlier detection, which is determining whether an event such as a purchase using a credit card occurs outside of the normal circumstances or habits of the person using it.

Real-time fraud detection is just the execution of fraud detection algorithms right as the purchase is happening. The system is not perfect and a lot of false positives are captured, but this just ensures that fraud is detected immediately and possibly prevented outright.

For example, a man that has exclusively been using his credit card to purchase gadgets online suddenly purchases women’s lingerie in a store from a town far away from his home.

This would immediately register as an outlier occurrence because it deviates so much from the person’s purchasing habits, and depending on the credit card issuer, the transaction might be blocked or the person would get a call immediately afterwards from a representative in order to confirm whether the recent purchase was legitimate or not.

Before real-time systems made fraud detection instant, it used to be done in bulk with the results often arriving weeks or months after the purchase, which makes it difficult to track down the fraud or has allowed the culprit to commit many more fraudulent purchases before being detected and caught.

This was because data used to be stored on slower disks since memory was still relatively costly. But since the cost of memory has gone down significantly since the early ’90s, it has become possible to store data in-memory so that processing can happen very quickly.

Real-time fraud detection can occur in as little as 40-60 milliseconds; in comparison, a human eye blink happens in 300 milliseconds. As of today, real-time fraud detection is a very common use case in the field of big data.

At the consumer level, some top-tier antivirus software packages include identity protection and fraud detection features to prevent the user from falling victim to identity theft and other financial crimes.


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Margaret Rouse
Technology Expert
Margaret Rouse
Technology Expert

Margaret is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical business audience. Over the past twenty years, her IT definitions have been published by Que in an encyclopedia of technology terms and cited in articles by the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine, and Discovery Magazine. She joined Techopedia in 2011. Margaret's idea of a fun day is helping IT and business professionals learn to speak each other’s highly specialized languages.