Voice of the Industry

False positives hurt your business more than you think

Friday 22 June 2018 08:43 CET | Voice of the industry

Businesses should consider false positives part of their fraud prevention strategy to increase sales and keep a good brand reputation. Dustin Clinard from RISK IDENT tells us how.

With so many recent data breaches leading to the rise of account takeover fraud, more and more businesses are investing in tougher fraud prevention solutions to protect profits as well as customers. But the risk of implementing stricter anti-fraud strategies or tuning a company’s fraud filters too tightly is an increase in false positives (when a fraud prevention solution wrongly flags or declines a legitimate transaction). Unfortunately, these declined purchases have a high cost for businesses in more ways than one.

1. Reduced sales and revenue

The most obvious way false positives hurt your business is that they lead to lost sales, because legitimate customers’ purchases are declined. False positives, also called false declines, cost US ecommerce companies over USD 8 billion per year, and the exorbitant number continues to rise in America as well as all over the globe.

2. Damaged reputation

More and more consumers expect a quick and smooth online purchasing experience, and declined transactions can have a detrimental effect on a business’ reputation. The good news is that the majority of customers will attempt their purchase one more time after an initial decline. The bad news? Most will abandon their purchase and blame the website if a decline happens a second time.

Unfortunately, the negative feelings felt by the declined buyer don’t just translate to one unhappy customer, especially if he or she decides to share the experience with friends or via social media — which is likely to happen following an unpleasant customer experience. Studies have shown that consumers tell an average of nine people about positive experiences with a business and an average of 16 people about bad experiences. And considering word of mouth drives 20 to 50 percent of all purchasing decisions, one unhappy customer can significantly impact future sales.

This is not something to take lightly. One customer’s unhappiness with an incorrect decline actually made headline news earlier this spring, with major outlets like the Wall Street Journal giving it coverage. Both the business and the fraud prevention company that protects said business experienced uncomfortable publicity — all because the miffed customer alerted the media and shared the story that he was denied a headphone purchase due to an algorithm that incorrectly flagged him as a fraudster (thus, resulting in a false positive).

3. Lost customer relationships

Not only can false positives frustrate legitimate customers and threated brand reputation, they can lead to lost customers altogether. It’s been estimated that 89% of consumers will begin doing business with a competitor following a poor customer experience. That is the majority of customers, meaning a friction-free checkout process and accurate fraud flags are of the utmost importance.

Reducing false positives

Surprisingly, though false positives have a detrimental impact on businesses, they’re not often fully considered in the vast majority of fraud prevention operations. Many companies are increasingly employing technology to automate the accept or decline process without understanding the nuances created by these mechanized algorithms and fraud prevention settings. In fact, a recent study shows that only 29% of fraud teams measure false positives as team KPIs (key performance indicators).

Part of the problem is that, by nature, false positives are difficult to measure. When a system flags a transaction as fraudulent, the fraud manager or the automated system usually rejects it without further research into the transaction.

Because false positives are so hard to detect, it’s especially important that companies implement proper intelligent software as part of its fraud prevention strategy. The most effective solutions are backed by a vast pool of high-quality device information and can be fine-tuned to deliver exceptionally accurate results — thus reducing the frequency of false declines.

RISK IDENT’s products, for example, leverage the device identification information from billions of transactions within the Otto Group — one of the world’s largest online retailers. This allows for precise risk assessment of transactions without the need of overly strict rule settings. The company’s products were also engineered with the increasingly ubiquitous account takeover in mind; the FRIDA Fraud Engine delivers two risk scores: the traditional measure of the likelihood that a transaction is fraudulent or not and a separate score that predicts the likelihood that an account has been compromised. The double scoring model gives fraud managers a heightened sense of the transaction activity at hand, which can also help keep false positives at bay.

To find out more about how RISK IDENT can help your business lower false positives, contact our team today at contact@riskident.com.

About Dustin Clinard

Dustin leads RISK IDENT’s business expansion in the United States and is responsible for all US-based customers, products, and services. As Managing Director, he gets the best of both worlds – working with an all-star team and working on interesting fraud problems. Prior to RISK IDENT, Dustin has held senior leadership roles in the services, manufacturing, and engineering industries. He has consulted to some of the world’s biggest and best companies, expanded businesses continentally, and been a seed investor in an ecommerce company. Dustin has an MBA from Northwestern’s Kellogg School of Management.


Result-driven fraud prevention solutions engineered by RISK IDENT protect global e-commerce, telecommunication and financial businesses. Reducing identity theft, account takeovers, payment fraud, and account/loan application fraud on all channels is made simple with cost-effective products that use extensive domain knowledge and machine learning technology tailor made for tier-one enterprises.

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Keywords: Dustin Clinard, Risk Ident, false positives, machine learning, fraud prevention, fraud management, ecommerce
Countries: World

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