TJ Horan

For a while now, folks at FICO have been talking about the convergence of fraud- and financial crime-fighting data, processes and systems. And with good reason—all signs indicate this direction to be the most efficient for banks, the most beneficial for customers, and the most aligned with regulation. In this blog I’ll reprise the product strategy version of the conve…

“It Could Happen to You” might be one of the cheesiest movies of the 1990s (71% on Rotten Tomatoes) but in making my fraud predictions for 2020, the title has an ominous ring to it. Unlike the movie’s lucky lottery-winning Nicolas Cage, “it could happen to you” means that you, a family member, or someone you know will be a victim of a scam or other major fraud this co…

As far as industry predictions go, perhaps surprisingly, one of mine actually came true: “2018 will be the beginning of the end for physical credit cards. However, their functionality will become even more omnipresent in our lives as more cards migrate to consumers’ mobile phones.” It’s true that more and more Americans are adopting mobile payments. In May Recode rep…

This holiday season should be a joyous one — for criminals. Holiday spending always makes it easier for fraudsters to steal your money, for two reasons. First, you may be so busy with shopping and parties that you don’t take that extra minute to scrutinize an email link that purports to come from a store or delivery service. People in a rush are also more susceptible…

For more than 25 years, the Falcon consortium has served as the world’s largest collection of payment card transaction details, consisting of the diverse fraud and non-fraud truncation assets that have spawned 80+ fraud-focused artificial intelligence and machine learning patents, with 30+ patents pending. It has provided a “force multiplier” effect that benefits cont…

This is the fifth in my series on five keys to using AI and machine learning in fraud detection. Fraudsters ensure that protecting customers’ accounts is very complex and dynamic, a challenge where machine learning thrives. For continual performance improvement, fraud detection professionals should consider adaptive technologies designed to sharpen responses, particu…

This is the fourth in my series on five keys to using AI and machine learning in fraud detection. Research shows that depth and breadth of data is more impactful to machine learning model performance than cleverness of the algorithm. It’s the computing equivalent of human experience. This suggests that, when possible, you can improve predictive accuracy by expan…

This is the third in my series on five keys to using AI and machine learning in fraud detection. As in many professional fields (medicine, law, construction, etc.), there are generalists and specialists. The same applies to the development of behavioral analytics; there are general modeling techniques and highly specialized techniques. For example, your communicati…

This is the second in my series on five keys to using AI and machine learning in fraud detection. Key 2 is behavioral analytics. Behavioral analytics use machine learning to understand and anticipate behaviors at a granular level across each aspect of a transaction. The information is tracked in profiles that represent the behaviors of each individual, merchant, acco…

Payment fraud is an ideal use case for machine learning and artificial intelligence (AI), and has a long track record of successful use. When consumers get a call, text, email or in-app messages from their card issuer asking them to validate a transaction, or informing them of fraud on their card, they may not even suspect that behind this bit of excellent customer se…

As a drumbeat of data breaches becomes the new reality — 42% of organizations breached in 2017 were breached in the past — it’s easy for consumers to throw up their hands and brace themselves for becoming a victim of identity theft or other financial crime. However, there’s an obvious step you can take to protect your personal information: Don’t give it away to fraud…

As FICO reported today, there was a 10% increase in the number of payment cards compromised at U.S. ATMs and merchants in 2017. The number of compromised card readers at U.S. ATMs, restaurants and merchants rose 8%. On the face of it, there’s nothing to celebrate in this ATM fraud data from our FICO^® Card Alert Service, which monitors hundreds of thousands of ATMs an…