![]() ![]() Social graph information can help here as well. ![]() Fraud prevention systems need to go one level up and see who victims are sending money to. ![]() There are limited fraud signals on a singular personal level. Too many systems focus only on the sender side, but this fails with RTP because real people fall for scams and authorize payments to scammers. To the second point, zooming out to look beyond a single account helps us reveal networks of scams where there are multiple victims. For example, has the user recently updated their phone number? Is the payment recipient brand new to them? Did they call customer service? All of this is important information when determining payment risk. To the first point, we have to take in all information about a user’s actions, not just the transaction. That means: 1) looking at 360° of customer activity, 2) taking in all network and linkage information to determine the fraud, and 3) automating as much of fraud detection as possible. We need to cover the gaps and monitor transaction activity all the time. Romance scams and money mule schemes are easier to operate thanks to real-time transfer and settlement of payments.Īll of this increased fraud begs the question, how do we protect customers in real time? Relying on manual reviews and traditional case management processes isn’t fast enough. AI tools help fraudsters craft phishing emails and orchestrate scams that make victims believe they’re complying with real processes from their bank. They trick users into authorizing fraudulent payments. The ever-present availability of RTP isn’t the only thing the fraudsters exploit. In fact, fraudsters know this and cleverly exploit it by attacking more on weekends outside business hours. With RTP being 24/7/365, that opens the gates for fraud 24/7/365 too. Banks are used to processing transactions-ACH transfers, wires, etc.-in batches during their business hours. It’s understandable why they feel this way. If you dig deeper though, they may also reveal they have worries about how their current systems detect fraud. Many banks today will tell you they’re more than ready to offer real-time payments. Adjusting to real-time fraud means filling the gaps Once I explain exactly how AI detects fraud in real-time-and the ability we have to scale this technology-I believe you will feel the same way. ![]() I believe if we see widespread adoption of AI in fighting real-time fraud, we can stamp down on it globally. Machine learning and AI might be tools fraudsters can exploit, but they’re also powering the fight against fraud on the front lines. But with AI tools to assist them, scammers have found ways to take advantage of real-time payments to victimize customers at unprecedented levels. The schemes, it turns out, aren’t all that different from the ones they’ve been running for years. When fraudsters see these numbers, their eyes light up and their heads fill with schemes. But faster payment platforms like Zelle already dominate the money transfer market with total transfer value glimpsing $500 billion in 2021. FedNow is one of the United States’ first true attempts to offer real-time payments at scale. At 35% CAGR, this already staggering number will only continue to rise.Ĭountries around the world are implementing real-time payment rails, if they don’t have them already. $195 billion dollars-that’s the value of real-time payments (RTPs) in 2022. ![]()
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