AI Fraud Detection Techniques For Banks

"AI will replace fraud analysts" is the wrong conversation. Every fraud leader I talk to knows this. But they're still asking: "What can I actually do with AI today that won't freak out my team?" And the pressure is real. Here's what I'm hearing: • Boards want "AI strategy" yesterday • Teams fear being replaced • Leaders stuck in the middle • Everyone pretending they have it figured out Let's be honest... Nobody has this figured out yet. But the smartest fraud leaders I'm talking to share one approach: Small. Specific. Human-in-the-loop. That's it. That's the entire strategy that's actually working. Opportunity 1: Start with investigation summaries Don't automate decisions. Automate documentation. • Feed transaction details into your tool • Generate investigation summaries • Save 2 hours per analyst per day One team reduced case notes from 20 minutes to 2 minutes. That's 18 minutes back to catch actual fraud. Opportunity 2: Pattern detection assistant Not replacing analysis. Augmenting it. • Upload daily fraud cases • Ask: "What patterns do you see?" • Use AI to spot trends humans might miss One team found 3 new fraud patterns their rules missed. Opportunity 3: Rule writing helper The most underrated AI use case. • Describe the fraud pattern in plain English • AI drafts the rule logic • Human reviews, tests, deploys What took 3 hours now takes 30 minutes. Stop thinking: AI vs. Humans Start thinking: AI + Humans vs. Fraudsters Your people know fraud. AI knows patterns. Together, they're stronger.

Mastercard's recent integration of GenAI into its Fraud platform, Decision Intelligence Pro, has caught my attention. The results are impressive and shows the potential of “GenAI in Advanced Business Applications”. As someone who follows AI advancements in Fraud across the FSI industry, this news is genuinely exciting. The transformative capabilities of GenAI in fortifying consumer protection against evolving financial fraud threats showcase the potential impact of this integration for improving the robustness of AI models detecting fraud. The financial services sector faces an escalating threat from fraud, including evolving cyber threats that pose significant challenges. A recent study by Juniper Research forecasts global cumulative merchant losses exceeding $343 billion due to online payment fraud between 2023 and 2027. Mastercard's groundbreaking approach to fraud prevention with GenAI integrated Decision Intelligence Pro is revolutionary. - Processing a staggering 143 billion transactions annually, DI Pro conducts real-time scrutiny of an unprecedented one trillion data points, enabling rapid fraud detection in just 50 milliseconds. - This innovation results in an average 20% increase in fraud detection rates, reaching up to 300% improvement in specific instances. As we consider strategic imperatives for AI advancement in fraud, this news suggests what future AI models must prioritize: - Rapid analysis of vast datasets in real-time, maintain agility to counter emerging fraudulent tactics effectively, and assess relationships between entities in a transaction. - By adopting a proactive approach, AI systems should anticipate and deflect potential fraudulent events, evolving and learning from emerging threats to bolster security. - Addressing the challenge of false positives by evolving AI models capable of accurately distinguishing legitimate transactions from fraudulent ones is vital to enhancing overall security accuracy. - Committing to continuous innovation embracing AI is essential to maintaining a secure and trustworthy financial ecosystem. #artificialintelligence #technology #innovation

Being in the fraud prevention industry gives me an insider’s view of how fraud attacks work - including seeing new patterns emerge. Here are recent insights on how fraudsters are increasingly targeting people to take control of their bank accounts and initiate unauthorized wire transfers. 📞 The Phone Call Scam: Scammers exploit the vulnerability in PSTN to spoof caller IDs, making it seem like the call is coming from a trusted bank. A number of well-known VoIP providers make this possible. 🔓 Remote Access: Once they establish contact, scammers mention there is some suspicious activity or other important reason behind their call. They then persuade victims to install remote desktop applications like AnyDesk, or to turn on WhatsApp or Skype's screen sharing. This allows them to access banking apps and initiate transfers. This helps them to intercept login data and one-time passcodes. Banks also don't insure against such scams, leaving victims exposed. 🤖 AI in Voice Scams: Imagine combining voice recognition with GPT-based text-to-speech technology. Scammers scale their operations massively, this is a future risk we must prepare for now. So what proactive measures can banks and digital wallets take? 1. Customer Education: Many banks already do this; keeping their customers informed about official communication channels and the importance of calling back through their verified numbers. 2. One-Time Passcodes for Payments: OTPs aren’t just for logins but also useful for transactions, with detailed payment information included. 3. Being On a Call During Transactions: The top FinTechs are already looking into, or developing technology to detect if a customer is on a call (phone, WhatsApp, Skype) during banking activities. 4. Detect Remote Access: Implement detection mechanisms for any remote access protocol usage during banking sessions. 5. Behavior and Velocity-Based Rules: Sophisticated monitoring should be used to flag activities in real-time based on unusual behaviour and transaction speed. 6. Device, Browser, and Proxy Monitoring: This is a quick win, as there are many technologies available to flag unusual devices, browsers, and proxy usage that deviates from the customer's norm. 7. Multiple Users on Same Device/IP: Ability to identify and flag multiple customers who are using the same device or IP address in one way to detect bots. 8. Monitoring Bank Drops and Crypto Exchanges: Pay special attention to transactions involving neobanks, crypto exchanges, or other out-of-norm receiving parties, to identify potential fraud. Some of them might not ask for ID and even if they do, it can be easily faked with photoshopped templates. Hope you find that useful, and in the meantime, I’d love to hear what other emerging threats you’ve seen or heard of. Fostering these open conversations is what enables us all to unite together against combating fraud 👊 #FraudPrevention #CyberSecurity #DigitalBanking #ScamAwareness #AIinFraudDetection