DataVisor’s Post

Did you know synthetic identity fraud accounts for about $20-40 billion losses per year, and is growing at about 10% annually, surpassing credit card fraud and identity theft? 🪪 💼 This type of fraud, easy and cheap to create especially since the advent of GenAI, generally does not affect individuals, but businesses are extremely vulnerable to it as they lack the right customer check systems to protect against them. 💳 Fake customers will just be created, build credit slowly, and then get away with a large unpaid expense. 🥊 But all is not lost - You can fight AI with AI. If generative AI can create fictitious customer identities more easily, discriminative AI can also detect pattern variations. You, as a customer data owner, have the advantage because the fraudster does not know your customers as well as you do (unless you had a data leak but then you have a bigger problem to solve). 🚩 The right AI can be an effective police force, by flagging what data signatures do not build a credible proof of a customer profile. DataGenesis has the power to build fraud detection profiles from your customer data: Build a Synthetic Digital Twin for your demographic segment, blend it with your customer data, and make it feed your detection algorithm. Ask us how! ➡️ https://lnkd.in/gV-YMiBj #datagenesis #syntheticidentityfraud #frauddetection

Let's face it: Criminals are using AI to create entirely new kinds of scams. But AI isn't just for bad guys: One study shows that 83% of fraud fighters plan to add #GenAI tools. SAS' David Stewart tells Bank Info Security how fraud fighters are responding, and what might come next. http://2.sas.com/6048W5YUp

𝗔𝗜 𝘁𝗼𝗼𝗹𝘀 𝗵𝗲𝗹𝗽𝗲𝗱 𝗧𝗿𝗲𝗮𝘀𝘂𝗿𝘆 𝗿𝗲𝗰𝗼𝘃𝗲𝗿 𝗯𝗶𝗹𝗹𝗶𝗼𝗻𝘀 𝗶𝗻 𝗳𝗿𝗮𝘂𝗱 𝗮𝗻𝗱 𝗶𝗺𝗽𝗿𝗼𝗽𝗲𝗿 𝗽𝗮𝘆𝗺𝗲𝗻𝘁𝘀 This headline caught my attention since Fraud Avoidance is a big part of my job. How Data and AI Are Revolutionizing Fraud Detection Fraud prevention isn’t just about mitigating risks—it’s about creating trust in the systems we rely on every day. Recent advancements in data analytics and AI-driven tools are proving to be game-changers. For instance, the U.S. Treasury recently announced that enhanced fraud detection efforts, including risk screening and check fraud detection, helped recover over $4 billion—a testament to the power of technology in safeguarding public funds. 💡 How does data and AI contribute to these successes? 1️⃣ 𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗥𝗶𝘀𝗸 𝗦𝗰𝗿𝗲𝗲𝗻𝗶𝗻𝗴: AI models quickly identify anomalies in transactions, flagging suspicious activities before they escalate. 2️⃣ 𝗣𝗮𝘁𝘁𝗲𝗿𝗻 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻: Machine learning algorithms sift through vast datasets to detect trends and hidden patterns often missed by manual processes. 3️⃣ 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗜𝗱𝗲𝗻𝘁𝗶𝘁𝘆 𝗩𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻: AI ensures robust identity checks, reducing cases of identity theft or false claims. 4️⃣ 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀: By analyzing historical fraud cases, AI can predict potential vulnerabilities and help organizations implement preventive measures. Beyond financial savings, these tools help rebuild trust and confidence in public and private institutions. As we integrate these technologies into fraud prevention strategies, we can better protect consumers, businesses, and governments from evolving threats. Let’s keep the momentum going—what are your thoughts on how AI and data can further enhance fraud prevention efforts? 🚀 #AI #DataAnalytics #FraudPrevention #RiskManagement #Innovation https://lnkd.in/evTMsHm4

AI-generated deepfakes is a concerning topic that needs much bigger attention than it has now. Deepfakes are getting harder to detect by day and more human awareness and attentiveness is required to avoid falling victim to this type of fraud. Thank you Alex Kosik for bringing extra awareness about the issue! At Brightside AI we focus not only on technological but also on psycological protection as deepfakes are all about making the victim believe.

🚀 Breaking News: DeepSeek AI Revolutionizes Fraud Detection! 🛡️ Join this #DEFEND webinar to understand how DeepSeek AI’s release is transforming the battle against financial fraud.  🔍 Discover: ➡️ DeepSeek AI's Impact Explore how this groundbreaking model release is changing the game for fraud detection and the new attack vectors it unlocks. ➡️ AI Agents Learn how deploying AI agents can provide faster, more accurate fraud detection while addressing data privacy concerns. ➡️ The New Fraud Benchmark See why a holistic fraud assessment approach is necessary to proactively tackle fraud. ➡️ Emerging Trends and Strategies for 2025 From AI-driven scams and first-party fraud to deepfake threats, identity fraud, and the regulatory shifts of the new administration, gain actionable insights and strategies to stay ahead and build a resilient fraud prevention framework for the future. If you only attend one webinar, this is the one. We're bringing together industry leaders that you can trust for practical insights for 2025: ⭐️ Frank Badalamenti (PwC) ⭐️ Ian Mitchell (Mission Omega) ⭐️ Trace Fooshée (Datos Insights) ⭐️ Yinglian Xie (DataVisor) Limited spots remain! 🗓️ Wed. Jan. 29  🕒 11 am PT / 2 pm ET 🔗 Register here: https://lnkd.in/g-umu7FB #DeepSeekAI #FraudTrends #CyberRisk #AMLCompliance #Fintech #DataVisor

Fraudsters move fast — is your organization equipped to keep up? Organized fraud groups are leveraging new tools and technologies to perpetrate fraud schemes at speed and scale. They are using the same tools FIs are using to fight those very fraud schemes. AI, machine learning and predictive analytics are how FIs of all sizes gain their edge. Fraud and risk managers must have access to tools and data that help them do their jobs better and faster. To do so, FIs need better data analysis capabilities, enhanced card risk visibility and faster risk detection. You also need trusted fraud experts who can help you make sense of all that data and recommend fraud rules tailored to your specific fraud risks: https://lnkd.in/den4_EkP Not sure where to get started? Our team of data and fraud experts can help: https://lnkd.in/gzrvVC4Y #fraudmitigation #bankriskmanagement #bankfraud #fraudtools #frauddetection #banking #creditunions #phishing #paymentfraud

Fraud is as old as time—and so is the race to stay one step ahead of fraudsters. From my years on the front lines of fraud prevention to my current role as CTO, I’ve seen firsthand that AI is more than just a tool—it’s THE game-changer. Here’s why I believe AI is our strongest ally against fraud: ●Adaptive Learning: Traditional fraud detection systems rely on rigid rules and static models, which can’t keep up with rapidly evolving fraud tactics. With AI, models can update daily and adapt instantly to new threats. The result? Fewer false positives and less friction for genuine customers. ●Holistic behavioural analysis: AI doesn’t just flag suspicious transactions—it understands typical financial patterns at a granular level. This allows us to detect anomalies that could indicate anything from social engineering to money mule activity, helping to stop fraud before it escalates. ●Real-time response: In today’s world of instant transactions, waiting days to detect and report fraud just isn’t viable. AI-powered systems enable real-time intervention, preventing illicit funds from disappearing into the ether. @Lynx was born to lead the fight against fraud and financial crime through advanced AI technologies. Our platform uses AI to detect fraud and money laundering in real-time and learns new fraud attacks and genuine patterns automatically. Read more in this highlighting fraud with AI article: https://lnkd.in/dBWQxtDT #FraudFighter #FraudAwarenessWeek Lynx Tech

While generative AI grabs headlines these days, a predictive AI use case is quietly delivering impact in production: AI Fraud Detection for tackling the $500B in financial fraud losses each year. We've just released Tecton's API Resources to help AI fraud detection teams harness the full power of data by frictionlessly integrating crucial signals from 3rd parties. This post shares the patterns used by leading companies to prevent identity fraud, transaction fraud, merchant fraud, money laundering, etc. and recommends essential third-party APIs that boost fraud detection model performance. Give it a read! https://lnkd.in/g8JVgEdX

 Combating Financial Fraud with Artificial Intelligence The financial industry, increasingly focused on integrating technology into its offerings, faces a persistent challenge: financial fraud. This threat looms over individuals, businesses, and economies worldwide, demanding robust countermeasures. As fraud evolves, financial institutions must leverage the latest technologies to stay ahead. One such technology is artificial intelligence (AI), which plays a pivotal role in detecting financial fraud. Fraudsters often use phishing or identity theft to access a legitimate user’s credit card details, enabling them to transact without physically acquiring the card. AI can detect anomalies in the card owner’s spending patterns and flag them in real time, providing a crucial defence against such activities. AI-powered transaction monitoring systems analyse vast volumes of financial transactions in real-time. These systems are capable of flagging suspicious activities, such as unusual spending patterns and unauthorized transactions. Through the use of rule-based algorithms and machine learning models, these systems can accurately identify and investigate potential instances of fraud. Additionally, AI-driven banking systems can build detailed 'spending patterns' of customers. By understanding these patterns, the systems can flag transactions that deviate significantly from the norm, offering another layer of protection. In conclusion, as fraudsters become more sophisticated, the financial industry must harness the power of AI to safeguard against financial fraud effectively. AI's ability to monitor, analyse, and respond to suspicious activities in real-time makes it an indispensable tool in the fight against fraud. #ai #financialcrime #financialfraud #aml

🔒 2024 Fraud Trends: How Banks & Insurers Are Fighting Back with AI Here is a report on financial fraud trends and the game-changing role of generative AI in protecting our financial systems. Key highlights: 🚨 The Scale : UK alone lost £1.2 billion to fraud in 2023 across 2.97 million cases, with 40% attributed to authorized push payment ( APP ) fraud. 🤖 AI Adoption: 2 in 3 financial organizations are already using some form of AI for security. Notably, 1 in 5 are leveraging generative AI specifically. Organizations using AI and automation security tools save an average of $2.2 million compared to those that don't. ( source : IBM ) 📱 Mobile Threats: SIM swap fraud and synthetic identity theft are emerging as major concerns, with over 80% of new acount fraud linked to synthetic identities. 🔄 Regulatory Changes : Starting October 2024, UK banks will split #APP fraud liability 50/50 between sending and receiving institutions, while #DORA compliance becomes mandatory by January 2025. 💡 Innovation Impact : Generative AI combined with network APIs is revolutionizing fraud detection, offering real-time monitoring and hyper-personalized security measures while addressing the cybersecurity skills gap. With fraudsters becoming increasingly sophisticated, how can we ensure our AI defenses evolve faster than their tactics ? Thanks to Finextra Research, Vonage, and AWS for this comprehensive analysis of the evolving fraud landscape . #FinTech #FraudPrevention #Banking #AI #Cybersecurity #PSD3 #FinancialServices #GenerativeAI #PaymentSecurity #VAS #VISA, Victor Yaromin , Sam Boboev , Neeraj Malhotra , Saleh ALhammad , Arjun Vir Singh , Nicolas Pinto , Brice GROCHE , Sandra Mianda.