Alloy’s Post

𝗔𝗜: 𝗔 𝗗𝗼𝘂𝗯𝗹𝗲-𝗘𝗱𝗴𝗲𝗱 𝗦𝘄𝗼𝗿𝗱 𝗶𝗻 𝗙𝗿𝗮𝘂𝗱 #AI is revolutionizing fraud - both for attackers and defenders. From synthetic identities to generative AI, the game has changed. Discover how AI can detect and prevent fraud, turning the tide in your favor. Check out this blog on this topic https://bit.ly/3Ratewn Get in touch with us to learn about our fraud solutions here https://bit.ly/3NOle1N #InnovativeTech #ArtificialIntelligence #KOUNT #TechAgainstFraud #DigitalSecurity

Widespread adoption of AI is likely to happen rapidly. Organisations need to be reminded that AI is a double-edged sword, if in the wrong hands, this technology can provide fraudsters the tools to accelerate their fraud schemes. To fight the battle against fraudsters, organisations need to constantly stay abreast on the latest fraud trends and scams, consistently update and educate its employees against AI-assisted fraud schemes and consider adopting AI-powered tools to complement traditional methods to keep fraudsters at bay. I delve into more insights in this article: https://lnkd.in/dzNCm2Cc

AI for good? Yes, AI could play a major role in #fraud prevention in the near future. Here is an interesting overview of how AI could augment legacy fraud prevention tools in #PaymentProcessing. https://bit.ly/40qEet2

💰 “AI driven #fraud is the fastest growing aspect of identity fraud today and will be over $100b problem this year” 💰 Artificial Intelligence (#AI) is transforming finance with innovation and efficiency, but it also introduces significant challenges, particularly in fraud detection and prevention. Most financial institutions struggle to distinguish AI-generated fraud from other types, often grouping them into one category. The use of legitimate personal information combined with socially engineered email addresses and phone numbers makes detection by legacy systems nearly impossible. As AI can create synthetic, lifelike identities, preventing and addressing these frauds becomes exceptionally difficult. In this particular article, Ari Jacoby, an AI fraud expert and the CEO of Deduce, highlights the need for firms to be “relentlessly proactive” in their pursuit of preventing the continued explosion of AI-generated fraud. Financial institutions will need to lean on sophisticated RegTech and RiskTech products to create a layered program that works to identify fraudsters lingering within the existing customer base while also working to prevent new fake identities before they infiltrate. Our upcoming research report, “Generative AI in Risk and Compliance: Friend or Foe” tackles this subject head-on, exploring the key risks posed by Generative AI as well as the innovative RegTech products at the forefront of risk mitigation. Keep your eyes peeled, the full report is dropping on MONDAY, totally free to download for all Check out the full article in the comments

Fraudsters are becoming increasingly sophisticated as AI and machine learning technology becomes more accessible. Don’t miss these insights from Discover Global Network discussing common payment-related fraud schemes and how machine learning can be implemented to prevent fraud.    #DiscoverEmployee #MachineLearning #FraudPrevention #AI #Payments #Security 

Fraudsters are becoming increasingly sophisticated as AI and machine learning technology becomes more accessible. Don’t miss these insights from Discover Global Network discussing common payment-related fraud schemes and how machine learning can be implemented to prevent fraud.    #DiscoverEmployee #MachineLearning #FraudPrevention #AI #Payments #Security 

Deepfakes are fabricated videos, images, or voice recordings designed to imitate real individuals. Their creation has become alarmingly simple, with accessible apps requiring minimal technical expertise. These deceptive manipulations rely on generative AI, machine learning, and neural networks to replicate details from one source (Person A) onto another (Person B). The implications of deepfakes in financial services predominantly revolve around fraud. Criminals exploit this technology to breach video verification systems used in account access, particularly impacting Know Your Customer (KYC) processes. Fraudsters can potentially replicate biometric verifications, leading to compromised security in fintech and banking systems. Voice replication poses another risk. Scammers require only a few seconds of someone's voice, often obtained from unsuspecting individuals, to engineer sophisticated social engineering scams. For instance, they might use a child's voice to manipulate their parents into revealing personal information or transferring money. Deepfake-related threats can potentially extend to account manipulation, money laundering, and money mule schemes. The evolution of fully synthetic faces further complicates the issue by allowing the creation of accounts unattached to real individuals, rendering traditional methods of flagging transactions with stolen documents ineffective. Detecting deepfakes is a challenge due to the rapid advancements in the technology. To mitigate risks arising out of deepfakes, multifactor authentication emerges as a fundamental step, eliminating a significant portion of potential threats. Behavioral anti-fraud measures, like monitoring repetitive IP addresses or transaction clusters, also aid in detecting fraudulent patterns. Integrating multiple checks on a single platform enables a comprehensive assessment of suspicious activity. However, the nature of deepfake technology implies a persistent challenge in identifying fabricated content. Staying updated on evolving techniques and leveraging various detection sources remains crucial. #deepfakes #fraud #moneylaundering #scams #financialcrime #fincrime

Thank you Discover Global Network for this overview of machine learning and AI in the payments space. It is interesting to learn the types of payment fraud that machine learning can detect. Read the full article for insight into common payment related scams here.    #DiscoverEmployee #Payments #Security #AI #MachineLearning 

There's a surprising reason why scammers adopted AI so quickly: they hijacked the pandemic Paycheck Protection Program and funneled payouts into new fraud weaponry. We're funding Spec to help businesses fight back. https://lnkd.in/gSjqGXVi AI is supercharging fraud, but not through DeepFakes like you see in the news. Instead, neural networks and reinforcement learning allow fraudsters to reverse-engineer defenses, mimic real customers, and sneak underneath enforcement.  Tech giants like Amazon spend fortunes trying to keep up with attackers, but Spec gives the same real-time, adaptive protection to every business. It can even trap attackers in a "mirror dimension" where they unknowingly can’t transact but Spec can study their methods. That’s why we’re doubling down and leading a $15 million Series A for Spec after co-leading its $4.3 million Seed in 2021. It's built by Nate Kharrl and Patrick Chen after a lifetime of experience at eBay and ThreatMetrix. Fraudsters will only get more advanced as AI matures, but Spec will ensure its customers always innovate even faster.

Tired of chasing after fraudsters? Let’s turn the tables! Imagine AI that predicts and stops fraud before it even happens. Balachandra Kamat from Fractal talks about how one can use AI to fight fraud in a whole new way: AI learns from real data to sniff out suspicious patterns. ️ Generates synthetic data to train itself against sophisticated fraud scenarios Examines behavior to proactively pinpoint fishy activity. Constantly learning and adopting to catch evolving threats, outsmarting fraudsters. The possibilities of AI in fraud prevention are mind-blowing! It lets us take complete control, protect our stuff, and build trust with our customers. Feeling ready to armor up your business against fraud?