Payment Fraud Prevention

If cybercrime were its own country, it would be a $8 trillion economy, larger than almost all countries on earth. That is why job #1 for me and everyone at Visa is cyber & payment security. 24x7x365 days a year we are focused on protecting cardholders, merchants and our infrastructure. We are at the very front lines in protecting payment flows and use the most sophisticated technologies, many of which we have invented ourselves – from finger printing typing/mouse movements to deep inspection of every transaction in near real time. We have thousands of the best engineers in the world working on this across every major time zone, and our multiple operations command centers monitor every aspect of the payment flow and our global infrastructure. On a normal day we collect and analyze billions of data points and use the most sophisticated AI techniques to assist us in ensuring the security of the ecosystem we are so privileged to serve. On Cyber Monday this year, we blocked 85% more suspected fraud globally compared to last year. Our newest tools like Visa Account Attack Intelligence Score, which launched earlier this year, leverages gen AI to stop enumeration attacks even before they commence. Last year we proactively blocked $40B of suspected fraudulent transactions, and our focus on continued investment is relentless and reflected in the $11B we have spent on this over the last 5 years. With that said, the hackers are not resting. They are using cutting edge tools, AI and other social engineering techniques to try and scam you directly. The best way to stay protected is to be aware of these methods, remain vigilant and ensure you are practicing good cybersecurity habits: - Always activate every alert on all your accounts – bank, cards, emails, social media, etc. - Always have strong passwords, change them regularly and don’t use the same credentials on different sites. Ideally use a good password manager. - Activate multi-factor authentication (MFA), and better still, use authenticators from reputable companies like Microsoft, Google, or Symantec. Passkeys are another form of MFA and are supported by many organizations including Visa. Passkeys eliminate passwords and are phishing-resistant. - Lock down money transfers in your bank/brokerage accounts when you are not planning to transact. - Establish SIM PINs with your telecom providers. - Do not click on hyperlinks in emails and text messages from anyone unknown - Use a good antivirus/anti malware on your devices - Keep your applications and operating system always up to date and patched - Always confirm legitimacy of the site you are on and it is a secure ‘s’ connection (ensure the url begins with https://) As we approach peak shopping season, I encourage everyone to be aware of the latest threats and read the recent report published by Visa (link in the comments). Please stay safe and enjoy the holidays. Rest assured we will be working behind the scenes to do our part to protect you 24x7.

Financial crime compliance (FCC) remains a critical priority for financial institutions, requiring robust controls, governance, and regulatory alignment. The Financial Crime Guide (FCG) 2025, published by the UK Financial Conduct Authority (FCA), offers a comprehensive framework for firms to strengthen their financial crime risk management, covering money laundering, fraud, bribery, sanctions, insider trading, and market manipulation. Key Takeaways ✅ Governance and Senior Management Responsibility • Firms must establish a clear governance structure where senior management actively oversees financial crime risks. • Boards and risk committees should regularly review financial crime reports and escalate key concerns. • Financial crime risk must be integrated into corporate risk management, with dedicated MLROs ensuring compliance. ✅ Risk-Based Approach & Compliance Framework • Firms must continuously assess their exposure to financial crime risks across products, services, customers, and jurisdictions. • A proactive risk assessment model should be in place, using data-driven insights and regulatory intelligence. • EDD is required for high-risk entities, such as PEPs and businesses in high-risk sectors. ✅ Money Laundering & Terrorist Financing Controls • Real-time transaction monitoring must detect unusual patterns, particularly in cross-border payments and digital assets. • Strong KYC and CDD processes are required to UBO. • Firms should leverage AI-driven AML analytics to track complex laundering networks and illicit flows. ✅ Fraud Prevention & Data Security • Firms must strengthen internal controls to detect fraudulent transactions and mitigate risks from synthetic identity fraud and cybercrime. • Cybersecurity measures should align with the NCSC, GDPR, and UK ICO guidelines to prevent data breaches and financial fraud. • A zero-trust security model is encouraged, with continuous monitoring of internal and external fraud risks. ✅ Sanctions, Asset Freezes & Proliferation Financing • With evolving geopolitical risks, financial institutions must align their sanction screening tools with FATF, OFSI, and EU sanction lists. • Compliance teams must detect and prevent trade-based money laundering (TBML) and ensure crypto asset compliance against sanctions circumvention tactics. • Third-country correspondent banking relationships must undergo stringent due diligence and ongoing risk monitoring. Strategic Actions for Compliance Leaders 🔹 Automate financial crime controls—AI-driven compliance tools improve fraud detection, sanctions screening, and transaction monitoring. 🔹 Enhance regulatory engagement—proactive collaboration with FCA, FATF, and JMLSG ensures alignment with evolving compliance expectations. 🔹 Integrate cybersecurity and financial crime risk strategies—given the rise in cyber-enabled financial crime, firms must merge cyber risk governance with FCC protocols. #FinancialCrime #Compliance #AML #Sanctions #CyberRisk

The Wolfsberg Group has issued a new Statement on Monitoring for Suspicious Activity (MSA). The statement recognises that criminal networks “continue to evolve at a rapid pace.” As a result, both national security priorities and financial institutions’ innovation governance frameworks must evolve accordingly. It makes a significant distinction between: ↳ Transaction Monitoring (TM) - rule-based, transaction-focused, and heavily reliant on fixed thresholds. ↳ Monitoring for Suspicious Activity (MSA) - data-driven, outcome-focused, and informed by a broader set of inputs: • customer behaviour • typologies • contextual risk indicators • and transactional activity combined Traditional TM detects pre-defined transactional patterns - such as cash structuring or high-value wire transfers. But many risks cannot be identified through transactions alone. The Wolfsberg Group highlights that real suspicion often emerges when transactions are viewed in context - alongside customer profiles, behavioural patterns, and known typologies. 𝗪𝗵𝗮𝘁 𝗿𝗶𝘀𝗸𝘀 𝗱𝗼𝗲𝘀 𝘁𝗵𝗲 𝗪𝗼𝗹𝗳𝘀𝗯𝗲𝗿𝗴 𝗚𝗿𝗼𝘂𝗽 𝗵𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁? → Financial institutions relying solely on rules-based TM may be missing high-impact risks. → Innovation is slowed by governance frameworks designed for prudential risk, not financial crime. → Low-quality alerts and SARs continue to burden investigators and add limited value to law enforcement. 𝗪𝗵𝗮𝘁 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 𝗱𝗼𝗲𝘀 𝘁𝗵𝗲 𝘀𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱? The Wolfsberg Group outlines a transition framework based on three pillars: 1️⃣ 𝗧𝗿𝗮𝗻𝘀𝗶𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻: FIs should update their approach based on redefined outcomes - not legacy system performance. The goal is to improve precision and relevance, not to replicate outdated alerts. 2️⃣ 𝗕𝗮𝗹𝗮𝗻𝗰𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹 𝗿𝗶𝘀𝗸 𝘄𝗶𝘁𝗵 𝗳𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗰𝗿𝗶𝗺𝗲 𝗿𝗶𝘀𝗸: AML models should not be governed like credit or market risk models. Financial crime risks require adaptability, and excessive oversight can hinder timely implementation. 3️⃣ 𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Institutions must be able to clearly explain how models work, what risks they cover, and how analysts can use outputs to support meaningful investigations. 𝗪𝗵𝗮𝘁 𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁𝘀 𝗰𝗮𝗻 𝗳𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗶𝗻𝘀𝘁𝗶𝘁𝘂𝘁𝗶𝗼𝗻𝘀 𝗲𝘅𝗽𝗲𝗰𝘁 𝗯𝘆 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗶𝗻𝗴 𝘁𝗵𝗲𝘀𝗲 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀? ✔ Better alignment with law enforcement priorities ✔ Improved quality of suspicious activity reporting ✔ More effective use of data and analytics across the institution ✔ Stronger ability to detect emerging risks - not just known patterns The message is clear: Effective financial crime monitoring is no longer about catching what’s obvious. It’s about uncovering what’s relevant. Is your institution prepared for this change?

🚨 Major Fraud in ICICI Bank Fixed Deposits A former ICICI relationship manager at the Kota DCM branch has been arrested for siphoning off ₹4.58 crore from 110 FD accounts belonging to 41 customers over more than two years (2020–2023), diverting the funds into the stock market where the entire amount was lost. Key concerns: Internal control failure: Fraud went undetected for years. Customer impact: Devastating financial loss for many trust-bound investors. Regulatory oversight: Signals urgent need for stronger audit protocols and real-time monitoring. This case underlines the importance of: 1. Rigorous internal audits and oversight in banking institutions 2. Transparent customer communication regarding FD issuance and statements 3. Prompt escalation mechanisms for suspected irregularities 👉 As banking professionals, investors, and regulators, we must advocate for stronger safeguards, meaningful transparency, and strict accountability to rebuild trust and protect investors. What steps do you think banks and regulators should take to prevent such incidents in the future?

You just had a HIPAA breach? Breathe.....then move fast! (Save this post for the future) When protected health info (PHI) leaks, the first 24 hours will most likely determine if you’ll be remembered for chaos or competence. So today, I have brought you a simple blueprint I'd follow 👇🏾 1. Quickly isolate the affected systems, lock down access, and kick off a forensic investigation so you know what, when, and how; before attackers erase the breadcrumbs. 2. Document the nature of the PHI, who touched it, whether it was actually viewed/acquired, and how much you’ve mitigated so far. If the probability of compromise isn’t “low,” it’s officially a reportable breach. 3. Notify every affected individual “without unreasonable delay” and absolutely no later than Day 60. If the breach hit 500+ people, please make sure to tell HHS and the media at the same time. If fewer than 500 were impacted by the breach, you'll only need to log it and include it in your annual HHS report. 4. HIPAA spells out the must‑haves: what happened, which data types were exposed, the steps people should take, what you’ve done to plug the hole, and a hotline/email for questions. Bonus points if you provide for free credit‑monitoring codes to those impacted. 5. Lastly, please patch the root cause, retrain staff, and update policies, then keep every action in a breach file. Good‑faith compliance radically lowers penalties and proves you’re serious about protecting patient trust. Remember that a clear, rehearsed response plan buys you time, credibility, and in many cases, millions in avoided fines. Check out #kiteworks full guide for more information. https://lnkd.in/em-zaBcs

Next-Level AI Prompting for Forensic Accounting Here are 5 advanced yet practical prompting techniques you can use to get sharper, more investigative outputs from AI. Perfect for fraud examiners, auditors, and forensic professionals. 1️⃣ Chain of Thought Prompting Guide the AI step-by-step for deeper analysis. Great for tracing root causes, intent, or layered logic. Example: “Step-by-step, assess whether these ledger anomalies suggest intentional concealment or accounting error.” 2️⃣ Role Switching for Perspective Analysis Make AI simulate different viewpoints: auditor, suspect, regulator, for better risk triangulation. Example: “As a fraud examiner, list red flags in this purchase trail. Now, as the perpetrator, explain how you'd justify them.” 3️⃣ Constraint-Based Prompting Set boundaries like legal limits, timeframes, or financial thresholds to get realistic answers. Example: “Within Indian anti-corruption law and a ₹50 lakh threshold, identify 3 audit trail gaps in this case.” 4️⃣ Multi-Modal Prompt Linking Use tables, images, or docs as inputs for audit reviews or voucher testing. Example: “Using the attached audit table, flag entries where supplier payments exceed contract terms or approved limits.” 5️⃣ Prompt Stacking for Complex Analysis Chain multiple prompts to build deeper insights, case narratives, or fraud models. Example chain: → Extract unusual cash flows → Explain how they may relate to money laundering → Draft a preliminary fraud risk note ✨ Bonus Micro-Tip: Add structure to your prompt: • “Use a formal tone for report inclusion” • “Rank by severity” • “Limit to 150 words in bullet points” — #ForensicForesight #AIinAccounting #FraudInvestigation #ForensicAccounting #PromptEngineering

Welcome to 𝐓𝐡𝐞 𝐏𝐚𝐲𝐦𝐞𝐧𝐭𝐬 𝐀𝐜𝐚𝐝𝐞𝐦𝐲 by Checkout.com — Episode 6 👋 𝐓𝐡𝐞 𝐓𝐲𝐩𝐞𝐬 𝐨𝐟 𝐅𝐫𝐚𝐮𝐝 𝐢𝐧 𝐏𝐚𝐲𝐦𝐞𝐧𝐭𝐬: ► Fraud in payments is a growing challenge for merchants, issuers, and payment processors. Fraudulent transactions not only cause financial losses but also damage a merchant’s reputation ► To combat fraud effectively, businesses must leverage fraud detection tools, authentication techniques, and dispute management strategies to stay ahead of bad actors while maintaining a seamless customer experience — 𝐓𝐡𝐞 𝐓𝐲𝐩𝐞𝐬 𝐨𝐟 𝐅𝐫𝐚𝐮𝐝 & 𝐄𝐱𝐚𝐦𝐩𝐥𝐞𝐬 ► 3-𝐏𝐚𝐫𝐭𝐲 𝐅𝐫𝐚𝐮𝐝 – This occurs when a fraudster uses stolen card details to make purchases. ► 𝐅𝐫𝐢𝐞𝐧𝐝𝐥𝐲 𝐅𝐫𝐚𝐮𝐝 – A cardholder disputes a legitimate transaction, either by mistake or to reverse a purchase. ► 𝐆𝐨𝐨𝐝 𝐅𝐚𝐢𝐭𝐡 𝐏𝐚𝐲𝐦𝐞𝐧𝐭 𝐃𝐢𝐬𝐩𝐮𝐭𝐞𝐬 – The customer disputes a payment due to issues with product quality or fulfillment. Fraud prevention strategies must be tailored to identify, assess, and respond to these types of fraud in real time. — 𝐓𝐡𝐞 𝐏𝐫𝐨𝐜𝐞𝐬𝐬: 𝐂𝐮𝐭𝐭𝐢𝐧𝐠 𝐃𝐨𝐰𝐧 𝐨𝐧 𝐂𝐚𝐫𝐝 𝐅𝐫𝐚𝐮𝐝 1️⃣ 𝐅𝐫𝐚𝐮𝐝 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧 𝐄𝐧𝐠𝐢𝐧𝐞𝐬 – These tools analyze transaction data (e.g., IP addresses, device data...) to assess fraud risks. 2️⃣ 3𝐃 𝐒𝐞𝐜𝐮𝐫𝐞 𝐀𝐮𝐭𝐡𝐞𝐧𝐭𝐢𝐜𝐚𝐭𝐢𝐨𝐧 – Adds an extra layer of protection by requiring customer verification for high-risk transactions. 3️⃣ 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 & 𝐀𝐈 – Predicts fraud patterns based on historical transactions and behavioral analytics. 4️⃣ 𝐓𝐨𝐤𝐞𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧 – Converts sensitive payment data into tokens, reducing the risk of stolen card details being misused. 5️⃣ 𝐂𝐡𝐚𝐫𝐠𝐞𝐛𝐚𝐜𝐤 𝐏𝐫𝐞𝐯𝐞𝐧𝐭𝐢𝐨𝐧 – Strategies like real-time alerts and clear billing descriptors — 𝐓𝐡𝐞 𝐃𝐚𝐭𝐚: 𝐊𝐞𝐲 𝐃𝐚𝐭𝐚 𝐏𝐨𝐢𝐧𝐭𝐬 𝐭𝐨 𝐑𝐞𝐝𝐮𝐜𝐞 𝐅𝐫𝐚𝐮𝐝 Fraud detection relies on rich transaction data to identify suspicious activity and block fraudulent payments: ► Customer Name – Verifies the cardholder’s identity and checks for patterns of fraudulent behavior (e.g., fake names...). ► IP Address – Flags transactions from high-risk regions or locations inconsistent with the customer’s normal behavior. ► Billing Address – Used for Address Verification System (AVS) checks to confirm that the billing address matches the cardholder’s bank records. ► Delivery Address – Helps detect fraudulent transactions by assessing mismatched shipping details. ► Email Address – Identifies fraud patterns, such as disposable email addresses or emails associated with prior chargebacks. Providing complete and accurate data in payment requests enhances fraud detection and reduces false declines, improving both security and conversion rates. —— Source: Checkout.com x Connecting the dots in payments... ► Sign up to 𝐓𝐡𝐞 𝐏𝐚𝐲𝐦𝐞𝐧𝐭𝐬 𝐁𝐫𝐞𝐰𝐬 : https://lnkd.in/g5cDhnjC ► Connecting the dots in payments... and Marcel van Oost

PayPal launches Dynamic Scam Alerts for Friends & Family payments PayPal has introduced a new layer of protection for peer-to-peer transactions—Dynamic Scam Alerts, a real-time, AI-powered system that intervenes before funds are sent under the Friends & Family category. This is significant because Friends & Family payments, while convenient, are excluded from purchase protection. That makes them attractive targets for scams involving impersonation, fake listings, or coercion via social platforms. Dynamic Scam Alerts analyze each transaction in real time, scoring its fraud risk using behavioral signals, historical patterns, and metadata. Based on that risk score, users are presented with one of three outcomes: Low risk → Informational warning, minimal friction Medium risk → Stronger prompt, highlighting the option to cancel High risk → Transaction is blocked automatically, no override The system is built on adaptive models that continuously evolve—detecting new scam techniques by learning from live transaction data. This approach allows PayPal to move away from static rules and toward a contextual, decision-based framework. This marks a shift in how financial platforms handle consumer-grade fraud risk: - Risk detection is embedded directly into the user flow - Alert fatigue is minimized by tailoring the intervention - Response time is immediate, before funds move - Trust is reinforced through intelligent escalation As scams become more AI-driven, the industry is clearly moving toward upstream fraud prevention—where every transaction is assessed, and every warning is data-informed. This rollout sets a precedent for contextual, real-time protection in P2P payments. https://lnkd.in/eM-FRgTp Nicolas Pinto Sam Boboev Simon Taylor #Fintech #Payments #FraudPrevention #AI #RiskManagement #PayPal #CyberSecurity #P2P #MachineLearning #TransactionRisk #DigitalTrust

S'pore banks ramp up fight against scammers with anti-scam measures, "one-way" bank vaults. Digital banks in Singapore are creating new features to protect our life savings from scammers. DBS, OCBC, and UOB will offer a new "money lock" feature by November. Features are being developed independently to eliminate the possibility of a systemic weakness. 🔍 𝗛𝗼𝘄 𝗶𝘁 𝘄𝗼𝗿𝗸𝘀 Customers can specify a certain amount in their bank accounts that cannot be transferred out without additional authentication measures. DBS called its solution "digiVault" - customers can still make transfers digitally into this account, but not for outgoing transactions. Funds will only be accessible when they verify their identities. • [DBS] Visit bank branch with IC, passport • [OCBC] From another platform such as OCBC ATM • Other options are being explored I feel this is a good move to ensure that entire life savings don't get siphoned off in a single sitting. 🛡️ 𝗠𝘂𝗹𝘁𝗶-𝗹𝗮𝘆𝗲𝗿𝗲𝗱 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 In the meantime, banks have also rolled out anti-malware features as part of a multi-layered measure. For instance, DBS' banking app will restrict access if it detects: • Presence of malware • Ongoing screen-sharing or mirroring • Sideloaded apps with accessibility enabled We are in a pandemic of scams, and even digital-savvy users can be a victim. We can do our part by: - Educating ourselves on the latest scam tactics - Be vigilant against suspicious messages or calls - Share information about scams with friends, family In the meantime, 𝗻𝗲𝘃𝗲𝗿 install an app offered by a stranger. What are your thoughts? What more can we do to stem the current tide of scams? 𝗦𝗰𝗿𝗲𝗲𝗻𝘀𝗵𝗼𝘁: DBS email outlining new measures. --- My name is @Paul Mah and I write #EverydayTechStories. I believe everyone has a story to tell. DM me if you need help with yours. 👍 If you found this useful or interesting. 👀 See my latest posts: https://lnkd.in/gapTkh5A 🙋 Follow me on LinkedIn: https://lnkd.in/gVksGYZy 🔔 Tap bell on my profile to be notified of new posts. #scam #cybersecurity