Fraud Risk Consulting

🚨 Understanding L1, L2 & L3 in Transaction Monitoring (TM) Transaction Monitoring is the backbone of Fraud Risk & AML operations — but many professionals are still unclear about how the investigation workflow actually moves across L1, L2, and L3 teams. Here’s a simple breakdown 👇 🟢 L1 – First Level Review (Alert Triage) L1 analysts handle the initial screening of system-generated alerts. They: ✔ Review customer profile & recent activity ✔ Identify false positives ✔ Check for unusual patterns (IP/location/device changes) ✔ Escalate genuine suspicious behavior Goal: Close false positives quickly and send genuine alerts upward. 🔵 L2 – Deep Investigation (Case Building) L2 analysts perform comprehensive analysis to understand the real intent behind transactions. They: ✔ Trace money flow across accounts ✔ Check beneficiary linkages ✔ Perform KYC refresh + adverse media checks ✔ Identify patterns like structuring/smurfing ✔ Build a full investigation narrative Goal: Decide whether the case is clearable or needs compliance review. 🔴 L3 – Compliance Review (Final Decision) L3 teams handle the most critical part — regulatory action. They: ✔ Review L2 findings ✔ Validate suspicious behavior ✔ File SAR/STR with regulators ✔ Liaise with legal & law enforcement ✔ Suggest rule enhancements to reduce false positives Goal: Ensure regulatory compliance and protect the financial system. 🔍 In short: 👉 L1 = Screening 👉 L2 = Investigation 👉 L3 = Compliance Decision A strong TM process depends on how well these three layers work together. 💬 If you're working in Fraud, Risk, AML, or aspire to — mastering this framework is essential. #FraudRisk #AML #TransactionMonitoring #RiskManagement #FinancialCrime #Compliance #FinTech

🔍 Fraud Investigation in E-Commerce – Made Simple Every day, thousands of transactions happen online. Among them, only a few are fraudulent—but finding those is critical. Here’s how a solid fraud investigation process works 👇 1️⃣ Detection – Spotting the Unusual Automated systems scan transactions in real time. • AI/ML tools score transactions based on past fraud patterns. • Velocity checks flag things like multiple cards on one IP or too many orders in minutes. • Risk rules highlight suspicious scenarios (e.g., high-value orders from high-risk countries). 2️⃣ Data Collection – Gathering Clues Once flagged, investigators dig deeper. • Check order details, payment info, and device/browser data. • Review IP location and see if it matches billing/shipping. • Look at customer history—new account vs. trusted long-term buyer. 3️⃣ Verification – Double Checking This is where outside validation comes in. • Confirm card details with banks/gateways. • Do KYC checks for high-value orders. • Sometimes, a quick call or email to the customer clears doubts instantly. 4️⃣ Analysis – Connecting the Dots Fraud teams piece everything together: • Match with known fraud patterns. • Check blacklists for risky emails, IPs, or devices. • Watch for behavioral red flags like rushed checkout or fake-looking info. 5️⃣ Decisioning – The Call At this stage, three outcomes are possible: • ✅ Approve – Looks genuine. • ❌ Decline – Clearly fraud. • 🔄 Escalate – Needs manual review before deciding. 6️⃣ Chargeback Handling – Fighting Back If fraud slips through and leads to a chargeback: • Collect strong evidence (IP match, order history, delivery proof). • Present the case to the bank to recover lost revenue. 7️⃣ Reporting & Prevention – Learning from Every Case • Document every decision—what worked and what didn’t. • Refine fraud rules for new attack patterns. • Feed outcomes back into AI models to make detection smarter 💡 Takeaway: Fraud investigation isn’t just about blocking fraud. It’s about protecting revenue, building customer trust, and keeping online shopping safe. A proactive approach means fewer losses, happier customers, and a stronger brand. To continued wait for next post #Ecommerce #FraudPrevention #RiskManagement #Payments #Chargebacks #Cybersecurity #Fintech

🚨 AI + Font Forensics = ₹68 Lakh Tax Fraud Busted in Hyderabad 🚨 The Income Tax Department in Hyderabad recently used AI-powered font forensics to uncover a Long-Term Capital Gains (LTCG) fraud worth ₹68.7 lakh. A taxpayer claimed improvement costs from a bill dated 2002, but AI tools flagged the use of the Calibri font—which was only released in 2006–07. This inconsistency exposed the document as forged, prompting a revised ITR and additional taxes paid . 🔍 Why This Matters for Auditors & Risk Professionals 1. Innovative Forensics AI isn't just for big data and predictive insights—it’s now a frontline tool in document authenticity verification. Font analysis is a low-cost, high-impact method. 2. Red-flag Awareness It’s not enough to verify the content—verify the context. Details like font age, metadata timestamps, or even document origin can reveal fraud. 3. Regulatory Relevance Tax authorities are stepping up forensic capabilities. Expect similar methods to be applied in other regulatory areas—GST, money laundering, financial filings. 4.Upgrade Your Toolkit Incorporate similar forensic checks—font, metadata, version histories—into due diligence, vendor audits, expense claim reviews, and whistleblower investigations. ✅ Action Steps ✅ Add font & metadata analysis to your internal audit and investigation playbooks. ✅ Train teams to look beyond signatures—validate document authenticity at a granular level. ✅ Evaluate simple AI tools that can detect anomalies in fonts or document history. ✅ Share this knowledge in audit committees, risk forums, and compliance training. This case is another reminder: fraudsters adapt, but so must we. In a world where even fonts can betray deception, staying ahead requires curiosity, precision, and technology-backed scrutiny. What forensic techniques are you using to catch today’s more subtle frauds? #Forensics #Audit #RiskManagement #AI #InternalAudit #Compliance

He is a CA who has spent nearly two decades in forensic accounting. He has personally studied 1,000+ companies in India & over 300 companies globally to uncover what most investors miss. He has faced police threats, lawsuits, & even spent 2 weeks in jail for exposing a corporate fraud, yet he continues to share his findings transparently. He has identified multiple reporting blunders, including a GST fraud by inflating revenue through inter-depot transfers, as well as an interesting case of a car company claiming a fake 24-month waiting list. He is none other than Nitin Mangal, the Founder of Trudence Capital Advisors Private Limited and a veteran in the Forensic Audit space. In the latest episode of Konversation with Kushal, we went deep into the art of Forensic Research, where Nitin shared his framework for finding red flags in companies. We decoded the subtle manipulation of Closing Inventories to boost gross margins and why the Cash Yield ratio is a useful weapon for spotting scams before they blow up. We also covered real-world case studies like Stove Kraft, EaseMyTrip and Zaggle, exploring why high Related Party Transactions and selective accounting practices are major red flags. This episode is powered by Groww. #linkedin #linkedinforcreators #investing #forensicaccounting #stockmarket #wealth #kushallodha

Free Resource Friday! If 2024 has taught us anything, it’s that fraud remains one of the most critical compliance challenges we face today. From APP fraud to synthetic identity scams, money muling, and cross-border fraud, financial criminals are evolving faster than ever. For compliance professionals, fraud risk assessment is no longer optional—it’s a must-have for proactive risk mitigation, regulatory alignment, and reputational protection. 🔍 ACAMS has released a FREE best practice guide on Fraud Risk Assessment, offering: ✔️ A step-by-step methodology for conducting robust fraud risk assessments ✔️ Insights into emerging fraud threats and trends ✔️ A risk prioritization matrix to help organizations focus on high-impact risks ✔️ Strategies to break down silos and create a multi-disciplinary fraud risk approach ✔️ Real-world examples, frameworks, and a fraud risk register template 💡 Key takeaway? Fraud is not just an AML issue—it’s an enterprise-wide risk. Organizations that embed fraud risk assessments into their compliance framework will be better equipped to handle regulatory changes and reduce financial crime exposure. #FraudPrevention #Compliance #RiskAssessment #ACAMS #FinancialCrime

50 fraud experts just got scammed at their own security conference. They all fell for the same fake QR code. Here's what this reveals about AI-powered fraud in 2025: The conference was in Singapore, the global hub for anti-fraud technology. Organizers offered attendees a chance to skip the queue by scanning a QR code. It was a trap demonstrating "quishing" (QR phishing attacks). Even the world's best couldn't spot it. Jorij Abraham from the Global Anti-Scam Alliance delivered the real message: "Everybody—even you—can be scammed." Global fraud losses reached $485 billion in 2023, up 30% from 2022. Singapore alone saw scam reports double to 31,728 cases last year. These aren't hackers in hoodies anymore. They're corporate campuses with HR departments and training programs. Myanmar's KK Park alone employs 100,000 workers running fraud operations 24/7. The UN estimates 300,000 people are trafficked into cyber-slavery across Southeast Asia. AI fundamentally changed the economics of fraud. Before AI, scammers needed weeks to research victims. Now they analyze your entire digital footprint in seconds. Traditional phishing had 3% success rates. AI-personalized attacks hit 45%. The Arup case proved no company is safe: Hong Kong, early 2024. An employee joined a video call with the CFO and several colleagues discussing an urgent HK$200 million transfer ($25 million). The employee recognized everyone. Their voices matched. Their mannerisms were perfect. All of them were deepfakes. The technology gap keeps widening. Banks process fraud checks overnight. Scammers operate in milliseconds. While your bank queues your transaction for review, criminals have already moved money through 4 exchanges into untraceable assets. Legacy systems analyze 10 signals: amount, location, time. AI scammers track 1,000+ variables including typing speed, mouse movements, even how you hold your phone. Some institutions caught up with AI-native defense. TransPecos Bank replaced 8 security vendors with one platform. Within 6 weeks, they cut fraud by 90%. These platforms analyze every transaction in under 100ms—faster than a blink. They catch fraud before money moves, not after it's gone. The machine-versus-machine war has begun. Every day, AI defenders and AI attackers evolve. Fraudsters test new vectors in the morning. Defense systems adapt by afternoon. Companies relying on manual rules are bringing knives to a gunfight. Oscilar built the first unified AI-native risk solution. Sub-100ms decisions that adapt faster than fraudsters evolve. Founded by Apache Kafka's co-creator who scaled real-time data for 80% of Fortune 500s. Learn more at oscilar.com

𝐊𝐢𝐧𝐠 𝐕 𝐡𝐚𝐬 𝐣𝐮𝐬𝐭 𝐜𝐡𝐚𝐧𝐠𝐞𝐝 𝐭𝐡𝐞 𝐠𝐚𝐦𝐞 𝐟𝐨𝐫 𝐄𝐭𝐡𝐢𝐜𝐬 𝐚𝐧𝐝 𝐅𝐫𝐚𝐮𝐝 𝐑𝐢𝐬𝐤 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞. The conversation has shifted dramatically: ❌ 𝐍𝐨 𝐥𝐨𝐧𝐠𝐞𝐫: "Do you have ethics policies?" ✅ 𝐍𝐨𝐰: "Can you evidence their impact on ethical culture?" King V doesn't take your word for it. It demands tangible proof. 𝐒𝐢𝐱 𝐜𝐫𝐢𝐭𝐢𝐜𝐚𝐥 𝐜𝐡𝐚𝐧𝐠𝐞𝐬 𝐄𝐭𝐡𝐢𝐜𝐬 𝐚𝐧𝐝 𝐅𝐫𝐚𝐮𝐝 𝐑𝐢𝐬𝐤 𝐏𝐫𝐚𝐜𝐭𝐢𝐭𝐢𝐨𝐧𝐞𝐫𝐬 𝐨𝐮𝐠𝐡𝐭 𝐭𝐨 𝐤𝐧𝐨𝐰: 1. 𝐄𝐭𝐡𝐢𝐜𝐬 𝐢𝐬 𝐚 𝐛𝐨𝐚𝐫𝐝‑𝐥𝐞𝐯𝐞𝐥 𝐊𝐏𝐈: Culture indicators, leadership behaviour, and whistleblowing responsiveness are now measurable governance outcomes that require evidence-based reporting. 2. 𝐃𝐢𝐠𝐢𝐭𝐚𝐥 𝐞𝐭𝐡𝐢𝐜𝐬 𝐢𝐬 𝐚 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐦𝐞𝐧𝐭: AI-enabled fraud, algorithmic bias, deepfakes, and data manipulation are recognised as core governance risks, reflecting how fraud has evolved into digital ecosystems. 3. 𝐅𝐫𝐚𝐮𝐝 𝐫𝐢𝐬𝐤 𝐢𝐬 𝐞𝐦𝐛𝐞𝐝𝐝𝐞𝐝 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜𝐚𝐥𝐥𝐲: King V integrates fraud risk across the entire value chain, from supply chain vulnerabilities to ESG reporting integrity, making it a strategic imperative rather than an operational function. 4. 𝐋𝐞𝐚𝐝𝐞𝐫𝐬𝐡𝐢𝐩 𝐚𝐜𝐜𝐨𝐮𝐧𝐭𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐢𝐬 𝐞𝐧𝐟𝐨𝐫𝐜𝐞𝐚𝐛𝐥𝐞: Boards must demonstrate proactive consequence management, transparent conflict oversight, and ethical decision-making frameworks as governance requirements. 5. 𝐂𝐨𝐦𝐛𝐢𝐧𝐞𝐝 𝐚𝐬𝐬𝐮𝐫𝐚𝐧𝐜𝐞 𝐢𝐧𝐜𝐥𝐮𝐝𝐞𝐬 𝐞𝐭𝐡𝐢𝐜𝐬 𝐚𝐧𝐝 𝐟𝐫𝐚𝐮𝐝: The first, second, and third lines of defence must align on ethics, fraud risk, compliance, and technology controls. Fragmented assurance is a governance failure. 6. 𝐄𝐒𝐆 𝐢𝐧𝐭𝐞𝐠𝐫𝐢𝐭𝐲 𝐜𝐨𝐧𝐧𝐞𝐜𝐭𝐬 𝐭𝐨 𝐟𝐫𝐚𝐮𝐝 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞: Carbon credit fraud, greenwashing, and climate-related misstatements are explicitly recognised as ethics and fraud risks requiring governance oversight. 𝐓𝐡𝐞 𝐬𝐡𝐢𝐟𝐭: Ethics, technology, and fraud governance have converged. Organisations must demonstrate credibility through evidence, not just compliance documentation.

Key Findings from the 2025 State of #Fraud Report 🔸 Rising Fraud Incidents Across All Sectors: 60% of financial institutions and #fintechs reported an increase in fraud events targeting #consumer and business accounts in 2024. Fraud was predominantly digital, with 80% of events occurring on #online or #mobilebanking channels 🔸 Key Fraud Types: Credit card fraud, identity theft, and account takeover (ATO) #fraud were the most common types of fraud reported. 20% of enterprise #banks ranked check fraud as their most frequent fraud type. 🔸 Financial and Reputational Costs: 31% of organizations experienced fraud losses exceeding $1M in 2024. 73% ranked #reputational damage as the most severe consequence of fraud, followed closely by direct financial losses (72%) and loss of clients (72%). 🔸 Role of Organized Crime: 71% of fraud attempts were attributed to financial #criminals or fraud rings, marking a shift from first-party to third-party fraud. 🔸 Fraud #Detection and Prevention: 56% of financial organizations most commonly detected fraud at the transaction stage, while 33% identified it during onboarding. Real-time interdiction was conducted by only 47% of respondents, highlighting a gap in immediate fraud prevention. 🔸 Fraud Detection Trends: Inconsistent user #behavior (28%) and mismatched personal data (20%) were leading indicators of fraud attempts. Mid-market banks reported the highest incidence of fraud, with 56% facing over 1,000 fraud cases. 🔸 AI and Technology Adoption: 99% of organizations reported using AI in fraud prevention, with 93% agreeing that machine learning and #generativeAI will revolutionize detection capabilities. #AI was predominantly used for anomaly detection (59%) and explaining large datasets for #risk analysis (67%). 🔸 Fraud Prevention Investments: 93% of respondents indicated ongoing #investments in fraud prevention, with identity risk solutions being the most impactful (34%). Top technologies for 2025 include identity risk solutions (64%), document #verification software (49%), and voice/facial recognition systems (38%). 🔸 Regulatory Impact: 62% of organizations plan to increase fraud prevention investments in response to #regulatory scrutiny and potential #reimbursement requirements for fraud losses. Predictions for 2025: 🔆 Fraud will continue to rise, driven by increased availability of consumer data on the #darkweb 🔆 Financial institutions are expected to adopt #centralized platforms for fraud and identity risk management to enhance efficiency and reduce losses 🔆 Advanced AI tools and real-time #payments systems will remain key focus areas for fraud mitigation strategies. These findings emphasize the need for a multi-layered approach to fraud prevention, prioritizing identity verification, AI-driven analytics, and real-time interdiction

On my first day in a new role, my assignment was to recover ₦2 billion in trade receivables reported in the company's books. It seemed like an easy win But as I started digging, I found something truly shocking. About ₦1.9 billion—95% of these receivables—weren’t real. A sequence of errors had quietly taken root: Here’s What Happened: - The accountant used the accounting system to issue invoices for every customer inquiry. - But many customers never followed through with their purchases. - This meant every quote was recorded as if it were an official sale. In other cases, - Invoices were issued for contracts that were later cancelled. - Yet, these invoices were still in the system and counted as revenue. So, all these "fake" invoices showed up in Receivables. That meant they also counted as Revenue. These false entries accumulated year after year, until it got to that amount. The sad part was that it was 𝗮𝗻 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲𝗱 𝗖𝗵𝗮𝗿𝘁𝗲𝗿𝗲𝗱 𝗔𝗰𝗰𝗼𝘂𝗻𝘁𝗮𝗻𝘁 𝘄𝗵𝗼 𝗱𝗶𝗱 𝘁𝗵𝗶𝘀. The sadder part was that it was 𝗮𝗻 𝗙𝗖𝗔 𝘄𝗵𝗼 𝘀𝗶𝗴𝗻𝗲𝗱 𝗼𝗳𝗳 𝗼𝗻 𝘁𝗵𝗲 𝗰𝗹𝗲𝗮𝗻 𝗮𝘂𝗱𝗶𝘁 𝗿𝗲𝗽𝗼𝗿𝘁𝘀.   The saddest part was that the company paid taxes and bonuses on profits that never existed. Who do we blame? Undoing this mess was challenging, but it underscored some critical truths: 1. Use Quotes to address customer interest, but only an invoice represents a sale. Don’t blur the line. 2. An invoice confirms real revenue. Issue it only when the transaction is final. 3. False figures go unnoticed if no one truly checks the substance. 4. There are too many incompetent people with certificates. This experience showed me the dangers of harmful practices in th𝗲 hands of people whom we trust to handle the technical parts of their jobs. Can your Company Trust You? ...sigh #myCFOng

Fraud isn't just getting smarter. It's getting faster than your defenses. Voice cloning now takes three seconds of audio. Deepfakes are fooling verification systems. And while most companies are still playing defense, the fraudsters are already three moves ahead. I talked to Tony Brancato from Charlie Financial on the Product Thinking Podcast, and his approach to this arms race caught my attention. Instead of just building better fraud detection, he turned his customers into an intelligence network. They built systems to surface when people get hit with new scams, and forward them directly to the product team. That intelligence gets processed and shared back through newsletters and support channels, creating a real-time defense system that protects the entire customer base before threats spread. This isn't reactive customer service. It's proactive threat intelligence. The financial services industry faces an evolving battlefield where traditional security measures aren't enough. Companies that treat fraud as an afterthought will watch their customers become casualties. The winners will be those who recognize fraud prevention as a core product feature, not a compliance checkbox. They'll build systems that learn, adapt, and stay ahead of increasingly sophisticated attacks. How is your product strategy accounting for the fraud threats your customers will face tomorrow?