How to Improve Payment Integrity Strategies

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Summary

Improving payment integrity strategies involves creating systems and processes that prevent fraud, detect irregularities, and maintain financial accuracy in transactions. By identifying vulnerabilities and implementing proactive measures, businesses can safeguard their financial operations from evolving threats.

  • Assess risk areas: Regularly review transaction data and operational touchpoints to identify vulnerabilities, prioritize high-risk areas, and allocate resources accordingly to mitigate risks.
  • Establish robust internal controls: Implement segregation of duties, authorization hierarchies, and detailed record-keeping measures to reduce fraud opportunities and create accountability within financial processes.
  • Use real-time monitoring tools: Leverage advanced technologies such as AI for real-time pattern detection, adaptive learning, and minimizing false positives to prevent fraud in faster payment systems like real-time payments (RTP).
Summarized by AI based on LinkedIn member posts
  • View profile for Brian D.

    safeguard | tracking AI’s impact on payments, identity, & risk | author & advisor | may 3-6, CO

    17,642 followers

    If my boss asked me to "assess our risk surface area and fraud priorities", this is how I would get it done by 5PM tomorrow. Step by step process. 1 - Pull our last 90 days of fraud data. Not just the obvious stuff like chargeback rates, but the full spread: login attempts, account creation patterns, payment declines... everything. Why 90 days? Because fraudsters love to exploit seasonal patterns, and we need that context. 2 - Map out every single entry point where money moves. I'm talking checkout flows, refund processes, loyalty point redemptions... even those "small" marketing promotion codes everyone forgets about. (Fun fact: I once found a six-figure exposure in a forgotten legacy gift card system) 3 - Time for some real talk with our front-line teams. Customer service reps, payment ops folks, even the engineering team that handles our API integrations. These people see the weird edge cases before they show up in our dashboards. 4 - Create a heat map scoring each entry point on three factors: → Financial exposure (how much could we lose?) → Attack complexity (how hard is it to exploit?) → Detection capability (can we even see it happening?) 5 - Cross-reference our current fraud rules and models against this heat map. Brutal honesty required here – where are our blind spots? Which high-risk areas are we treating like low-risk ones? 6 - Pull transaction data for our top 10 riskiest areas and run scenario analysis. If fraud rates doubled tomorrow, what would break first? (It's usually not what leadership thinks) 7 - Document our current resource allocation vs. risk levels. Are we spending 80% of our time on 20% of our risk? Been there, fixed that. 8 - Draft a prioritized roadmap based on: → Quick wins (high impact, low effort) → Critical gaps (high risk, low coverage) → Strategic investments (future-proofing our defenses) 9 - Prepare three scenarios for leadership: → Minimum viable protection → Balanced approach → Fort Knox mode Because let's be real, budget conversations need options. 10 - Package it all up with clear metrics and KPIs for each priority area. Nothing gets funded without numbers to back it up. ps... Make it visual. Leadership loves a good heat map, and it makes complex risk assessments digestible. Trust me on this one

  • Fraud grows unchecked without anyone noticing? That's exactly what happened to one of my clients. Because his businesses basic internal controls were non-existent, allowing a single employee to process payments, reconcile accounts, and destroy evidence without oversight. Then we helped him, here’s how: 1️⃣ Segregation of Duties – Strategically divide financial responsibilities so no single person controls multiple critical functions, creating natural checks and balances that make fraud exponentially more difficult. 2️⃣ Authorization Hierarchy – Establish clear approval thresholds and verification protocols for transactions, ensuring appropriate scrutiny based on risk and materiality. 3️⃣ Documentation Standards – Implement rigorous record-keeping requirements that create audit trails for every significant transaction, eliminating gaps where impropriety can hide. 4️⃣ Independent Reconciliation – Deploy regular account reconciliations performed by someone other than the transaction processor, catching discrepancies before they become systemic problems. 5️⃣ Periodic Internal Audits – Conduct surprise reviews of financial processes and transactions, creating accountability and deterrence through unpredictable oversight. The results?  ✅ Fraud risk reduced by 94%  ✅ Operational errors decreased by 76%  ✅ Stakeholder confidence strengthened Later, the business owner confessed: "I trusted completely and verified never. I didn't realize that internal controls aren't about suspicion, they're about creating systems that protect everyone, including honest employees." Strong internal controls make fraud difficult and detection inevitable. Weak controls create temptation and opportunity. I help businesses implement effective internal controls without bureaucratic complexity. DM "Controls" to safeguard your financial future. #internalcontrols  #finance  #accounting 

  • View profile for Soups Ranjan

    Co-founder, CEO @ Sardine | Payments, Fraud, Compliance

    35,946 followers

    The adoption of Real Time Payments will feel slow then sudden, especially in B2B payments. $18.9 trillion is a conservative estimate for RTP volume. The ROI calculation of the criminals improved dramatically since the dawn of GenAI and RTP compounds this problem. GenAI reduces the cost of creating convincing phishing emails, scams, and deep fakes. The payoff for a B2B payment can be in the low six to mid seven figures for a single transaction. We’ve already seen a spike in stolen business credentials from data leaks and hacks that lead to: 👉 Sophisticated business email compromise. Believable emails from what appears to be a company’s tech support staff. 👉 Remote access attacks. The “tech support team” taking over a screen and sending a transaction to the wrong recipient while “fixing the employee’s computer” 👉 Targeted deep fakes. Where finance ops teams are now directly attacked with fakes of internal staff, CFOs and leadership. Our clients tell us they regularly see generated documents, and deep fake attacks during their onboarding process. The volume has exploded in the past 12 months. Gen AI + Faster Payments makes B2B payments a critical potential vulnerability that gets ignored because it was once a sleepy backwater and not as high risk. That’s why it's critical to 🐟 Watch for device and behavior usage before, during and after every single customer interaction. If you can monitor their device and behavior, you can detect deep fakes and prevent a transaction from happening if the risk appears high enough. 🐟 Implement real-time transaction monitoring. If you only review transactions for fraud during cut-off windows and on batch, you’ll be vulnerable to RTP fraud and AML schemes.

  • View profile for Arthur Bedel 💳 ♻️

    Co-Founder @ Connecting the dots in Payments... | Global Revenue at VGS | Board Member | FinTech Advisor | Ex-Pro Tennis Player

    74,538 followers

    𝐇𝐨𝐰 𝐀𝐈 𝐦𝐢𝐭𝐢𝐠𝐚𝐭𝐞𝐬 𝐟𝐫𝐚𝐮𝐝 𝐢𝐧 𝐀𝐜𝐜𝐨𝐮𝐧𝐭-𝐭𝐨-𝐀𝐜𝐜𝐨𝐮𝐧𝐭 𝐏𝐚𝐲𝐦𝐞𝐧𝐭𝐬 by Visa👇 — 𝐓𝐡𝐞 𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐢𝐧 𝐀2𝐀 𝐏𝐚𝐲𝐦𝐞𝐧𝐭𝐬: ► Account-to-Account (A2A) payments are rapidly growing, with a forecasted 161% growth between 2024 and 2028. ► The fundamental characteristics of Real-Time Payments (RTP), such as speed, 24/7 availability, irrevocability, and lack of network visibility, contribute to the increasing fraud risks. ► Fraud is evolving with the growth of A2A payments, making it crucial for financial institutions to implement real-time fraud prevention strategies. — 𝐖𝐡𝐲 𝐢𝐬 𝐀𝐈 𝐂𝐫𝐢𝐭𝐢𝐜𝐚𝐥𝐥𝐲 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐢𝐧 𝐅𝐫𝐚𝐮𝐝 𝐏𝐫𝐞𝐯𝐞𝐧𝐭𝐢𝐨𝐧? ► 𝐒𝐩𝐞𝐞𝐝 𝐚𝐧𝐝 𝐀𝐜𝐜𝐮𝐫𝐚𝐜𝐲: AI enables real-time fraud detection and prevention, essential for instant payment transactions that are completed within 10 seconds. ► 𝐏𝐚𝐭𝐭𝐞𝐫𝐧 𝐑𝐞𝐜𝐨𝐠𝐧𝐢𝐭𝐢𝐨𝐧: AI can recognize patterns and detect irregularities, linked to mule accounts or changed geolocation. ► 𝐀𝐝𝐚𝐩𝐭𝐢𝐯𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: AI models adjust to new fraud trends in real-time, unlike traditional rules-based systems that require post-loss analysis. ► 𝐑𝐞𝐝𝐮𝐜𝐞𝐝 𝐅𝐚𝐥𝐬𝐞 𝐏𝐨𝐬𝐢𝐭𝐢𝐯𝐞𝐬: AI-enhanced systems provide more accurate fraud detection, reducing the need for manual reviews and minimizing false positives. ► 𝐍𝐞𝐭𝐰𝐨𝐫𝐤-𝐋𝐞𝐯𝐞𝐥 𝐕𝐢𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲: AI leverages a multi-financial institution (FI) view, enabling a comprehensive view of fraud across payment networks, which is crucial for detecting cross-network fraud schemes. — 𝐑𝐮𝐥𝐞𝐬-𝐁𝐚𝐬𝐞𝐝 vs. 𝐀𝐈-𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐒𝐲𝐬𝐭𝐞𝐦𝐬: 𝐑𝐮𝐥𝐞𝐬-𝐁𝐚𝐬𝐞𝐝 𝐒𝐲𝐬𝐭𝐞𝐦: 1️⃣ Transaction Initiated 2️⃣ Massive Volume of Transactions: High volume of transactions are flagged for manual review due to basic rule triggers. 3️⃣ Manual Review: Transactions are manually reviewed, leading to delays and operational inefficiencies. 4️⃣ Transaction Assessed: Risk is evaluated based on pre-set rules. 5️⃣ Transaction Authorized: If no rule is violated, the payment is authorized. 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬: High false positives, time-consuming manual reviews, and delays in payment processing. 🆚 𝐀𝐈-𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐒𝐲𝐬𝐭𝐞𝐦: 1️⃣ Transaction Initiated 2️⃣ Curated Volume of Transactions: AI intelligently filters transactions, reducing the volume that requires review. 3️⃣ AI-Assisted Review: Transactions are reviewed with AI input, providing real-time risk assessment. 4️⃣ Data & Model Assessment: AI evaluates transactions using data patterns and predictive models. 5️⃣ Transaction Authorized: If deemed low-risk, the payment is instantly authorized. 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬: Reduced false positives, real-time risk assessment, operational efficiency, and improved customer experience. — Source: Visa — ► Sign up to 𝐓𝐡𝐞 𝐏𝐚𝐲𝐦𝐞𝐧𝐭𝐬 𝐁𝐫𝐞𝐰𝐬 ☕: https://lnkd.in/g5cDhnjCConnecting the dots in payments... and Marcel van Oost

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