Understanding Payment Processing For Ecommerce

The PayPal, Mastercard and Visa announcements are not about agentic AI. They are about ownership of the next chapter of commerce and payments. Here is how they compare. 𝗪𝗵𝗮𝘁 𝗵𝗮𝘀 𝗯𝗲𝗲𝗻 𝗮𝗻𝗻𝗼𝘂𝗻𝗰𝗲𝗱: -   PayPal : APIs that let any AI agent pay, track shipping, issue invoices and resolve disputes without leaving the chat. -   Mastercard : Network tokens + passkeys so agents become “trusted purchasers,” with programmable rules and biometric SCA baked in. -   Visa:  Five modular APIs for discovery → checkout, including user‑set spend caps, MCC filters and real‑time approvals. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗮𝘁 𝘀𝘁𝗮𝗸𝗲? -   The payments race has always been about shaving seconds off checkout. In the agentic era, the winning time is 0 seconds, 0 clicks. Checkout disappears entirely as search, recommendation, and payment collapse into a single LLM-driven conversation. -   Whoever owns the payment credential becomes the default wallet in the loop, capturing not just the transaction, but data, interchange, and value-added services that follow. -   The players that get this right won’t just win conversions. They’ll own the customer relationship. The ones that don’t will find themselves disintermediated by someone else’s agent. 𝗧𝗵𝗲 𝗽𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹: Imagine: • A travel bot books flights, hotels, insurance and pays - no forms. • An SME sourcing agent negotiates fabric in Guangzhou and settles with a virtual card - no emails. • A grocery assistant notices the fridge is low and re‑orders - no conscious decision. Multiply that by every vertical and every consumer. That’s always‑on demand capture - and potentially trillions in incremental volumes routed through whoever provides the agent‑native rails. 𝗪𝗵𝗮𝘁’𝘀 𝗹𝗶𝗸𝗲𝗹𝘆 𝗻𝗲𝘅𝘁: 1.     Industry standards: Common schemas for trusted-agent registration, permissions, and dispute handling. 2.     Granular consumer controls: Per-transaction biometrics, spend limits, time-of-day and merchant-category restrictions. 3.     Merchant enablement: SDKs and APIs to expose real-time inventory, pricing, and loyalty programs to agents. 4.     Regulatory attention: How frameworks like PSD3, CFPB guidelines, or MAS oversight will apply to autonomous payers. 5.     New revenue models: Pay-per-call risk scoring, agent onboarding fees, premium fraud protection layers. 6.     Advanced risk infrastructure: Real-time monitoring of agent behaviour, intent detection, and adaptive risk scoring to flag anomalies. 7.     Liability frameworks: Clear rules for who’s accountable when an agent transacts incorrectly: the user, the platform, or the agent provider. The race to build the payment infrastructure for autonomous agents is underway. Expect a wave of partnerships, acquisitions, and early execution challenges as the industry adapts to a new model of always-on, agent-driven commerce. Opinions: my own 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐦𝐲 𝐧𝐞𝐰𝐬𝐥𝐞𝐭𝐭𝐞𝐫: https://lnkd.in/dkqhnxdg

A new model in Payments is emerging: 𝐓𝐡𝐞 𝐒𝐭𝐚𝐛𝐥𝐞𝐜𝐨𝐢𝐧 𝐒𝐚𝐧𝐝𝐰𝐢𝐜𝐡 Here's how it works: For decades, international payments have moved through a network of correspondent banks. Each transaction passed through multiple intermediaries, from local to international correspondents and back again, taking days and incurring fees at every step. This system worked, but it was slow, expensive, and opaque. A new model is emerging — The Stablecoin Sandwich — where blockchain replaces those intermediary layers to enable direct, near-instant settlement. Here’s how it works: → The sender initiates a transfer in fiat (for example, euros). → An on-ramp partner converts those euros into a stablecoin such as USDC. → The stablecoin moves across the blockchain, serving as the settlement medium. → An off-ramp partner converts the stablecoin into local currency (such as pesos or reais). → The recipient receives funds in their local account, often in under 30 minutes. → This hybrid flow combines the compliance and familiarity of traditional finance with the efficiency, transparency, and programmability of blockchain technology. The scale of this transformation is already visible. Stablecoin transactions now exceed $7 𝐭𝐫𝐢𝐥𝐥𝐢𝐨𝐧 annually, surpassing 50% of Visa’s global network volume: https://bit.ly/49aC07G Stablecoins are becoming a fundamental layer for liquidity management, B2B settlement, and cross-border treasury flows. An entire ecosystem is forming around this shift: → 𝐄𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 & 𝐁2𝐁: BVNK, Bitwave, and Contact are helping global merchants manage stablecoin liquidity, compliance, and treasury operations. → 𝐁𝐥𝐨𝐜𝐤𝐜𝐡𝐚𝐢𝐧 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞: Polygon Labs, Aptos Labs, and Chainlink Labs are building the rails that connect traditional payment networks with blockchain-based settlement. → 𝐖𝐚𝐥𝐥𝐞𝐭𝐬 & 𝐂𝐮𝐬𝐭𝐨𝐝𝐢𝐚𝐧𝐬: Dfns and BitGo offer programmable, secure wallet solutions designed for enterprises managing large digital asset volumes. → 𝐏𝐚𝐲𝐦𝐞𝐧𝐭 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐨𝐫𝐬: Mural Pay, Fipto and Noah are integrating stablecoin rails into existing payment stacks, bridging traditional and digital commerce. → An exciting one, Breeze is reimagining the 𝐌𝐞𝐫𝐜𝐡𝐚𝐧𝐭 𝐨𝐟 𝐑𝐞𝐜𝐨𝐫𝐝 (MoR) model with programmable, blockchain-enabled settlements that occur instantly. What's happening is not a replacement of the financial system, but an upgrade. Traditional bank accounts are evolving into wallets. Money movement is becoming programmable. Settlement is shifting from days to seconds. The Stablecoin Sandwich represents a new layer of global financial infrastructure, one that merges the reliability of banks with the speed and transparency of blockchain. Source: Fipto, CB Insights, Dawn Capital, and kudos to Arthur Bedel for this great update! 👌 Find this helpful? [𝗿𝗲𝗽𝗼𝘀𝘁] Anything to add about this subject? [𝗶𝗻𝘃𝗶𝘁𝗲𝗱 𝘁𝗼 𝗰𝗼𝗺𝗺𝗲𝗻𝘁] Nice story, Marcel. Next! [𝗹𝗶𝗸𝗲]

Building a Payment Service from Scratch - What I Learned as a Founder When we started building the payment system at takeUforward, I thought it would be simple, just integrate Razorpay/Paypal and move on. But once we went deeper, it turned into a full product within a product. Payments are about reliability, data integrity, and how gracefully your system behaves under pressure. Here’s what we learned 👇 - Don’t build only for “plans”, design for plan entities in your schema so upgrades/bundles/emi’s/future standalone offerings are easier to integrate - Support multiple validity periods within the same flow. - Implement an Adapter Pattern so gateways like Razorpay, PayPal, or Stripe can be swapped without touching business logic. - Keep a transaction_id as the single source of truth and design every API around it (create, capture, refund, audit) - Log everything, and store gateway response for future auditing - Ensure idempotency for every payment and refund API - a single retry shouldn’t double charge a user - Run all external calls async using background jobs or message queues to avoid blocking the user flow - Integrate refund callbacks with GST reversal logic to maintain accurate tax credits - Implement signature validation and webhook verification to avoid spoofed callbacks - Support EMI and split payments, each transaction linked via a parent-child hierarchy - Build monitoring dashboards for transaction latency, failure rates, and P95 response times - Use feature flags to roll out new gateways or payment logic gradually - Integrate third party sales - Integrate other product sales on our platform, manage taxes for them. These things sound overkill at the start, until you hit scale and realize why systems like Stripe and Razorpay obsess over these details. 💡 Check out TUF+ - we’ve covered OOPs/LLD over there, along with everything needed for Interview Preparation. It’s your one-stop interview prep platform for DSA, LLD, Core CS and more. Use code STRIVER to get the maximum discount, valid for the next few hours only ⏰

TL;DR: We built a transformer-based payments foundation model. It works. For years, Stripe has been using machine learning models trained on discrete features (BIN, zip, payment method, etc.) to improve our products for users. And these feature-by-feature efforts have worked well: +15% conversion, -30% fraud. But these models have limitations. We have to select (and therefore constrain) the features considered by the model. And each model requires task-specific training: for authorization, for fraud, for disputes, and so on. Given the learning power of generalized transformer architectures, we wondered whether an LLM-style approach could work here. It wasn’t obvious that it would—payments is like language in some ways (structural patterns similar to syntax and semantics, temporally sequential) and extremely unlike language in others (fewer distinct ‘tokens’, contextual sparsity, fewer organizing principles akin to grammatical rules). So we built a payments foundation model—a self-supervised network that learns dense, general-purpose vectors for every transaction, much like a language model embeds words. Trained on tens of billions of transactions, it distills each charge’s key signals into a single, versatile embedding. You can think of the result as a vast distribution of payments in a high-dimensional vector space. The location of each embedding captures rich data, including how different elements relate to each other. Payments that share similarities naturally cluster together: transactions from the same card issuer are positioned closer together, those from the same bank even closer, and those sharing the same email address are nearly identical. These rich embeddings make it significantly easier to spot nuanced, adversarial patterns of transactions; and to build more accurate classifiers based on both the features of an individual payment and its relationship to other payments in the sequence. Take card-testing. Over the past couple of years traditional ML approaches (engineering new features, labeling emerging attack patterns, rapidly retraining our models) have reduced card testing for users on Stripe by 80%. But the most sophisticated card testers hide novel attack patterns in the volumes of the largest companies, so they’re hard to spot with these methods. We built a classifier that ingests sequences of embeddings from the foundation model, and predicts if the traffic slice is under an attack. And it does this all in real time so we can block attacks before they hit businesses. This approach improved our detection rate for card-testing attacks on large users from 59% to 97% overnight. Perhaps even more fundamentally, it suggests that payments have semantic meaning. Just like words in a sentence, transactions possess complex sequential dependencies and latent feature interactions that simply can’t be captured by manual feature engineering. Turns out attention was all payments needed!

In SAP, the process of managing Accounts Receivable (AR) involves several key transactions, often carried out through the SAP Financial Accounting (FI) module. Below is a list of commonly used T-codes for Accounts Receivable in SAP: 1. Posting Customer Invoices and Payments: • FB70 – Post Customer Invoice: Used to post an invoice for a customer, which updates accounts receivable and sales revenue. • F-28 – Post Incoming Payments: Used to post a payment received from a customer (could be cash or transfer). • F-32 – Clear Customer: Used to clear open customer items (like payments or credit memos). 2. Customer Account Maintenance: • FD01 – Create Customer Master Data: Allows you to create a new customer in the system. • FD02 – Change Customer Master Data: Modify existing customer data. • FD03 – Display Customer Master Data: Display customer details without making changes. 3. Credit Management: • FD32 – Change Customer Credit Management: Used to update credit limits for customers. • FD33 – Display Customer Credit Management: Display customer credit information. 4. Customer Payments and Clearing: • F-39 – Post Payment: Manual posting of customer payments. • F-44 – Clear Open Items: Clears open customer items manually, like applying a payment to a specific invoice. 5. Account Reconciliation and Aging Reports: • F.13 – Automatic Clearing: Clears open items for customers automatically. • F-30 – Post Customer Down Payment: Used to post an advance or down payment made by a customer. • FS10N – Display G/L Account Balances: Can be used to check the balance for accounts receivable (G/L 100000, for example). • S_ALR_87012168 – Customer Open Items List: Displays open customer invoices and payments. • F.22 – Customer Aging Report: Provides a list of receivables broken down by overdue periods. 6. Credit Memos and Adjustments: • FB75 – Post Customer Credit Memo: Used to post credit memos (reduce amounts due from customers). • F-27 – Post Credit Memo for Customer: Another way to post credit memo for a customer. 7. Dunning (Reminders for Outstanding Payments): • F150 – Dunning: To create and send dunning letters to customers for overdue payments. • F150B – Dunning History: Displays the dunning history for customers. 8. Reports and Analysis: • S_ALR_87012182 – Customer Receivables Aging Report: Used to analyze aging of accounts receivable. • F-23 – Post Customer Payment and Clear: This is an alternative method for handling incoming payments and clearing. These T-codes cover a broad range of Accounts Receivable functions in SAP, from basic posting and customer account management to credit control, dunning, and reporting. However, If there is anyother T-codes, feel free to share.

Dear US Importers, The Supreme Court did not just put money back in your bank account. What they did was remove the legal foundation for a set of duties that many of you have been paying for years. The difference matters. Refunds are not automatic, they are procedural. If you want your cash back, you are going to have to go through the same channels we always use: PSCs for unliquidated entries, protests for anything still inside the statutory window, and test cases at the Court of International Trade for older entries that are already closed. Same rules, higher stakes. Your first priority should be understanding your entry universe. Open entries are the fastest path — remove the IEEPA duty through a post-summary correction and let Customs reliquidate. Liquidated entries within the protest period move into bulk protests, which will likely be held while CBP waits for headquarters guidance. The real recovery effort, and where most of the dollars will sit, is in the closed-entry population. That is a litigation-driven process at the CIT and it will take time. This is not a one-quarter event; it is a multi-year recovery program. Do not underestimate the importance of your data. Refund eligibility will depend on whether you can tie duty payments to specific entries, document what was paid, and ensure there is no overlap with drawback, transfer pricing adjustments, or other duty recovery mechanisms. Customs is not going to relax its documentation standards just because the underlying tariff was struck down. Clean records will determine who gets paid and who gets denied. Interest will accrue, and for large importers that interest component alone can become material. You also need to bring your tax department into the conversation immediately. Duty refunds are not just cash — they are prior-period cost recoveries. That means you may be looking at income recognition in the year the refund is received, potential amended returns depending on how the duties were treated, and book-to-tax adjustments that will need to be modeled. If you capitalized duties into inventory, the unwind hits cost of goods sold. If you expensed them, you may be dealing with income pickup when the refund arrives. State tax, transfer pricing, and financial statement implications all follow. This is a customs event with a tax shadow. So, no filings, no refunds. The path runs through PSCs, protests, and the CIT, and the companies that move quickly and methodically — with customs, legal, and tax aligned — will be the ones that actually recover their money and report it correctly. This is no longer a legal debate; it is an operational and financial workflow. Let's go get your money - all my love, Uncle Pete

E2E Accounts Payable steps :- Processing an Accounts Payable (AP) invoice involves several key steps to ensure accuracy, compliance, quality and timely payments. Here’s a standard workflow we can follow: 1. Invoice Receipt: • Receive the invoice via email, mail, EDI, or supplier portal. • Stamp the invoice with the receipt date (if manual). 2. Invoice Verification - Check the following: • Vendor name and address • Invoice number (unique) • Date of invoice • Purchase Order (PO) number (if applicable) • Description, quantity, and price of goods/services • Payment terms • Tax details (GST, VAT, etc.) • Ensure the invoice is not duplicated. 3. Match the Invoice: • 2-way match: (Service-based PO invoices, recurring purchases & subscriptions etc) Invoice vs. Purchase Order • 3-way match: (Material PO Invoice) Invoice vs. Purchase Order vs. Goods Receipt Note (GRN) Confirm:Quantity received = Quantity billed & Price as per PO= Price on invoice 4. Code the Invoice: • Assign appropriate GL (General Ledger) codes, cost centers, and project codes. • Ensure correct accounting treatment (capital vs. expense). 5. Approval Workflow: Route the invoice for internal approval if required (non-PO or exceptions). • Approval levels may depend on the invoice amount or department policy. 6. Enter into Accounting System: • Record the invoice in the AP module of ERP/accounting software. • Capture: • Vendor details • Invoice details • Due date (based on payment terms) 7. Schedule for Payment: • Review payment terms to determine due date. • Set for payment in the payment run. • Verify discounts for early payment, if any. 8. Make Payment: • Pay via approved mode: bank transfer, cheque, ACH, etc. • Record payment in the system. • Send remittance advice to the vendor. 9. Record & update: Record the payment in the accounting system to reflect the transaction and update the accounts payable ledger. 10. Reconcile and Archive: • Reconcile vendor statements with AP ledger. • Resolve discrepancies. • Archive invoice documents as per compliance requirements. #accountspayable #AP #APprocess #E2EAPworkflow #bestpractice #P2P #procuretopay #apsteps #workflow

If a customer is not clearing your payment in India... and you don't want to send them a legal notice, then there are two actions that you must take immediately... 1/ Go to the GST portal, and under User Services, go to "Communication Between Tax Payers" where you can create a communication with the client, putting it on record that you have not received payments against a particular invoice. This helps because when the amount is logged on to the portal, if the payment is delayed beyond 180 days after the invoice, the input credit is to be reversed... And the GST Department may take that as a record to officially send a notice and examine if your customer has reversed the GST, or made the payment. It's a way to create an additional evidence of non payment beyond just email exchanges. 2/ Send an email, where you attach your MSME Registration certificate and specify that if an MSME vendor is not paid within 45 days of the date of invoice, then as per Section 26 of the MSME Development Act 2006, there is an addition interest payable under law at the rate of 3X the prescribed RBI Bank Rate... As of now the bank rate is 5.25%, so interest is payable at 15.75% p.a., compounded monthly. At some point, you may have to send a legal notice, but people avoid sending it because they don't want to burn bridges... But doing these two things help you put more pressure on the client for payment. #casarthakahuja

🌍 Cross-border transactions are expected to reach $250 trillion by 2027, fuelled by digital transformation and financial inclusion efforts. But speed, security, and cost efficiency remain major challenges. Here are 10 strategic moves to future-proof your cross-border payment operations: 1️. Adopt ISO 20022 for Standardization: ISO 20022 adoption is no longer optional. By 2025, over 80% of global high-value transactions will use this structured format, enabling better compliance and seamless automation. 2️. Implement Real-Time Payment Systems: Instant payments are transforming B2B/B2C transactions. UPI, PIX, FedNow, TIPS, and other RTP systems are pushing for global interoperability. 3️. Leverage AI and Automation: AI-driven solutions reshape fraud detection and transaction monitoring. Gen AI in payments will drive 30-40% productivity gains in compliance and dispute resolution. 4️. Explore Blockchain and Stablecoins: Blockchain reduces settlement costs by up to 80%, while stablecoins offer transparent, borderless transfers. CBDCs will further revolutionize payments. 5️. Enhance Digital Identity Verification: Strengthening biometric authentication and decentralized identity solutions will enhance security and seamless user experiences. 6️. Expand Local Currency Settlement Options: Supporting multi-currency settlements reduces FX fluctuations and improves transaction predictability. 7️. Verification of Payee (VoP) and Confirmation of Payee (CoP): VoP ensures account details match before payment, while CoP gives payers the ability to confirm details before transaction. 8️. Prepare for Regulatory Changes: Stay ahead of evolving IP mandates, open banking, and enhanced AML/KYC rules to unlock new market opportunities. 9️. Invest in Fraud Prevention Technologies: AI-powered fraud detection and payment matching mechanisms are crucial to mitigate cross-border payment risks. 10. Embrace Embedded Finance: Integrating payments into non-financial platforms removes friction, improves retention, and drives new revenue streams. #payments #banking #crossborderpayments #fintech #is20022 #innovation #embeddedfinance #fraud #ai #blockchain #regulations #cbdc Nth Exception

VISA card settlements usually took days. But now they’re becoming INSTANT with USDC on Solana. Visa has enabled stablecoin settlement using USDC, moving money 24/7 instead of waiting for legacy banking rails to clear. Traditionally, card settlement happens on delayed schedules. T+1, T+2, sometimes longer depending on the bank, region, and cut-off times. Weekends slow it down. Cross-border makes it worse. Now replace that with real-time settlement. Funds move as soon as transactions clear. No banking hours. No multi-day float. No batch processing. Here’s what actually changed. Visa is not replacing cards. Visa is upgrading the settlement layer behind them. Instead of settling obligations through correspondent banks, Visa can settle directly in USDC on Solana. That means instant finality at the infrastructure level. Who is this for? Not retail users sending USDC peer-to-peer. This is for institutions. → Issuing banks → Acquiring banks → Large merchants → Payment processors → Cross-border payment flows This pilot is initially focused on the US and select institutional partners. But over time, it will expand to global settlement corridors where speed and liquidity matter most. Why did VISA choose Solana? A few reasons: • Low fees. • High throughput. • Near-instant finality. Stablecoins are no longer an edge case. They are becoming core financial plumbing. Payments don’t need to wait for banks to open. Treasury teams don’t need to manage multi-day settlement risk. Capital efficiency improves overnight. This is also a meaningful signal for Solana. Visa settles roughly $10T per year. So even a small % of that settling onchain translates into sustained demand for fees paid in SOL. VISA is moving to 24/7 settlement rails. And Solana is becoming part of the backend infrastructure that makes that possible. Which raises a real question. As global payments move toward instant settlement… Which banks still relying on legacy rails will be left behind? ________________________________________________________ 👋 I’m Aram, helping web3 leaders & B2B businesses grow on 𝗖𝗿𝘆𝗽𝘁𝗼 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻. ♻️ Repost this to help others in your network. 📌 Follow Aram Mughalyan for daily crypto insights & LinkedIn growth tactics.