A2A Payments Meet AI: How Real-Time Transfers + Instant Credit Could Revolutionise SME Finance in Southeast Asia

From Instant Payment to Instant Credit – In One Tap

Imagine you’re shopping at a local SME in Jakarta. You scan a QR code to pay directly from your bank account—instant and seamless. But what if, moments later, your phone offers you the option to convert that payment into a card-based installment plan, complete with reward points?

This isn’t a futuristic dream. With the integration of generative AI, real-time payment systems, and advanced card scheme APIs, this scenario is becoming a reality. This fusion has the potential to transform the financial landscape for consumers and small businesses across Southeast Asia.

Southeast Asia’s Real-Time Payment Boom

The region has witnessed a surge in account-to-account (A2A) payment systems:

• PayNow (Singapore): Enables real-time fund transfers using mobile numbers or NRIC/FIN numbers .
• PromptPay (Thailand): A rapid-growing instant payment service developed by Thai banks and Vocalink, a Mastercard company .
• DuitNow (Malaysia): Allows instant fund transfers using identifiers like mobile numbers or NRIC numbers .
• QR Ph (Philippines): A QR code standard facilitating quick and secure payments .

These systems are cost-effective, fast, and ideal for SMEs. However, they currently lack integrated credit options.

The Big Idea

1. Payment Initiation: Buyer pays via A2A or QR code.
2. Instant Assessment: An AI-driven underwriting engine evaluates the buyer’s creditworthiness in real-time.
3. Credit Offer: The buyer is prompted with an option: “Convert to EMI on your credit card & earn points?”
4. Transaction Conversion: Upon acceptance, a back-to-back card transaction is initiated.
5. Settlement: The buyer repays over time, while the merchant receives immediate payment.

This approach resembles Buy Now, Pay Later (BNPL) for A2A payments—but it’s smarter, safer, and more inclusive.

AI: The Matchmaker in the Middle

Generative AI combined with credit data enhances the process:

• Dynamic Credit Scoring: AI analyzes spending behavior to generate tailored offers in milliseconds.
• Fraud Protection: Integration with Visa & Mastercard’s fraud detection tools allows AI to flag suspicious activities.
• Contextual Offers: Offers are tailored based on time, merchant type, and customer behavior.
• Segmented SME Profiling: AI matches merchant categories with financing trends to create smarter campaigns.

It’s akin to having an AI-powered credit analyst in your pocket—with zero paperwork.

Benefits for SMEs

• Higher Average Basket Sizes: Consumers tend to spend more when credit options are available.
• Instant Settlements: Merchants receive full payment upfront.
• Customer Loyalty: Points, rewards, and status upgrades enhance customer retention.

Advantages for Card Networks

For card schemes like Mastercard and Visa:

• New Volume Flows: Transforming A2A transactions into card-backed spending.
• Enhanced Data & Risk Insights: Better understanding of consumer behavior and risk profiles.
• Increased Loyalty Program Engagement: Driving customer interaction with reward programs.
• Revenue Growth: Monetizing credit offerings without adding friction.

The Global Perspective: Why Southeast Asia is Poised for Transformation

• BNPL Market Growth: Southeast Asia’s BNPL market is projected to exceed $50 billion by 2027, with Indonesia leading at $16.8 billion .
• Real-Time Credit Card APIs: Visa and Mastercard have developed APIs enabling real-time credit card provisioning and transactions .
• Advanced Digital Infrastructure: The region boasts world-class digital wallets and QR payment systems.
• Cross-Border Transactions: Cross-border A2A transactions are on the rise, with initiatives linking systems like Singapore’s PayNow and Malaysia’s DuitNow .

The missing piece? A smart, AI-driven credit layer atop these systems.

Closing Thoughts: A Call to Collaborate

There’s no need to replace existing A2A or card systems. Instead, we should integrate them. By leveraging real-time data, predictive AI, and established card infrastructures, we can unlock a new paradigm in purchase financing—one that’s frictionless and low-risk.

If you’re involved in payments, lending, or fintech strategy in Southeast Asia, this could be your next significant opportunity.

Let’s connect and explore the possibilities.

Let’s get one thing straight — I’m not an AI expert.

I don’t write Python in my free time. I don’t build models in my garage. And I haven’t yet trained an AI to automate my grocery list (although, give me time).

But like many of you in the payments, tech, or digital leadership space, I’ve been incredibly curious about this wave of AI everyone’s talking about — especially Generative AI.

So, between managing work, chasing deadlines, and finding new use cases in my world of payments, I’ve been diving into courses, blogs, and real-world examples to understand how this tech can actually help in what we do.

Here’s what I’ve learned so far — not as an expert, but as a curious learner. With some sarcasm, of course. Because what’s a blog without it?

First Off: What’s the Difference Between Generative AI and Machine Learning?

Let’s break this down without turning it into a thesis.

• Machine Learning is the clever analyst in the room. You give it a mountain of data, and it tells you what’s likely to happen. Think: fraud detection, credit scoring, customer churn predictions.
• Generative AI, on the other hand, is the intern who shows up with three unsolicited logo options, a product jingle, and an entire blog post. It doesn’t just analyze — it creates.

The difference?
ML = “Tell me what’s next.”
GenAI = “Here’s something new I made — hope you like it.”

And what does GenAI create?
Practically everything:

• Marketing copy
• Email responses
• Product descriptions
• Code
• Images
• Business ideas (some of them questionable)
• And yes, even poetry — if that’s your thing

All it needs is a prompt. No coffee. No bathroom breaks. No Friday afternoon slumps.

AI Isn’t the Threat. Ignoring It Might Be.

Let’s kill the drama.

Generative AI isn’t here to take your job. But someone who learns how to use it to be more efficient, creative, and data-savvy? That person just might get promoted while you’re still resizing fonts in PowerPoint.

We’re not in a “man vs machine” standoff — we’re in the golden age of “man + machine.”

Used right, AI can:

• Write first drafts of documents
• Help you personalize marketing at scale
• Draft client proposals
• Speed up product mockups
• Summarize hours of customer feedback into usable insights

As someone working across cards, acquiring, loyalty, and alternative payments, I see GenAI playing a real role in:

• Designing smarter onboarding journeys
• Improving customer service scripts
• Rapid prototyping of new product flows
• Sales enablement content and pitch decks
• Even analyzing campaign data (so we can stop relying on “gut feel”)

Basically, it’s like having an intern, strategist, and copywriter — all in one — that works 24/7 and doesn’t ask for snacks.

But Beware: AI Hallucinations Are Real

Before we start building altars to GenAI, here’s a warning: it lies.

Not intentionally — it just sometimes gets too confident and starts making things up. This is what the cool kids call “AI hallucination.”

It might say your product was launched in 2017 when it was actually 2021. Or create a stat that sounds believable but doesn’t exist. Or worse, cite reports that were never written.

So the golden rule?
Trust… but verify.
Always apply human judgment. The tool is impressive, but it’s not a mind reader (yet).

Want to Learn About AI Without Feeling Overwhelmed?

If you’re like me — curious but allergic to tech jargon — here are some great LinkedIn Learning courses I’ve found helpful:

🧠 What Is Generative AI?
A breezy, jargon-free intro that won’t make you reach for a dictionary.

📊 AI for Business Leaders
Great for understanding the “why” behind AI without needing a technical background.

💡 How to Use ChatGPT for Work
Practical tips that can make your daily grind easier — from writing emails to brainstorming strategy docs.

⚖️ Ethics in the Age of Generative AI
Because just because AI can do something doesn’t always mean it should.

Note: You’ll need LinkedIn Premium to access these, but if you’re serious about learning and leadership, it’s worth it.

Final Thought: Curiosity > Expertise

You don’t need to become a prompt engineer overnight.

But staying curious? That’s your superpower.

Ask questions. Play with tools. Try small pilots in your team. Figure out how AI could help — not replace — your core strengths.

Because the real value of Generative AI isn’t just in what it creates…
…it’s in what you can create with it.

So, What’s Next?

If you’re exploring AI in your role — in payments, fintech, banking, or any fast-evolving space — I’d love to hear from you.

👉 Have you tried using GenAI in your day-to-day?
👉 Any surprising (or hilarious) use cases?
👉 What are you learning that’s changed your perspective?

Let’s share, laugh, and learn together.

#GenerativeAI #Payments #DigitalLeadership #AIForBusiness #LearningMindset #Fintech #Visa #Mastercard #CuriousNotReplaced

Let’s be honest — launching a new SME credit card program often feels like assembling IKEA furniture without the manual. You know it’s going to be great when done, but there are screws missing, people arguing, and someone’s yelling, “Just use UPI!”

As someone who’s spent the better part of my career in the trenches of card issuance, merchant acquiring, loyalty, and alternative payments across APAC, I’ve seen banks and fintechs alike dance around SME card programs. But the truth is — when done right — they can be absolute game-changers for banks. Not just from a “look-we-launched-a-product” perspective, but in terms of revenue, stickiness, and ecosystem play.

So how do you create a go-to-market (GTM) plan for an SME credit card that doesn’t just exist, but actually thrives?

Step 1: Fix Onboarding — Because SMEs Don’t Have Time for Your 7-Page Form

SMEs today are digital-first. They don’t want to stand in line, submit 45 documents, or wait 3 weeks for a credit decision.

Automated onboarding through API integrations (think: KYC, KYB, GST data scraping, digital credit scoring) is no longer a luxury — it’s hygiene.

Bonus points if your system integrates directly with cloud accounting tools (Xero, QuickBooks) for dynamic credit line decisions.

Step 2: Manage Risk — But Don’t Kill the Excitement

Yes, SMEs come with higher risk. But guess what? So did every startup before they became unicorns.
Smart use of:

• Virtual credit limits linked to transaction categories
• Real-time spend controls
• Supplier categorization
• Embedded insurance

…can help you build a risk-aware, not risk-averse product.

Step 3: Make It Swipe-Worthy — Spend Uplift Starts with the Right UX

An SME card should not be a “me-too” product. It should:

• Allow physical + virtual issuance (imagine a fleet manager getting virtual fuel cards in seconds)
• Enable instalments for B2B purchases
• Offer rewards that actually matter (skip the spa voucher, give cashback on logistics and SaaS tools)

Create segment-based campaign templates to target micro, small, and medium businesses differently. Your florist and your freight company have very different needs!

 Step 4: Build a Real Engagement Plan (Emails ≠ Engagement)

Want to keep your SME customers engaged? Think like a loyalty marketer.

• Integrate your card into a closed loop rewards ecosystem for everyday business spend
• Offer points-for-payments, access to business tools, and early pay discounts
• Use WhatsApp, not email, for proactive nudges (“Hey, your spend is 90% of your limit. Want a top-up?”)

And yes, webinars for SMEs are still a thing — if they come with coffee and real value.

Step 5: Drive B2B Flows On Card Rails — It’s Time to Move Away from RTGS and Cheques

Here’s where virtual cards shine. Instead of traditional banking instruments:

• Use single-use virtual cards for vendor payments
• Enable reconciliation using enriched data
• Create buyer-seller platforms where card payment is a default
  You’ll shift large B2B volumes on card rails, bringing in interchange, MDR, and precious data.

Step 6: Tackle Pricing — Dear Schemes, We Need a Heart-to-Heart

Standard SME pricing models often don’t cut it. High interchange fees can kill the use case.
Schemes need to:

• Create custom SME interchange programs
• Offer volume-based rebates to banks and issuers
• Support cross-border programs with competitive FX spreads

Let’s be real — the competition here is not another card. It’s SWIFT, and nobody’s sending a happy emoji after using SWIFT for a payment.

Step 7: Cross-Border — Hello, Global SME!

SMEs are going global. Why shouldn’t their cards?

A virtual card program with multi-currency wallets or optimized FX routing helps:

• Reduce payment costs
• Increase visibility and control
• Allow real-time reconciliations

Banks should integrate with platforms like Wise, Airwallex, or Nium — not to compete, but to collaborate. These players help banks deliver global payment capabilities without rebuilding the wheel.

Step 8: Build Your Ecosystem — You Don’t Need to Go Solo

Let’s ditch the “build everything in-house” mindset. The best GTM plans involve:

• Fintech enablers (for onboarding, risk scoring, loyalty, APIs)
• Payment processors with SME-first capabilities
• Marketing partners who understand SME lifecycle
  They’re not competition. They’re your shortcut to speed and agility.

Finally:

Banks that truly get SME cards right won’t just issue plastic. They’ll unlock new revenue lines, increase SME stickiness, and build ecosystems where SMEs thrive — with cards at the core.

It’s not just about the card. It’s about becoming the financial OS for SMEs — and if that’s not exciting, I don’t know what is.

So here’s a question for all the schemes, banks, fintechs and enablers out there:

What’s the one thing holding you back from launching your SME card program today?

Let me start with full transparency—I’ve never used tools like Gong, 6sense, or AI-powered chatbots in my day-to-day sales work.

Not because I wasn’t interested, but because my career path never demanded it. I’ve been fortunate to lead sales and business teams across Southeast Asia, working on exciting projects in issuing, acquiring, loyalty, and alternative payments. Yet, until now, AI hasn’t been a core part of my sales approach.

But that’s changing.

I’m not writing this as an AI expert—far from it. Instead, I’m sharing my early thoughts as someone eager to learn, hoping this might resonate with fellow leaders who are also just starting to explore AI’s potential in sales.

1. I Started with Questions, Not Tools

There’s no shortage of flashy platforms and software out there. But before diving into demos or buzzwords, I took a step back and asked: What sales challenges am I actually trying to solve?

• Could we qualify leads more effectively?
• Are we missing subtle buying signals in conversations?
• Could structured insights help us coach our team better?

Only after clarifying the why did I begin exploring which tools might help. For instance, I learned that Gong isn’t just a call recorder—it uncovers insights across hundreds of conversations. 6sense can identify accounts actively researching solutions before they even reach out. I’m still wrapping my head around these concepts, but the possibilities are exciting.

2. I’m Not Mastering the Tech—Just the Benefits

I’ll be honest: I don’t understand how these tools work under the hood. I can’t explain the algorithms. But I do want to grasp how they fit into real-world sales.

Right now, my mindset is simple:

→ What insights can these tools provide that I don’t already have?
→ How can they help my team sell smarter, faster, or more effectively?
→ Can they free up time so we focus less on admin and more on strategy?

I don’t need to be fluent in AI—just in how it benefits my business.

3. I Started Talking to the Right People (Finally!)

Turns out, many people in organizations are already experimenting with AI—RevOps teams, sales enablement specialists, even marketers. Once I started asking around, I realized I didn’t have to figure this out alone.

I also learned that starting small—like piloting a tool with one region or a single sales stage—is completely okay. Not everything has to be a full-scale digital transformation from Day 1.

4. I Gave Myself Permission to Be a Learner Again

This has been the most rewarding part.

Once I let go of the pressure to “know it all,” I rediscovered the joy of learning. Now, I:

• Follow insightful sales and AI voices on LinkedIn
• Read newsletters and blogs from sales tech communities
• Watch short webinars with zero expectations—just curiosity

I even set aside 30 minutes each week for unstructured learning—no pressure, no deliverables, just exploration.

5. My Mindset Is Shifting

I used to think: “AI is for someone else.”

Now I think: “If this can help me and my team grow, why wouldn’t I explore it?”

The truth is, AI isn’t about replacing people—it’s about enabling better outcomes. For leaders like me, that means staying open to new ways of thinking, selling, and engaging.

And if you’re a leader still figuring it out—I’m right there with you.

In Closing

I don’t have all the answers. I’m not even sure I’ve asked all the right questions yet.

But I do know this: Staying curious, humble, and open to learning is the best approach I can take.

There’s a quiet revolution happening in payments—and for once, it’s not coming from Silicon Valley.

London-based Curve Pay has officially stepped into the wallet wars, offering a multi-card, fee-free alternative to Apple Pay. It’s launching first on Android in the UK and Europe (with iOS coming soon), but this isn’t just another digital wallet. It’s a signal—one that could reshape pricing, payment rails, and power dynamics far beyond Europe, especially here in APAC.

So, what’s really at stake? Let’s break it down.

1. The Real Disruption: Pricing Power Shifts

For years, wallet providers like Apple Pay and Google Pay have dominated with pricing models that aren’t exactly transparent. Merchants pay blended merchant discount rates (MDRs), often with little clarity on how much goes to issuers, acquirers, or the wallet itself.

But Curve Pay is shaking things up. By pushing for fee-free NFC access (already approved in the EU, under review in the UK), it’s opening the door to more transparent—and potentially lower—costs for merchants. If more wallets can bypass toll fees and connect directly to hardware, pricing innovation will follow.

And that could force schemes and acquirers to rethink their fee structures. The days of relying on gatekeepers for protection might be numbered.

2. The Rise of Domestic Rails: RuPay, PromptPay & Local QR Codes

In APAC, where domestic payment rails like RuPay (India), PromptPay (Thailand), DuitNow (Malaysia), and Napas (Vietnam) are already thriving, Curve’s model is a wake-up call.

These local systems already offer lower interchange fees and are gaining traction in SME, transit, and government payments. But Curve’s flexibility—letting users assign smart rules or even switch payment methods after a transaction—could inspire these domestic networks to become more modular and interoperable.

Imagine a RuPay card sitting inside a Curve-like layer that works seamlessly with UPI rails. Or national QR ecosystems integrating with a wallet that adds rewards, smart spending rules, or even crypto. The possibilities are intriguing.

3. Schemes: From Control to Collaboration?

Visa and Mastercard have spent decades building secure, scalable payment rails. But with new wallets disrupting the interface layer—and governments backing local alternatives—their pricing and positioning are under scrutiny.

They now face a critical question:

• Do they double down on proprietary rails?
• Or do they partner with fintechs and regulators, offering open APIs and co-developed wallet ecosystems?

Ironically, Curve’s model—which doesn’t issue cards but relies on users’ existing ones—could actually increase scheme-backed card usage. But it would happen outside the schemes’ own apps or experiences, forcing them to adapt.

4. A New Idea: An “Interoperable Wallet Layer” for Closed & Open Loop Systems

Here’s a thought I haven’t seen explored much:

What if we had a universal wallet interface—brand-agnostic—that could integrate not just open-loop cards (Visa, Mastercard, RuPay), but also closed-loop programs, loyalty points, vouchers, local QR balances, and even stablecoins?

A system where:

• Merchants decide the order of payment acceptance (e.g., points first, QR second, card last).
• Consumers set their preferred funding sources (e.g., wallet balance first, stablecoin next, RuPay card last).

This wallet wouldn’t issue anything—it would orchestrate everything. The UX and operational gains for both merchants and consumers could be massive.

Final Thoughts

Right now, Curve Pay is a UK and Europe story. But its implications are global. As fee models open up, domestic networks evolve, and wallet layers gain traction, APAC is uniquely positioned to leapfrog with more inclusive, locally relevant innovations.

The future of payments isn’t just Big Tech vs. banks.
It’s modular, multi-rail, and merchant-first.