PayTo in Australia: Real-Time Payments Need Smarter AI

Australia moves fast on payments—and not just at the tap-to-pay terminal. 83% of point-of-sale payments were contactless in 2019, and by 2022 roughly 25% of card payments ran through digital wallets. That momentum has a predictable next step: more account-to-account, real-time rails that feel as easy as cards, but cost less and settle with fewer delays.

That’s why PayTo’s availability in Australia matters. PayTo is built for one-time and recurring real-time payments, and it’s now something merchants can accept through mainstream payments infrastructure. The headline isn’t “a new button at checkout.” The headline is this: every new payment method multiplies complexity—routing, fraud, refunds, disputes, reporting, and customer support—unless your infrastructure (and your AI) is ready.

This post is part of our AI in Payments & Fintech Infrastructure series, and PayTo is a clean case study. It shows how modern infrastructure makes emerging payment methods deployable at scale—and why AI-driven transaction routing, fraud detection, and risk controls are becoming mandatory, not optional.

What PayTo changes for Australian checkout flows

PayTo makes bank payments behave more like cards—without being cards. Customers can authorize an agreement with their bank and use it for recurring payments (subscriptions, invoices, top-ups) or one-off transactions.

From the Stripe product details, PayTo’s key characteristics are straightforward and merchant-friendly:

• Customer location: Australia
• Currency: AUD
• Use cases: one-time + recurring
• Confirmation: customer-initiated
• Refunds: supported (including partial)
• Disputes: supported
• Connect support: supported (relevant for platforms/marketplaces)

That mix matters because a lot of “alternative payments” fail in the real world on the operational details. Recurring is often bolted on later. Refund workflows are messy. Reporting is fragmented. PayTo’s positioning is different: it’s meant to fit into the everyday needs of digital businesses.

How PayTo works (and why it’s friction you can manage)

The PayTo user journey has four steps, and each step creates either conversion lift or abandonment risk:

1. Customer selects PayTo at checkout
2. Customer enters PayID (email/phone) or bank account details
3. Customer authorizes the PayTo agreement in their banking app
4. Payment completes

The “bank authorization” step is the big difference versus cards. It’s also the step where merchants need to be disciplined: messaging, retries, and fallbacks matter.

A real-time payment method succeeds or fails at the handoff moment—the point where your checkout leaves your UI and enters the customer’s banking experience.

If you’ve built payment flows, you know what that means: instrument every step, measure drop-off, and treat payments like a product funnel—not a finance afterthought.

The infrastructure lesson: one integration is the easy part

Accepting PayTo is not the hard part. Operating PayTo at scale is. The RSS content highlights the obvious benefit: you can enable a new payment method via a unified integration (for example, a single payment UI component or a hosted checkout).

That’s table stakes.

The real infrastructure questions start after launch:

• How do you decide when to show PayTo vs card vs wallet?
• How do you reduce failures caused by customer drop-off during bank authorization?
• How do you handle refunds, partial refunds, and disputes without breaking reconciliation?
• How do you support PayTo across direct sales, invoicing, and subscriptions?
• If you’re a platform, how do you support it for sub-merchants with different risk profiles?

This is where fintech infrastructure earns its keep: payments orchestration, unified reporting, consistent webhooks/events, predictable settlement and payout flows, and control surfaces for risk and compliance.

Why “100+ payment methods” is only valuable with smart orchestration

Offering many payment methods can increase conversion, but it can also create a bad user experience if it’s done indiscriminately. Showing 8–12 options to every shopper often backfires.

The better approach is intent-based presentment:

• Default to the likely best method for that shopper and transaction
• Keep alternatives available, but not overwhelming
• Learn from actual outcomes (conversion, disputes, refunds, support tickets)

That’s an orchestration problem—and it’s increasingly an AI problem.

Where AI fits: routing, fraud, and “trust UX” for PayTo

AI makes new payment methods safe and scalable by turning payments operations into a feedback loop. PayTo brings cost and conversion advantages, but also introduces new risk and behavior patterns. Card fraud signals don’t map 1:1 to account-to-account flows. Shopper drop-off dynamics change. Disputes can look different.

Here are three AI applications that actually move the needle.

1) AI-driven payment method routing (conversion + cost)

Smart routing chooses the best payment method for each attempt, not the most popular method overall. For PayTo, routing can consider:

• Transaction type (subscription setup vs one-time)
• Basket size (small “impulse buy” vs high AOV)
• Customer history (returning customer vs first-time)
• Device and context (mobile banking handoff tends to behave differently)
• Prior failure patterns (bank authorization drop-off, timeouts, user cancellation)

A simple starting policy might look like:

• For subscription signups, present PayTo prominently (because it’s built for recurring)
• For very low AOV, keep the fastest method first (often wallets)
• For high AOV, offer PayTo as a “lower fee / bank-authenticated” option

AI improves this by learning which presentation order and default choices lead to the highest completed payments, not just clicks.

2) AI fraud detection for real-time payments (different signals)

Real-time payments reduce some card-specific fraud, but they don’t eliminate fraud. They shift it.

Fraud teams should expect pressure in areas like:

• Account takeover attempts used to set up PayTo agreements
• Social engineering that pushes users to authorize agreements they don’t understand
• Synthetic identities that behave “clean” for a short period, then monetize

AI helps by correlating signals across sessions and payments:

• Device fingerprint anomalies
• Velocity patterns (agreement setups, attempts per device/account)
• Behavioral biometrics (typing cadence, navigation patterns)
• Merchant-level anomalies (sudden mix shifts to PayTo, unusual refund rates)

The goal isn’t to block aggressively. It’s to minimize false positives while stopping obvious abuse early.

The fastest way to kill adoption of a new payment method is to create friction for good customers in the name of “risk controls.”

AI is how you avoid that trap.

3) AI that reduces drop-off during bank authorization

PayTo includes a customer-involved authorization step. That’s good for security and consent. It’s also a point where people abandon—especially during peak shopping periods.

This is the moment for AI-assisted “trust UX”:

• Predict when a shopper is likely to abandon and proactively surface a clear explainer
• Detect confusion signals (rage clicks, repeated back-and-forth) and offer a fallback method
• Personalize microcopy by context (subscription vs one-time, first-time vs returning)
• Optimize retry windows (when to prompt, when to wait, when to switch methods)

The best teams treat authorization as a mini-funnel and run experiments weekly, not quarterly.

Practical launch plan: adding PayTo without creating chaos

Launching PayTo should be a controlled rollout with measurable outcomes. If you simply switch it on and hope for the best, you’ll learn the wrong lessons (or worse, you’ll blame the payment method for issues caused by UX).

Step 1: Pick the right first use case

Start with a segment where PayTo’s strengths matter:

• Subscriptions with high card churn (expired cards, reissues)
• Invoice payments where bank details feel “normal” to customers
• High-AOV ecommerce where fees and trust signals matter more

Avoid launching first on flows where speed is everything and users hate extra steps.

Step 2: Instrument the PayTo funnel end-to-end

At minimum, track these events:

• PayTo shown
• PayTo selected
• Bank details entered
• Bank authorization initiated
• Bank authorization completed
• Payment succeeded/failed

Then add outcomes:

• Refund rate
• Dispute rate
• Support contact rate (and reason codes)

If you can’t measure this, you can’t improve it—and you can’t defend the rollout internally.

Step 3: Use AI for decisioning, not just dashboards

Dashboards tell you what happened. AI decisioning changes what happens next. Two pragmatic starting points:

• Dynamic presentment: show PayTo as default only for cohorts where it wins on conversion and cost
• Risk-based step-up: add extra verification only when signals justify it

This keeps checkout clean for most users while protecting your loss rates.

Step 4: Prepare operations for refunds and disputes

The RSS content notes PayTo supports refunds (including partial) and disputes. Good. Now operationalize it:

• Define refund SLAs and customer messaging (especially around timing expectations)
• Train support on “agreement authorization” questions
• Ensure reconciliation can tie PayTo payments to orders, invoices, and subscriptions

Most payments projects fail here: the engineering launch goes fine, then finance and support drown.

Why PayTo is a signal for global fintech infrastructure

PayTo isn’t just “an Australian payment method.” It’s a pattern. Every region is building faster rails and pushing more payments directly from bank accounts. The winners will be the businesses that can:

• Add new methods quickly
• Operate them reliably across products (checkout, invoicing, subscriptions, platforms)
• Use AI to keep fraud low and conversion high
• Maintain clean reporting and reconciliation across rails

Australia is a useful proving ground because the market is already comfortable with modern payment experiences. If your stack can handle PayTo well—especially recurring payments and dispute workflows—you’re better positioned for the next wave of real-time payment methods elsewhere.

December is also when weak payment stacks get exposed. Peak season traffic, last-minute renewals, and gift-driven ecommerce spikes put pressure on authorization rates, fraud controls, and support queues. Adding a method like PayTo can help cost and resiliency—but only if it’s launched with the right instrumentation and AI guardrails.

What to do next (if you’re serious about PayTo adoption)

If you’re a merchant or platform operating in Australia, PayTo is worth testing now—especially for recurring payments. But don’t treat it like a simple toggle. Treat it like a new rail with new behavior.

Here’s the stance I’ll defend: the competitive advantage isn’t access to payment methods; it’s AI-guided execution. The teams that win will route intelligently, detect abuse without punishing good customers, and constantly refine authorization UX.

If you’re building your 2026 payments roadmap, ask yourself: when the next payment method shows up in your market, will you be able to launch it in days—and improve it every week after?