The strategic case for treating PIS and AIS as a single intelligence layer
Pay by Bank is now a standard part of the checkout. Most payment service providers (PSPs) already offer it because the advantage over cards is clear: lower fees, faster settlement, and fewer chargebacks.
But this maturity has changed the competitive equation. As volume shifts to open banking, the payment method itself is losing its differentiation. The margin benefit might remain, but it is being shared across the entire market, nullifying the competitive edge it once promised.
To make this shift, forward-looking PSPs are connecting payment infrastructure to the data layer, turning raw transactions into intelligence. This is critical as the market moves toward recurring payments and agentic commerce, where payments cannot function without the context of real-time data.
Every payment carries a data signal. Every data point can shape a payment.
Open banking connects two things that have traditionally sat apart: the movement of money and the financial intelligence that surrounds it.
With account-to-account payments, you get instant settlement and reduced scheme dependency. With consented bank account data, you get identity verification, account ownership, income patterns, and transaction behaviour in real-time.
But when you run both through the same infrastructure layer, they feed each other. Every payment generates valuable data that can sharpen onboarding, optimise credit decisioning, and enable fraud detection; while each data point can trigger, verify, or optimise the next payment.
Over time, this loop compounds, deepening the financial intelligence merchants can access. Because open banking payments are verified by the bank, they represent the highest quality behavioural data a merchant can access, outperforming sources like surveys, browser data, and even card transactions. PSPs that treat these signals as a commercial asset aren't just processing money; they are reshaping their position in the value chain.
A commercial shift in motion
The more payments and data are combined operationally and commercially, the more they amplify eachother’s capabilities across the merchant lifecycle. Every bank-verified payment is a behavioural signal that provides data, which is the engine that turns those signals into commercial outcomes. This principle can play out across the merchant lifecycle in the following three areas:
1. From processing transactions to powering merchant decisions
Bank-verified spending signals give PSPs a role in merchant decisions that extends across the lifecycle.
Before checkout, real spending behaviour can replace demographic estimations. For example, a travel platform targeting customers whose bank data shows consistent airline and hotel spend can work from a materially stronger data signal than one relying on interest-based segments (like browser or survey data).
During and after checkout, the same data can then inform pricing, personalisation, and risk. Consented financial data can reveal consumer preferences, subscription patterns, and income stability. Lenders using enriched transaction data can compress credit decisions while responsibly expanding access. For a travel merchant, this means they can isolate data on frequent international spend and adjust offers and ancillary services based on the consumer’s behavioural signals.
The more a PSP can surface bank-verified spending signals to merchants, the more its role shifts from executing payments to informing the commercial decisions around them.
2. Conversion, pricing, and fraud, all solved on the same layer
Conversion, pricing, and fraud are all interconnected at checkout, even when they sit with different teams internally. The infrastructure that connects them can create a single optimisation surface.
Creating an optimal payment experience depends on the financial context; who the customer is, what they are buying, and their real-time affordability all influence approval, pricing, and risk. When payment initiation and account data operate at the same layer, merchants can align payment methods, incentives, and financing terms with the actual financial position rather than assumptions.
The result is lower processing costs, higher approval rates, fewer chargebacks, and more intelligent monetisation. Conversion rates then improve because the risk is clearer. Pricing accuracy then improves because affordability is verified, and fraud risk declines because the payment itself is bank-authenticated.
When payments and data share infrastructure, conversion, pricing, and fraud become outputs of the same system. This matters even more as commerce becomes more automated.
3. Faster activation leads to deeper retention
Verified bank data can also automate the most friction-heavy elements of KYB: account ownership, business identity, and transaction history, potentially reducing onboarding time by days. The faster a merchant gets live, the sooner they transact, generating behavioural data earlier and embedding more deeply into the PSP's infrastructure.
Payment behaviour can offer insight into loyalty patterns with greater accuracy than CRM signals alone, from increased purchase frequency to early signs of churn. PSPs that provide enriched transaction intelligence become the source of these insights for their merchants, enabling higher-value services built on top of them. This can then drive customer engagement and retention.
This creates a chain reaction effect, where each stage feeds the next: Activation accelerates volume; volume enriches data; data strengthens merchant services; stronger services deepen retention; retention accelerates volume, and so on. Over time, this advantage compounds, and the competitive edge for the PSPs using this payment and data flywheel approach grows when compared to the rest of the market as volume and complexity increase.
The infrastructure bar is rising
The commercial case for connecting payments and data already exists, and the regulatory and market trajectory are making it increasingly difficult for PSPs to ignore.
Recurring open banking payments in the UK will extend Pay by Bank into subscriptions, utilities, and instalments. This shifts open banking from single transactions to continuous payment flows. Recurring payments generate longitudinal data, enabling smarter retry logic, churn prediction, and lifecycle management. As you scale, performance expectations from your customers rise. Recurring open banking payments enable this rising performance by feeding more data through transactions.
At the same time, emerging models such as agentic commerce will require real-time financial context, verified identity, and programmable payment controls, so sharing payments and data in the same infrastructure will improve agentic commerce readiness. The infrastructure serving today's checkout is the same infrastructure that will serve tomorrow's AI-initiated transactions. Payments will not operate in isolation from data when agents are making decisions, so PSPs need infrastructure that supports both.
Open Finance will further expand the perimeters of what’s possible. In both the UK and the EU, regulators are extending consented data-sharing beyond current accounts into savings, credit, investments, and insurance. This means the scope of usable financial data is widening, and providers will be expected to operationalise it responsibly and at scale.
Across markets, the direction is consistent: more data, more programmability, and higher infrastructure standards. AIS connectivity, enrichment capability, and verified data flows are now moving from competitive advantage to baseline expectation.
The strategic question you should be asking yourself
This perspective leaves us with a question that cuts across product, commercial, and partnership decisions for PSPs: Is your infrastructure treating payments and data as a single intelligence layer or running them in parallel?
That choice will shape margin resilience, merchant retention, and your ability to expand into higher-value services as the market evolves. PSPs unifying payments and data into a single layer will gain a unique and sustainable edge in the market with this approach.
As regulation expands, the data boundaries and commerce become more programmable, which means the returns on this structural advantage will compound, and the cost of building it later will rise.