.jpg)
Late payment in the UK is often framed as a question of values. Who is behaving badly. Who should be named, shamed, or pressured into doing the right thing. But decades of codes, pledges, and public commitments have failed to materially change outcomes. That suggests the problem is being misdiagnosed. Late payment persists not because of intent, but because payment behaviour is largely invisible, fragmented, and operationally disconnected from accountability.
Late payment in the UK is routinely framed as a values failure.
Large companies are bad actors.
SMEs are victims.
Procurement teams are negligent.
Finance leaders need to “do better”.
This framing is emotionally satisfying and strategically useless.
After decades of codes, pledges, awareness campaigns and public shaming, the numbers remain stubborn. UK businesses are still sitting on tens of billions of pounds in overdue invoices. SMEs continue to fund the working capital of larger firms. Insolvency risk is structurally skewed down the supply chain.
If moral pressure worked, this problem would already be solved.
The uncomfortable truth is that late payment persists because the UK lacks the data infrastructure required to make payment behaviour observable, attributable and operationally actionable. Without that, incentives cannot align and enforcement cannot scale.
This is not a culture problem. It is a systems problem.
Moral narratives do not survive operational reality
Let’s pressure test the common assumptions.
Assumption 1: Late payment is driven by bad intent
Counterpoint: In most organisations, payment outcomes emerge from fragmented systems, not malicious decisions.
Invoices arrive through multiple channels.
Supplier data is duplicated and inconsistent.
Approval workflows span email, ERP, spreadsheets and people’s heads.
Disputes are informal and poorly logged.
Cash forecasting is probabilistic at best.
In this environment, “paying on time” is not a single decision. It is the emergent property of dozens of micro-failures across data, process and visibility.
Assumption 2: Public commitments create accountability
Counterpoint: Commitments without instrumentation are theatre.
Signing up to a code or publishing a policy does not create control. Control requires the ability to measure reality continuously, not annually, and at transaction level, not headline averages.
Most organisations cannot answer basic questions such as:
- Which suppliers are currently delayed, and why
- Whether delays are caused by internal approvals, disputes, or supplier errors
- How payment behaviour differs across teams, subsidiaries or geographies
- Whether reported metrics align with what suppliers actually experience
If you cannot see it, you cannot govern it.
Assumption 3: Shame changes behaviour
Counterpoint: Shame does not survive budget constraints, system limitations or operational complexity.
Finance teams respond to incentives, risk and constraints. If late payment is invisible inside the organisation, it will always lose priority to things that are measurable, owned and audited.
The real problem: absence of shared, verifiable payment data
Late payment persists because payment behaviour is largely unobservable outside the four walls of an individual finance system.
Consider what is missing today.
No shared supplier identity layer
Suppliers appear as duplicates across systems, clients and platforms. There is no consistent way to know that Supplier A paid late by Company X is the same Supplier A paid on time by Company Y.
Without shared identity, reputation cannot compound.
No transaction-level visibility across parties
Suppliers and buyers often have fundamentally different views of invoice status. What one side considers “approved” the other considers “ignored”.
Disputes live in emails. Delays live in inboxes. None of this is structured data.
No attribution of delay
Most late payment reporting collapses everything into a single number. Days to pay.
This hides the most important question: who caused the delay.
- Supplier submitted late
- Invoice failed validation
- Approval stalled internally
- Payment run delayed due to cash timing
Without attribution, accountability is impossible and improvement is random.
No feedback loop into incentives
Payment behaviour rarely feeds back into procurement decisions, supplier financing terms, credit models or reputational signals.
Good payers and bad payers are treated the same in the market because the market cannot reliably tell them apart.
Why regulation struggles without data
UK initiatives such as the Fair Payment Code are directionally correct but structurally constrained.
The state can encourage disclosure, but it cannot easily verify behaviour at scale without direct access to transactional data. Self-reported metrics lag reality and are often too coarse to drive change.
This leads to a familiar pattern:
- High-level reporting improves
- Supplier experience does not
- Trust erodes further
Regulation without data becomes symbolic rather than systemic.
What a data-first solution actually looks like
Solving late payment does not require more pledges. It requires infrastructure.
Specifically:
1. Shared payment timelines
Invoices should have a single, shared timeline visible to both buyer and supplier, showing submission, validation, approval, dispute and payment events.
Not opinions. Events.
2. Delay attribution as first-class data
Every day of delay should be attributable to a cause and a party. This turns late payment from a moral accusation into an operational metric.
Teams can improve what they can see.
3. Persistent behavioural histories
Payment behaviour should compound over time into a verifiable track record at organisation and supplier level.
Not a badge. Not a claim. A dataset.
4. Machine-readable compliance
Codes and standards should be expressed in terms that systems can evaluate continuously, not statements humans review annually.
Compliance should be computed, not declared.
5. Market-level incentives
Once behaviour is visible and trusted, it can flow into:
- Procurement decisions
- Supplier prioritisation
- Financing terms
- Risk scoring
- Reputation signals
At that point, paying late becomes expensive without anyone needing to lecture anyone else.
A contrarian but likely outcome
If the UK builds credible payment data infrastructure, the debate around late payment will quietly disappear.
Not because everyone becomes virtuous, but because:
- Good behaviour becomes cheaper
- Bad behaviour becomes harder to hide
- Incentives realign without confrontation
Markets are far more effective disciplinarians than moral narratives.
The uncomfortable conclusion
Late payment persists because we keep trying to solve a data problem with ethics.
The UK does not need better intentions.
It needs better instrumentation.
Until payment behaviour is observable, attributable and interoperable, every new code or campaign will produce diminishing returns.
The moment data flows, the system self-corrects.
And that is the difference between feeling right and actually fixing the problem.
.jpg)
