In today’s data-driven financial landscape, institutions are under mounting pressure to deliver reporting that’s accurate, fast, transparent and (most importantly) audit-ready. Yet many continue to rely on outdated manual workflows, especially when it comes to complex, recurring obligations like card scheme reporting.
Aaron Holmes, CEO and Founder of Kani Payments, explains why the status quo is breaking down and how a shift toward automation is becoming essential for compliance, scalability and long-term resilience.
Built for a different era
In our recent survey of 250 UK payments and banking professionals, Kani uncovered persistent reporting pain points across the industry. Despite rapid growth in transaction volume and data complexity, legacy technology and spreadsheet-based processes are still widely used—creating friction in workflows that need clarity and confidence.
“The real challenge isn’t just inefficiency,” says Holmes. “It’s that the tools teams are relying on were built for a much simpler time, and now they’re being stretched to breaking point.”
The Excel time sink
The average card issuer or acquirer in the UK loses 142 hours per year—nearly a full month of productivity—to manual reporting tasks. That includes gathering data, formatting spreadsheets, validating inputs, reconciling across sources and submitting reports in the formats required by card schemes.
Much of this burden comes from recurring scheme-specific reports like Mastercard’s QMR (Quarterly Mastercard Report) and Visa’s GOC (Global Operating Certificate). These reports demand cross-functional collaboration, consistent data formatting and a high level of precision. Yet 44% of companies still rely on Microsoft Excel, either entirely or as a central part of the process.
And the risk is real: 64% of companies frequently encounter errors or anomalies in their final reporting outputs. These aren’t just typos—they’re structural issues, driven by inconsistent templates, poor version control and limited integration between systems. That’s why many businesses are turning to automated QMR and GOC reporting software to streamline compliance and reduce the risk of submission errors.
Where the bottlenecks lie
Manual friction isn’t confined to a single step in the process—it’s systemic. The survey revealed a wide range of pressure points across card scheme reporting workflows:
- Exception handling (33%): The biggest time drain, with teams spending hours resolving transaction discrepancies that could be flagged automatically.
- Data collection (30%) and reconciliation (29%): Often fragmented across silos or systems with limited interoperability.
- Currency conversion and FX rate management (29%): A major challenge for multi-currency businesses like neobanks (45%) and e-money providers (32%).
- Categorisation and terminology (27–28%): Highlighting how difficult it is to align transaction records with scheme-specific codes and formats.
“The real problem is that the pain is everywhere,” says Holmes. “Without a structural change, this operational drag won’t ease—it will intensify as the industry continues to scale.”
Automation fatigue… or fear?
You might expect businesses to be automating these processes en masse. In reality, 67% have explored automation, but one-third chose not to implement.
Interestingly, the roadblocks aren’t primarily technical. Resource constraints (49%), a preference for familiar tools like Excel (41%) and a belief that “current processes are good enough” (41%) all feature prominently.
Companies using spreadsheets or custom in-house systems report the highest inertia, despite also facing the most acute inefficiencies. “The irony,” Holmes points out, “is that the systems that once gave teams control are now the biggest blockers to progress.”
The case for real change
Manual reporting creates hidden risk. Outdated templates, inconsistent data sources and manual re-entry all contribute to a process that’s slow, error-prone and hard to audit.
Automation doesn’t just improve speed—it standardises formatting, validates data at the source and applies consistent business logic across all reporting cycles. The result is better data integrity, fewer last-minute errors and greater confidence with regulators and scheme operators.
In fact, 45% of companies now cite data accuracy as the main reason to pursue automation, followed by regulatory confidence (39%) and cost-efficiency (39%). These are tightly linked: greater accuracy reduces non-compliance risk, which lowers cost and protects reputation.
The hidden cost of doing nothing
The time lost to reporting inefficiency is measurable. But the opportunity cost is harder to see and more damaging over time.
“Every hour spent compiling data is an hour not spent building your business,” Holmes notes. “Teams should be focusing on insights, not inputs.”
Instead, many are still stuck at the starting line—cleaning data, chasing anomalies and preparing files for submission—before reconciliation and analysis can even begin. The solution here is to adopt a more intelligent reconciliation tool that eliminates inefficiencies at the source.
As reporting requirements become more complex and frequent, that drag only increases. In an industry that relies on speed and scalability, it’s a disadvantage few can afford to ignore.
What comes next
The path forward is clear for businesses willing to modernise their reporting infrastructure. “It’s not just about automation for automation’s sake,” says Holmes. “It’s about building workflows that can scale, adapt and support real growth.”
That means moving past Excel, replacing ad hoc fixes with integrated processes and embracing platforms purpose-built for payments data.
In a landscape where reporting risk is business risk, it’s time to shift from ‘what works’ to ‘what works better.’
Attribution note
This article is adapted from an original feature in Software Testing News, where Kani CEO Aaron Holmes explores the tech challenges around Mastercard QMR and GOC reporting in the payments industry.
