By Aaron Holmes, CEO of Kani Payments
In an industry built on data, financial businesses are under growing pressure to deliver accuracy, speed and transparency – especially when it comes to mandatory reporting. Yet reporting workflows remain outdated, creating friction and inefficiency where clarity and control should exist.
A recent survey of 250 UK payments and banking professionals uncovered persistent challenges in how data reporting is managed across the industry. Legacy tech remains deeply embedded, tying up teams and introducing unnecessary risk. Without change, what’s inefficient today could become a liability tomorrow.
The Excel Challenge
The 2025 Card Scheme Reporting Survey revealed just how much manual reporting is costing the industry. On average, companies lose nearly a full month (142 hours) of productivity annually to these tasks alone. Time is spent on routine jobs like data collection, validation, reconciliation and formatting.
At the heart of this efficiency gap are the complex, high-stakes reports required by card networks—the Mastercard QMR (Quarterly Mastercard Report) and Visa GOC (Global Operating Certificate). These reports are detailed, recurring submissions that demand precision and cross-functional output.
Despite the critical nature of these reports, many organisations still use outdated processes to complete them. Nearly half (44%) of companies continue to rely on Microsoft Excel—either partially or exclusively, exposing teams to time-intensive workflows and a greater risk of errors.
And the consequences are clear. Around two-thirds (64%) of organisations frequently encounter data errors and anomalies in reporting outputs. These issues stem not only from human error, but from the structural limitations of spreadsheets: manual data entry, poor version control, lack of integration and limited formatting capabilities all leave teams struggling with data as deadlines approach.
Reporting Bottlenecks
Challenges are rarely confined to one part of the process. While some pain points stand out more than others, the survey shows just how widespread inefficiencies are:
- Exception handling (33%) is the primary time drain, with teams spending hours resolving transaction discrepancies that software could flag and route automatically.
- Data collection (30%) and reconciliation (29%) create challenges, often due to fragmented or siloed data sources.
- Currency conversions and FX rate management (29%) are major hurdles, especially for companies dealing with multi-currency payment flows like neobanks (45%) and e-money institutions (32%).
- Categorising transactions (27%) and understanding card scheme terminology (28%) also contribute to the burden, highlighting the complexity of scheme reporting requirements.
The operational burden is felt everywhere. Unless there is a structural change, it won’t ease as the industry grows.
Why Automation Stalls
With widespread inefficiencies, it’s no surprise that 67% of companies have explored automated reporting solutions. But interest doesn’t always translate into action. Of those who have explored automation, one-third decided not to implement.
The barriers aren’t always technical – they’re often psychological or cultural. Resource constraints (49%) are the top blocker, followed by a preference for the familiarity of Excel (41%) and satisfaction with current processes (41%). These obstacles point to limited internal capacity to manage change and a deeper reluctance to disrupt what is seen to “work well enough”.
Interestingly, change inertia is more common among companies using spreadsheets (53%) or in-house systems (60%), where resource constraints are most acute. The irony? The very systems that once offered control and flexibility are now some of the biggest barriers to progress.
The Case for Change
Manual processes introduce risks through inconsistent formatting, outdated templates and fragmented data sources. Automation addresses these issues at the root, validating inputs at source, applying consistent logic across datasets and ensuring alignment with reporting requirements.
Forward-thinking businesses are shifting their focus from manual efficiency hacks to long-term resilience. Around one-quarter (23%) plan to pursue automation in the near term, either actively evaluating options or planning to implement.
The push to automate is being driven less by speed and more by a need for control over data quality, compliance and cost. 45% cite improved data accuracy as their primary motivation, followed closely by regulatory confidence (39%) and cost-effectiveness (39%). These three drivers are interconnected: stronger data accuracy supports ongoing compliance, which in turn reduces the cost and risk associated with errors and submission penalties.
The True Cost of Inaction
While the time lost to reporting is significant, the bigger issue is the opportunity cost. Every hour spent compiling data is an hour not spent building new products, improving customer experience or exploring new markets.
Much of that time is spent on routine tasks like gathering and preparing data, long before reconciliation and investigative work even begins. As reporting requirements become more complex and frequent, the drag on productivity compounds with every cycle. In an industry that depends on agility, that’s a disadvantage few can afford.
The path forward is clear—but only for those willing to rewire legacy thinking and invest in smarter, more scalable systems.
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