{"id":3949,"date":"2025-10-10T12:15:18","date_gmt":"2025-10-10T11:15:18","guid":{"rendered":"https:\/\/kanipayments.com\/?p=3949"},"modified":"2025-10-13T12:16:33","modified_gmt":"2025-10-13T11:16:33","slug":"aaron-holmes-on-the-changing-face-of-payments-data","status":"publish","type":"post","link":"https:\/\/kanipayments.com\/company\/newsroom\/aaron-holmes-on-the-changing-face-of-payments-data\/","title":{"rendered":"Aaron Holmes on the changing face of payments data"},"content":{"rendered":"\n
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Originally featured in Finextra<\/a>, Kani CEO and founder Aaron Holmes reflects on how the payments industry has changed and why data clarity remains one of the biggest challenges facing fintechs today.<\/p>\n

From manual chaos to data clarity<\/h2>\n

When I first entered the payments space nearly two decades ago, reconciliation was a manual slog. Teams were buried in spreadsheets, tracing transactions and hunting mismatches\u2014often for days at a time. What should have been straightforward was anything but.<\/p>\n

Technology has moved on, but the core issue remains: payments data is messy, fragmented and hard to trust.<\/strong><\/p>\n

Solving the data problem means treating raw inputs not just as information, but as infrastructure. When data is standardised, complete and traceable, it stops being a blocker and becomes a platform\u2014one that enables lightning-fast reconciliation<\/a>, confident reporting and iron-clad compliance at scale.<\/p>\n

The root problem: fragmented, ambiguous data<\/h2>\n

Payments data rarely arrives clean or consistent<\/a>. It comes from banks, processors, schemes and acquirers\u2014each with their own formats, field names and definitions. One file says \u201csettled,\u201d another says \u201ccleared,\u201d a third says \u201cposted.\u201d<\/p>\n

Same action, different terms. Or worse: different actions described the same way.<\/p>\n

Multiply this across partners, currencies and time zones, and you\u2019re facing a reconciliation puzzle before you\u2019ve even begun.<\/p>\n

The cost? Missed revenue. Compliance gaps. Reputational risk. And with fintechs scaling fast and regulation tightening, the stakes have never been higher.<\/p>\n

The myth of matching<\/h2>\n

There\u2019s a common misconception that reconciliation is all about matching numbers.<\/p>\n

In reality, the hard work happens long before that. You need to clean the data, structure it and understand what it\u2019s really telling you long before any reconciliation takes place.<\/p>\n

We\u2019ve worked with companies of every shape and size, and the story\u2019s always the same: messy data is the biggest blocker.<\/p>\n

That\u2019s why we built Kani to focus first on transforming data. Once the groundwork\u2019s solid, matching, reporting and analytics flow naturally.<\/p>\n

New pressures: speed and scrutiny<\/h2>\n

The environment today is very different from when I started.<\/p>\n

We\u2019ve moved from monthly reports to real-time expectations. Customers want instant updates. Regulators demand timely submissions. Finance teams need live visibility to make confident decisions.<\/p>\n

To meet these rising demands, the data itself needs to be up to the task. Speed means nothing if the inputs are flawed. Without a solid foundation, even the most advanced systems will fail under pressure.<\/p>\n

Why clean data changes everything<\/h2>\n

A solid data foundation is the difference between barely coping and operating at scale. When your data is structured, validated and complete, you can:<\/p>\n