If you’re scaling a payments operations team globally, this is a question worth sitting with:
How do you handle thousands of transactions daily in a fast-growing fintech – while reducing payment errors, not increasing them?
I recently sat down with the team at Miden as part of their fintech expert series on building trust in payments, and I’ll be breaking this down over my next two posts – but here’s my full perspective on the highlighted question.
From day one, you have to build with scale in mind. The right question isn’t just how do we handle errors today? but what happens if these errors multiply 100x or 1,000,000x? If the outcome would be a disaster for customers, internal teams, or growth, then you need to design systems that prevent or flag those errors before they ever happen at scale.
I learned this firsthand, leading payments at a billion-dollar fintech while we were still a promising startup with trickles of transactions, preparing to launch instant payments. At first, we used Excel sheets and formulas to flag errors, but we quickly realised that wouldn’t hold once volumes surged.
So we built automation.
Our system could flag when a transaction showed “pending” or “failed” internally but returned a “00” success response from the payment processor. It worked by running real-time queries against the processor’s API, updating statuses immediately rather than waiting hours or days for the reconciliation team to catch it.
The key is collaboration. Payments teams must work hand-in-hand with engineers to anticipate error scenarios and build real-time resolutions. That way, when the payments team reviews data, they’re focused on catching the 1% of new or edge-case errors that automation didn’t pick up – not firefighting the 99% that could have been prevented.
