Is Your Fintech Data Actually Trustworthy? With Yuliia Komaryn

Why “real time” doesn’t mean what most people think it means: #

Igor Tomych sits down with Yuliia Komaryn, Business Analytics Team Lead at DashDevs, to unpack a phrase that gets thrown around in every fintech pitch deck. Her position: real-time is a marketing concept, not a technical spec. A fraud alert needs milliseconds. A monthly revenue metric doesn’t. The actual job of a dashboard is giving each metric the right latency for someone to act on it in time.

A BNPL fraud case that shows why dashboards without action plans fail: #

Yuliia walks through a real case: a buy-now-pay-later product whose user base shifted to include people accessing credit with no intention of repaying. The fix wasn’t a better-looking dashboard; it was flagging suspicious patterns fast enough for compliance and support teams actually to intervene before losses compounded.

The “cute puppy” problem: one word, five different meanings inside your own company: #

The conversation’s most memorable example: “customer” means a completely different thing to a marketing team (anyone who clicked an ad) than to a finance team (someone who’s actually paid). Yuliia argues that unresolved naming conflicts like this quietly corrupt every downstream metric, from LTV to acquisition cost, long before anyone notices the dashboard is wrong.

The market shifted from “can you build it” to “can you trust it”: #

According to Yuliia, the defining shift in 2026 isn’t about dashboard capability; AI has made building a polished-looking dashboard almost trivial. It’s about whether the data behind it is traceable and trustworthy. A dashboard that looks complete but pulls from unreliable or ambiguously defined data is, in her words, exactly how vibe coding a financial system leads to mistakes nobody catches until it’s expensive.

Why listen: #

This episode is a useful corrective for anyone building or buying fintech dashboards: a clear framework for deciding what actually needs to be real-time, a live fraud example showing what happens when it isn’t, and a warning about the gap between a dashboard that looks trustworthy and one that actually is.