Between 2023 and 2025, regulators issued more than 40 enforcement actions tied to bank-fintech partnerships. Consent orders landed at community banks of all sizes, many of which thought they were doing things right. Compliance programs. Oversight committees. Policies and procedures in place.
So why did regulators keep finding problems?
In most cases, it wasn’t a missing policy. It was data they couldn’t trust — reports that didn’t match reality, departments working off different numbers and systems that couldn’t produce accurate information on demand.
A broken data model. And nobody’s talking about it.
What Is a Bank Data Model and Why Does It Matter for Compliance?
Every time someone pulls a report — delinquencies, deposit trends, board reporting, STACS filings — they’re making decisions about what information they need, where it lives and how it connects. That structure is your data model. Not software. Not a dashboard. The logic that determines whether your data tells you something true.
When regulators show up, they’re not just checking your policies. They’re checking whether your numbers are accurate, consistent and traceable to your source data. Five departments pulling the same data five different ways and arriving at five different answers isn’t an operational quirk. It’s the kind of discrepancy that triggers a finding.
Why Fragmented Data Is a Regulatory Risk for Community Banks
Most banks have data models; they’re just fragmented. Accounting pulls their version. Loans have their own. Compliance is working off something else. Somewhere in the middle, someone is manually updating a spreadsheet, emailing it to five departments, waiting for everyone to send it back, and compiling the “final” version.
That process feels normal. It’s been working fine for years. But when a regulator asks you to demonstrate that your reporting is accurate and consistent and you can’t trace it back to your core data, “we’ve always done it this way” is not a defense.
For sponsor banks, this is urgent. The enforcement actions of the last two years weren’t just about bad fintech partners. They were about banks that couldn’t see inside their own walls clearly enough to catch problems before examiners did.
Three Questions Every Community Bank Should Ask About Its Data
- Can we trace any board report or regulatory filing cleanly back to our core data?
- Do we have all the data we need, or are pieces sitting in a disconnected system nobody linked up?
- If a regulator asked us to explain our numbers today, could anyone answer without pulling a spreadsheet together first?
If any of those landed hard, you’re not alone, but you’re also not in a position you can afford to stay in.
How Community Banks Can Fix Their Data Model Before the Next Exam
Start by asking whether your institution can demonstrate that its reporting is accurate, consistent and traceable to a single source of truth. If the answer requires pulling together five spreadsheets and hoping everyone used the same formula, that’s the gap. The goal is simple: When a regulator asks a question, your data should already have the answer. The banks getting there are the ones treating data infrastructure as a compliance issue, not just an IT one.
Lee Easton is the president and founder of iDENTIFY, helping community and sponsor banks turn fragmented, siloed data into something they can actually use. For more information, email Lee at lee@goidentify.com.
Kyle Thorton is a solutions architect and sales engineer at iDENTIFY with a background in AML compliance, fraud operations and financial crime risk across fintech and traditional banking.
