TL;DR

• What it is: Core deposit analytics classifies which deposits in a community bank’s book are core, meaning stable and low-cost, versus noncore, meaning large, rate-sensitive or wholesale, using the FFIEC’s own definition.
• The core mechanic: The FFIEC’s formula splits deposits by account type, balance size and insurance status, down to a $250,000 line that moves a single account from one bucket to the other.
• Why it matters: The Net Noncore Funding Dependence ratio built on this classification is a standard line on every bank’s Uniform Bank Performance Report, the document examiners use to assess funding stability.
• One caveat: No named case study exists yet for this specific capability. This piece grounds it in the FFIEC’s own definition and the classification problem that definition creates for any bank trying to track it continuously.

A community bank already reports a core deposit number every quarter. Almost none of them can say, on any given day between those reports, exactly which accounts are driving it. This piece lays out what the FFIEC counts as a core deposit, why that definition is harder to apply than it looks, and what changes once a bank classifies its book continuously, on every day between reporting cycles.

What the FFIEC Counts as a Core Deposit

The FFIEC’s own formula is the starting point, and it is more specific than most bankers assume. The FFIEC’s Uniform Bank Performance Report User Guide defines core deposits as the sum of all transaction accounts, nontransaction money market deposit accounts, nontransaction other savings deposits, and nontransaction time deposits of $250,000 and less, minus fully insured brokered deposits of $250,000 and less.

Noncore liabilities cover the other side: total time deposits of more than $250,000, other borrowed money, foreign office deposits, securities sold under repurchase agreements, federal funds purchased, and insured brokered deposits under $250,000. Every account in a bank’s core system falls somewhere in this split. The definition itself answers the question. Applying it to a live, changing book of accounts is the harder problem.

Why the $250,000 Line Makes Classification Harder Than It Looks

A single dollar can move an account from one side of this formula to the other. A time deposit of $249,999 counts as core. The same account at $250,001 counts as noncore. A bank running a large CD promotion can watch its core deposit ratio shift as balances cross that line, with no change in customer behavior at all.

Brokered deposits add a second layer. A brokered deposit under $250,000 and fully insured counts toward core. A brokered deposit between $100,000 and $250,000 and insured counts as noncore. The distinction runs on insurance status and balance size together. The word “brokered” alone does not decide it. Money market deposit accounts complicate the picture further. MMDAs count as core under the FFIEC definition even though large commercial MMDA balances often behave like rate-sensitive, noncore money in practice. The formula and the underlying economic behavior do not always point the same direction, which is exactly why classification takes more than reading the definition once.

What a Quarterly Call Report Can’t Catch Between Cycles

The Net Noncore Funding Dependence ratio is the number examiners look at, and it is a snapshot. The FFIEC’s formula divides noncore liabilities, less short-term investments, by long-term assets. It appears on every bank’s Uniform Bank Performance Report, recalculated each quarter from whatever the book looked like on the reporting date. It does not update between reporting dates.

Between those reporting dates, the underlying classification keeps moving. CDs mature and roll into new terms that cross the $250,000 line in either direction. Brokered deposit balances shift between insured tiers. A commercial customer’s MMDA balance swings from core-sized to noncore-sized and back within a single month. The next quarter’s report is the first place any of that shows up. A bank relying on the quarterly number alone is managing funding risk with a three-month lag built into the only measurement it has.

What Continuous Account-Level Classification Adds

Classifying every account against the FFIEC definition on a continuous basis, beyond the quarterly cycle, turns a lagging compliance number into an operating one. iTuring.ai’s Data Accelerator applies the same account-type, balance-size and insurance-status logic the FFIEC formula uses, scored continuously across the deposit book, independent of the reporting calendar.

That gives treasury a running view of the Net Noncore Funding Dependence ratio between call reports as well as on them, and it flags the specific accounts driving a shift in either direction. A CD campaign pushing balances across the $250,000 line shows up as it happens, well ahead of the quarterly report that would otherwise be the first to catch it.

Why Core Classification Comes Before Flight Risk

A flight risk score is only as useful as the classification underneath it. Scoring which deposits are likely to leave assumes the bank already knows which deposits are core in the first place. A large, rate-sensitive relationship that core deposit analytics has already flagged as noncore is exactly the kind of account a flight risk model needs to watch most closely.

We cover that next step in Deposit Flight Risk: Seeing It Before the Quarter Closes, which applies propensity-based scoring to the relationships this classification identifies as carrying the most concentration risk.

See how this applies to your deposit base

A conversation with our team walks through how continuous core deposit classification applies to your own book, using your own numbers. Book a working session.

Sources

• FFIEC, Uniform Bank Performance Report User Guide, “Liquidity and Funding.” Confirmed by direct fetch of ffiec.gov.
• iTuring.ai Data Accelerator platform description.