Real Estate Operating Companies · FDIC
FDIC Failed Bank List — Every U.S. Bank Failure Since 2000
Datadory delivers fdic failed bank list data covering the complete modern history of American bank failure: roughly 577 institutions placed into FDIC receivership since October 1, 2000, one row each carrying the failed bank's name and headquarters city and state, its FDIC certificate number, the acquiring institution that assumed the deposits, the exact closing date and the insurance fund sequence behind the resolution — from the 2008-2013 cascade through Silicon Valley Bank, Signature Bank and First Republic in March 2023 to the July 2026 closings. Delivered daily, weekly, or hourly.
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- Where it covers
- United States — every state and territory where a covered institution failed, with headquarters city and state carried on each row
- How far back
- October 1, 2000 through the most recent closing — roughly 577 failures as of July 2026, covering the 2008-2013 cascade and the March 2023 wave
- How fine
- One row per failed institution; resolution-level supplements available on request
What is the FDIC Failed Bank List dataset?
It is the regulator's complete record of who did not make it. Since October 1, 2000, every bank placed into FDIC receivership has landed on this list as a single row carrying seven facts: the institution's name, its headquarters city and state, its FDIC certificate number, the acquiring institution that assumed its deposits, the closing date, and the insurance fund sequence that settled the resolution. Roughly 577 rows cover the entire modern era as of July 2026.
The list reads differently depending on where you put your finger. Open it in the middle and you find the 2008-2013 cascade — several hundred institutions, heavily concentrated in Georgia, Illinois, California and Florida, failing week after week. Jump to March 2023 and three names dominate: Silicon Valley Bank, Signature Bank and First Republic Bank, each with its own resolution record. Scroll to the end and the most recent closings sit days old, still warm.
Around the core table sits the material most users never find: per-bank resolution detail, receivership financial statements, depositor payout outcomes, the year-by-year Bank Failures in Brief narratives and the pre-2000 historical publications. Those layers fold into your extract on request, which matters for anyone doing century-scale banking research or sizing distressed asset flows rather than counting headlines.
What do sample rows look like?
The two newest entries, exactly as they arrive:
bank_name : Small Business Bank
hq : Lenexa, KS
cert : 25744
acquiring_institution: The Farmers State Bank of Oakley, Kansas
closing_date : 17-Jul-26
fund : 10553
bank_name : Kentland Federal Savings and Loan Association
hq : Kentland, IN
cert : 28722
acquiring_institution: Kentland Bank
closing_date : 10-Jul-26
fund : 10552Ten days apart, two small institutions, both resolved with an acquirer stepping in — and already the shape of the dataset shows itself. The cert number (25744, 28722) is the join key that connects either row to every other cert-addressed regulatory panel. The acquirer line tells the consolidation story: deposits did not vanish, they moved to a named surviving institution. The Fund value ties each closing to the specific insurance fund transaction behind it.
One quirk worth knowing before you chart anything: closing dates cluster on Fridays, because that is when regulators prefer to act — a weekend gives the successor institution time to reopen under new ownership Monday morning. A naive weekly histogram of this data looks like a metronome; group by month or quarter and the actual waves appear.
What fields does the dataset include?
Seven verified fields, and none of them are decoration. Bank Name and the City/State pair give identity and geography. Cert is the load-bearing column — the FDIC certificate number that joins a failure to every other cert-keyed dataset without fuzzy matching. Acquiring Institution answers the question everyone actually asks: who got the deposits?, reading as none on the minority of resolutions where no buyer appeared. Closing Date supplies the timeline. Fund ties the row to the insurance fund transaction that settled it.
We deliver the fields as recorded, including the small indignities of the raw publication — stray byte artifacts in headers, the dd-Mon-yy date formatting, the occasional blank acquirer — normalized on ingest so your pipeline never meets them. Anything beyond the seven-field core (resolution paperwork, receivership financials, payout outcomes, pre-2000 history) folds under additional fields on request rather than pretending to be part of the verified table.
Why do real estate operating companies watch bank failures?
Because a failed bank rearranges physical markets, not just balance sheets. Three channels run straight from this list to real estate operating income:
Lending relationships reset overnight. When an institution fails, its borrowers — including the developers, landlords and operators financing projects in your submarkets — wake up with a new lender who did underwrite none of them. The acquirer column tells you which surviving institutions absorbed which books, and therefore where credit standards shifted.
Branch networks change hands. Each headquarters city and state anchors a physical footprint; joined against a branch directory, the failure list maps the corridors and downtowns whose banking storefronts were consolidated away after every wave.
Receivership assets resurface. Failed lenders' owned and collateralized real estate re-enters local markets through the resolution process, and the timing comes from this list. The 2008-2013 rows mark exactly when that supply hit; the March 2023 rows flag the newest cohort.
A quarter-century of failures with dates and successors attached is, among other things, a history of where American credit pulled back — which is a history of where property markets had to stand on their own.
What is not in the list, and how do we handle it?
Three honest boundaries. First, the clock: the list begins at October 1, 2000. The savings-and-loan era and everything earlier live in other FDIC historical publications — we fold them in on request if your backtest needs the extra decades. Second, the depth: the core table records that a bank failed and who took the deposits, while the richer resolution paperwork, receivership financial statements and payout details ride alongside as supplementary layers rather than core columns. Third, the formatting: the raw publication carries minor byte-level artifacts in its headers, which we clean before delivery rather than shipping you a puzzle.
Everything else is there, one row per failure, cert numbers intact, from the first October 2000 entry to the most recent closing.
Field dictionary
Every field below is documented against real records. The full dictionary ships with the sample.
| Field | Type | Definition | Example |
|---|---|---|---|
Bank Name | string | Legal name of the institution at the moment regulators closed it — the row's human-readable identity, preserved exactly as recorded at resolution. | Small Business Bank |
City | string | City where the failed bank was headquartered, anchoring each failure to a physical market rather than a charter. | Lenexa |
State | string | Two-letter state abbreviation of the headquarters location, the field that turns the list into a map of where banking stress actually landed. | KS |
Cert | integer | FDIC certificate number of the failed institution — the stable identifier that joins a failure row to every other cert-keyed regulatory dataset without fuzzy matching. | 25744 |
Acquiring Institution | string | Institution that assumed the failed bank's deposits and assets; reads as none when no buyer stepped forward and depositors were paid out directly. | The Farmers State Bank of Oakley, Kansas |
Closing Date | date | The date regulators closed the bank and appointed the receiver — typically a Friday, which is why failure waves cluster on weekends in any time-series view. | 17-Jul-26 |
Fund | integer | Insurance fund sequence number assigned to the resolution, tying each failure row to the specific fund transaction that settled it. | 10553 |
Coverage chips
| Dimension | Coverage |
|---|---|
| Geography | United States — every state and territory where a covered institution failed, with headquarters city and state carried on each row |
| Temporal | October 1, 2000 through the most recent closing — roughly 577 failures as of July 2026, covering the 2008-2013 cascade and the March 2023 wave |
| Granularity | One row per failed institution; resolution-level supplements available on request |
Record families
| Record family | Contents |
|---|---|
| Core failure table | One row per failed institution since October 1, 2000 with name, geography, cert, acquirer, closing date and fund sequence |
| Resolution supplements | Per-bank resolution detail, receivership financial statements and depositor payout outcomes for the resolutions that carry them |
| Narrative histories | Year-by-year failure-wave accounts providing the context around each cluster of closings |
| Pre-2000 extension | Earlier failure records folded in from companion FDIC historical publications on request |
Additional fields on request
| Field group | Notes |
|---|---|
| Per-bank resolution detail | Each failure links to its own resolution record — press releases and closing documentation for the individual institution, folded into your extract when you want the narrative beside the numbers. |
| Receivership financial statements | Statements filed through the receivership process showing what the failed institution held when it went down, useful for sizing distressed asset flows. |
| Depositor payout records | How insured and uninsured deposits were resolved on the failures where no acquiring institution appears on the core row. |
| Bank Failures in Brief narratives | The FDIC's own year-by-year narrative accounts of each failure wave — context for why a cluster of closings happened when it did. |
| Pre-2000 failure history | Failures before October 1, 2000 sit outside this list in other FDIC historical publications; we fold them in on request so a century-scale backtest starts from one table. |
| Fund-sequence lineage | How the insurance fund numbering runs across assisted and non-assisted resolutions, so the Fund column can be read as history rather than treated as noise. |
What teams do with it
- Counterparty and deposit-franchise stress testing A treasury team reads which institutions actually failed in each prior stress episode — by size class, region and resolution type — instead of trusting a survivorship-cleaned sample.
- Branch network and market disruption mapping Joining failures against a branch directory shows where a closed bank's storefronts changed hands overnight — the retail corridors and commercial districts whose banking relationships got reassigned.
- Event studies across failure waves Precise closing dates let a quant line up the 2008-2013 cascade against the March 2023 failures and measure how deposits, equities and credit spreads reacted each time.
- Default and failure model training Five hundred seventy-seven labeled positive examples with cert keys ready to merge against call reports and financial panels — the ground truth every bank-health classifier needs.
- Acquirer consolidation research The acquiring-institution column reveals which buyers built scale by absorbing failed banks, a consolidation pattern invisible in organic-growth league tables.
- Distressed real estate flow tracking Operators and credit analysts trace where receivership-era asset pools surfaced — the failed lenders whose loan books and owned properties re-entered local markets during each wave.
Questions buyers ask
How far back does the failure history reach?
The list covers every bank placed into FDIC receivership since October 1, 2000 — roughly 577 institutions as of July 2026. Failures before that date sit in other FDIC historical publications rather than this table; if your research needs the pre-2000 record, we fold those sources into your extract so the whole span arrives as one continuous series.
What is the Cert field and why does it matter?
It is the FDIC certificate number — the permanent identifier issued to each insured institution. Because certs persist across every FDIC-keyed dataset, a failure row joins to call reports, financial panels and branch records on an exact match, no name-based fuzzy matching required. It is the difference between a list and a research-grade panel.
What does the Fund number represent?
The insurance fund sequence assigned to the resolution — the accounting thread connecting a failure row to the specific fund transaction that settled it. Read across the column, the sequences also encode resolution order within each wave, which makes them handy for reconstructing how a cascade unfolded week by week.
What happens on rows where no acquirer is listed?
Those are the resolutions where no institution stepped forward to assume the deposits, so account holders were paid out directly rather than transferred. They are a minority of the record but an analytically important one — the failures severe enough that nobody wanted the franchise. Payout detail for those cases folds in under additional fields on request.
Why do closing dates cluster on Fridays?
Regulators schedule failures at week's end deliberately: a Friday closing gives the acquiring institution the weekend to convert systems and reopen branches under new ownership Monday morning. Group the rows by month or quarter rather than day-of-week, and the genuine failure waves — 2008-2013, March 2023 — stand out clearly instead of drowning in a weekly metronome.
Which datasets pair well with the failed bank list?
Three complements cover the rest of the picture. The FDIC Bank Data Guide resolves any cert — failed or surviving — into its institutional profile. The Quarterly Banking Profile frames each failure wave inside the industry-wide earnings and deposit cycle it happened in. And the US Bank Locations branch directory turns headquarters locations into physical footprint maps, so a failure becomes a set of affected neighborhoods rather than an abstraction.
Datasets that pair with this one
- FDIC - source profile The insurer behind the list — its banking, supervision and resolution programs profiled end to end.
- FDIC Bank Data Guide Resolve any cert — failed or surviving — into its full institutional profile and financial history.
- FDIC Quarterly Banking Profile (QBP) Frame each failure wave inside the industry-wide earnings and deposit cycle it happened in.
- US Bank Locations Bank Branch Directory Turn headquarters locations into physical footprint maps — every branch a failed lender left behind.
- real estate operating companies data hub All primary datasets in this industry, ranked and cross-linked.
See the rows before you pay anything.
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