FFIEC Call Report data is useful because it forces every U.S. bank into a comparable regulatory format. The hard part is not finding the data. The hard part is knowing which fields answer which diligence question, and which signals belong together before you form an opinion about a bank.
This article narrows the job to one practical question: what can a 155-field FFIEC analytical set tell you before you ask for private data, a management call, or a loan tape?
The answer is more specific than "bank health." A good field set lets you read seven things quickly: balance-sheet shape, earnings power, loan mix, asset-quality migration, funding pressure, liquidity, and capital cushion. Used in that order, FFIEC data becomes a first-pass operating profile rather than a spreadsheet of regulatory codes.
Scope note: Banking Intelligence local FFIEC detail coverage referenced here runs through the 2025-12-31 reporting date. The 155 count means distinct populated Call Report line-item codes in the local analytical set across RC, RC-B, RC-C, RC-E, RC-L, RC-M, RC-N, RC-O, RC-R, RC-T, RI, and RI-B. Derived ratios are discussed, but they are not counted as separate regulatory fields.
Start With The Decision, Not The Schedule
The most common mistake is opening a Call Report and reading it schedule by schedule. That is how the document is filed, but it is not how a diligence question gets answered. A fintech founder evaluating a sponsor bank, an investor screening community banks, and a vendor building a prospect list all need the same first move: convert fields into decision categories.
Use this sequence:
- Size and shape: Is this a small relationship bank, a CRE-heavy lender, a securities-heavy balance sheet, or a large diversified institution?
- Earnings: Is the bank producing enough pre-provision income to absorb credit and funding stress?
- Loan mix: Where is credit risk concentrated before losses appear?
- Asset quality: Are borrowers moving from current to delinquent to nonaccrual to charge-off?
- Funding and liquidity: Does the bank rely on stable deposits, rate-sensitive deposits, brokered deposits, or wholesale borrowing?
- Capital: Is the risk manageable relative to equity and regulatory capital?
That structure also fixes the problem with isolated ratios. A high CRE concentration means something different at a well-capitalized bank with strong deposits than it does at a thinly capitalized bank funding loan growth with brokered deposits.
The 155-Field Map
The point of 155 fields is not to make the reader inspect 155 rows. It is to make sure each major diligence question has enough coverage to avoid false confidence. The table below groups the full analytical set by question, schedule, and use case. Counts sum to 155 and reflect the local populated field inventory for 2025-12-31.
| Question | Field count | Main schedules | What the fields tell you | Example codes |
|---|---|---|---|---|
| Size and balance-sheet shape | 22 | RC, RC-B | Total scale, asset mix, loan intensity, securities exposure, equity base, and whether the bank is balance-sheet-light or balance-sheet-heavy. | RCON2170, RCON2200, RCON3210 |
| Funding and liquidity | 24 | RC-E, RC-M, RC-O, RC-L | Deposit base, uninsured deposits, brokered deposits, borrowed money, FHLB advances, and off-balance-sheet liquidity obligations. | RCONB528, RCONA564, RCON6810 |
| Earnings power | 23 | RI | Net income, net interest income, fee income, expense load, provision expense, and whether profits are recurring or fragile. | RIAD4340, RIAD4107, RIAD4093 |
| Loan mix and concentration | 30 | RC-C, RC-R | Exposure by loan type, including construction, non-owner-occupied CRE, residential, C&I, agricultural, consumer, and other loan categories. | RCFN1420, RCON1766, RCON1590 |
| Asset quality and loss migration | 26 | RC-N, RI-B | 30-89 day delinquency, 90+ day delinquency, nonaccrual loans, charge-offs, recoveries, and allowance coverage. | RCON5525, RIAD4635, RCONG641 |
| Capital and solvency cushion | 18 | RC, RC-R | Equity, risk-based capital, leverage, CET1 capital, and the cushion available against loan and concentration risk. | RCON3368, RCON7205, RCON7204 |
| Fiduciary, off-balance-sheet, and context fields | 12 | RC-T, RC-L, RC-M | Trust activity, unused commitments, letters of credit, other real estate owned, and context that can matter for specialized banks. | Schedule-specific RC-T, RC-L, RC-M items |
That map is also a workflow. Start at the top, then move down only when the prior category raises or clears a question.
A Worked First-Pass Read
Here is how the field map works in practice. The example below is an anonymized single-bank screen built to show the method, not an investment recommendation or a statement about a specific live institution.
| Field | Example value | First-pass read |
|---|---|---|
| RCON2170: total assets | $4.2 billion | Large enough for meaningful specialization, small enough that concentration can dominate the story. |
| RCON2200: total deposits | $3.3 billion | Deposits fund most of the balance sheet, but the next question is whether they are stable or rate-sensitive. |
| RCONA564: brokered deposits | $620 million | Brokered deposits are deposits placed through third-party brokers or listing services; this level suggests funding may be more rate-sensitive than a plain deposit total implies. |
| RCON6810: FHLB advances | $410 million | FHLB means Federal Home Loan Bank. Advances can be useful liquidity, but rising reliance often signals funding pressure or loan growth ahead of core deposits. |
| RCFN1420: non-owner-occupied CRE | $1.1 billion | CRE means commercial real estate. This is a large exposure relative to the bank’s asset size and needs to be compared with capital. |
| RCON3368: total risk-based capital | $505 million | CRE is roughly 2.2x total risk-based capital in this example, so concentration is material even before losses appear. |
| RCON5525: noncurrent loans | $72 million | Noncurrent loans are loans 90+ days past due or on nonaccrual. This is the first asset-quality check after loan mix. |
| RIAD4635: net charge-offs | $11 million | Charge-offs are losses recognized through earnings. Modest current charge-offs do not erase the concern if delinquency and nonaccrual are moving up. |
The first-pass conclusion is not "good bank" or "bad bank." It is narrower and more useful: this bank deserves a deeper look at funding stability and CRE credit migration. The next diligence questions are clear: how much of the CRE book is office or construction, how much of the deposit base is uninsured or rate-sensitive, whether FHLB reliance has increased quarter over quarter, and whether early-stage delinquencies are leading nonaccruals.
That is what a structured FFIEC read should produce: a short list of real questions, not a generic health score.
The Schedules That Matter Most
FFIEC data comes from standardized Call Report filings made available through the Central Data Repository and related FFIEC materials.[1] The useful schedules are not interchangeable:
- RC: the balance sheet. Use it for assets, deposits, liabilities, equity, securities, loans, and borrowed money.
- RI: the income statement. Use it for revenue, expense, provision, and net income.
- RC-C: loan composition. Use it to see whether the bank is concentrated in CRE, C&I, residential, construction, consumer, or specialty lending. C&I means commercial and industrial lending.
- RC-N: past due and nonaccrual loans. Use it to detect credit deterioration before it fully hits charge-offs.
- RI-B: charge-offs and recoveries. Use it to separate emerging stress from realized loss.
- RC-E and RC-O: deposits and other deposit-related detail. Use them for uninsured deposits, brokered deposits, and deposit mix.
- RC-R: regulatory capital. Use it for leverage, risk-based capital, and CET1, which means Common Equity Tier 1 capital.
- RC-L, RC-M, RC-T: off-balance-sheet, other assets, and fiduciary context. Use them when commitments, other real estate owned, or trust activity matter to the bank’s business model.
UBPR data can help with peer comparison once the bank’s own profile is clear, but it should not replace the field-level read.[2] Peer ranks are useful after you know what you are comparing.
How To Avoid The Three Bad Reads
Bad read one: profitability without credit context. Return on assets, or ROA, measures net income relative to assets. Return on equity, or ROE, measures net income relative to equity. Both can look fine while early delinquencies are building. Pair RI earnings fields with RC-N delinquency and nonaccrual fields before you treat profitability as durable.
Bad read two: loan growth without funding context. Loan growth funded by core relationship deposits is different from loan growth funded by brokered deposits, higher-cost deposits, or FHLB borrowing. A sponsor-bank screen should care about this because sponsor-bank relationships depend on operational resilience, not just balance-sheet size.
Bad read three: concentration without capital. CRE-to-capital and construction-to-capital are not judgment by themselves. They are pressure tests. A concentrated bank with thick capital, strong reserves, and low delinquency may be manageable. The same concentration with thin capital and rising nonaccruals is a different risk profile.
Mini Glossary For Non-Bank Analysts
- NPL: nonperforming loan, usually loans that are nonaccrual or 90+ days past due.
- Nonaccrual: a loan where the bank has stopped accruing interest income because collection is doubtful.
- ROA: return on assets, a profitability measure scaled to total assets.
- ROE: return on equity, a profitability measure scaled to shareholder equity.
- CET1: Common Equity Tier 1 capital, a core regulatory capital measure.
- CRE: commercial real estate. Non-owner-occupied CRE often carries different risk than owner-occupied property.
- C&I: commercial and industrial loans to businesses.
- FHLB: Federal Home Loan Bank. Member banks can borrow through advances, often secured by eligible collateral.
- Brokered deposits: deposits gathered through deposit brokers or placement networks, often more rate-sensitive than local relationship deposits.
- Sponsor-bank screening: diligence on a bank that provides regulated banking services behind a fintech, payments, card, or embedded-finance program.
Methodology: How The 155 Count Was Derived
The 155-field count is not a count of every possible Call Report item. It is the count of distinct populated Call Report line-item codes exposed in the Banking Intelligence local analytical detail snapshot for the 2025-12-31 reporting date. The underlying public data comes from the FFIEC Central Data Repository; the December 31, 2025 reporting cycle is also addressed in FFIEC-related Call Report instructions and notices.[1][3]
The count excludes internal labels, bank identifiers, display-only fields, and calculated ratios created after ingestion. It includes populated regulatory line items from RC, RC-B, RC-C, RC-E, RC-L, RC-M, RC-N, RC-O, RC-R, RC-T, RI, and RI-B. Field definitions and MDRM code references should be checked against official FFIEC and Federal Reserve data-dictionary materials when exact reporting treatment matters.[4]
That distinction matters. A product can expose 155 useful regulatory fields without claiming to replace the full Call Report, and a reader can use those 155 fields without pretending every field carries equal analytical weight.
Where Banking Intelligence Fits
For readers who want to move from manual review to workflow, Banking Intelligence keeps the public diligence layer in one place. You can search institutions in Banks, review source coverage on the data-sources page, wire fields into internal workflows through API Docs, or monitor changes with Alerts.
The practical value is speed before expensive diligence. FFIEC fields will not answer every private credit question, but they can tell you where the real questions are.
Bottom Line
FFIEC data is valuable because it is standardized, recurring, and comparable. It becomes more valuable when it is read as a field map: structure first, earnings second, credit and funding together, and capital last as the context for risk.
A 155-field set is enough to build that first-pass view. It can show whether a bank is conservatively funded, stretching for growth, concentrated in a risky loan segment, absorbing credit deterioration, or carrying enough capital to make the risk manageable. That is the difference between having public bank data and being able to use it.
Sources
- [1] FFIEC Central Data Repository, Call Report Bulk Data: https://cdr.ffiec.gov/public/PWS/DownloadBulkData.aspx
- [2] FFIEC, Uniform Bank Performance Report: https://www.ffiec.gov/UBPR.htm
- [3] FDIC, Consolidated Reports of Condition and Income for Fourth Quarter 2025: https://www.fdic.gov/news/financial-institution-letters/2026/consolidated-reports-condition-and-income-fourth-quarter
- [4] Federal Reserve, MDRM Data Dictionary: https://www.federalreserve.gov/apps/mdrm/data-dictionary