Diversified Banks Data Provider · Head-to-head
BIS Locational Banking Statistics (LBS) & BIS Data Portal vs FDIC Quarterly Banking Profile (QBP)
Which diversified banks data provider data fits your job: BIS Locational Banking Statistics & BIS Data Portal, or FDIC Quarterly Banking Profile. API, files, or your warehouse. Daily, weekly, or hourly.
BIS Locational Banking Statistics (LBS) & BIS Data Portal
FDIC Quarterly Banking Profile (QBP)
Where the fields line up
No shared field names. These two answer different questions.
| Field | BIS Locational Banking Statistics & BIS Data Portal | FDIC Quarterly Banking Profile |
|---|---|---|
L_MEASURE / Measure | Measure carried by the series: S = amounts outstanding (stocks), F = FX- and break-adjusted change computed upstream so valuation swings do not read as new lending, G = annual growth, B = break in stocks. | not in this set |
L_POSITION / Balance sheet position | Side of the balance sheet the series describes: C = total claims, L = liabilities. | not in this set |
L_INSTR / Type of instruments | Instrument breakdown: A = all instruments, G = loans and deposits, D = debt securities, C = currency and deposits. | not in this set |
L_DENOM / L_CURR_TYPE | Currency denomination of the position - USD, JPY, EUR, TO1 for all currencies - with a flag for whether it sits in the reporting country's domestic or a foreign currency. | not in this set |
L_REP_CTY / Reporting country | Country whose banking offices disclose the position; about 50 reporter codes plus aggregates 5A = all reporting countries and 5C = euro area. | not in this set |
L_CP_SECTOR / Counterparty sector | Resident sector of the counterparty: A = all sectors, N = non-banks total, B = banks. | not in this set |
L_CP_COUNTRY / Counterparty country | Residence of the counterparty - more than 200 country codes plus aggregates such as 5J = all countries. | not in this set |
L_POS_TYPE / Position type | N = cross-border position; R = local position of foreign-owned offices in local currency vis-a-vis local residents. | not in this set |
COLLECTION / Collection Indicator | How the observation was collected: E = end of period, S = summed through the period. | not in this set |
FREQ | Observation frequency of the series; the published panel is quarterly. | not in this set |
<YYYY-Qn> value columns | One column per quarter from 1977-Q4 through 2026-Q1 carrying the observation in millions of US dollars, or the growth ratio the measure calls for. | not in this set |
Number of institutions reporting | not in this set | documented |
Coverage, side by side
| BIS Locational Banking Statistics & BIS Data Portal | FDIC Quarterly Banking Profile | |
|---|---|---|
| Geographic | Roughly 50 reporting countries; counterparties in more than 200 countries | United States |
| Temporal | 1977-Q4 through 2026-Q1 | Q1 1986 through Q1 2026 in verified editions; more than 160 quarters deep |
What each contains
They tie on 1 attribute. Pick by fit, not by loyalty.
| BIS Locational Banking Statistics & BIS Data Portal | FDIC Quarterly Banking Profile | |
|---|---|---|
| Publisher | Bank for International Settlements (compiled under the Committee on the Global Financial System) | Federal Deposit Insurance Corporation (FDIC) |
| Subject lens | Cross-border claims and liabilities of internationally active banks, from the residence perspective of the banking office | Aggregate earnings, balance-sheet, loan-performance and problem-bank lines for all FDIC-insured institutions |
| Geographic coverage | Roughly 50 reporting countries; counterparties in more than 200 countries | United States |
| Temporal coverage | 1977-Q4 through 2026-Q1 | Q1 1986 through Q1 2026 in verified editions; more than 160 quarters deep |
| Detail level | Series keyed by measure x position x instrument x currency x reporting country x counterparty sector and country x position type | Industry aggregates with subtotals by asset size group and community-bank status |
| Formats | CSV (column and flat layouts), SDMX 2.1, XLSX templates | XLSX workbooks, PDF reports |
| Scale | 609,065 series rows across 225 columns in the current panel | About 3 MB of Excel workbooks per quarter across a 160-plus-quarter run |
| Documented fields | 11 | 10 |
| Delivery | Daily, weekly, or hourly - your call | Daily, weekly, or hourly - your call |
| Best for | Corridor questions: who holds whose claims, in which currency, across which borders | US industry benchmarks: profitability, margins, provisioning and problem banks by size and charter cohort |
What each does better
BIS Locational Banking Statistics & BIS Data Portal
Cross-border dimensionality nobody else matches. Positions are recorded from the residence perspective of the banking office, on an unconsolidated basis that keeps intragroup positions between offices of the same group, and BIS estimates the framework captures around 95 percent of all cross-border banking activity. Reading who lends to whom, in which currency, starts here; see locational banking statistics.
Currency decomposition with derived flows. Every stock splits by denomination - USD, JPY, all-currency totals - and four measure types ride alongside: amounts outstanding, FX- and break-adjusted change, annual growth, and breaks in stocks. Those adjusted deltas approximate underlying flows that raw stocks obscure.
Depth. Quarterly positions reach back to 1977-Q4, nearly five decades of history in a single panel - the longest continuous record of its kind in this slice.
FDIC Quarterly Banking Profile
A whole-industry P&L in one place. Q1 2026 printed ROA of 1.26 percent and USD 80.5 billion of aggregate net income, up 3.6 percent quarter over quarter; full-year 2025 closed at USD 295.6 billion. Every FDIC-insured institution sits inside those numbers.
Cohort texture the headline figures hide. Lines repeat across asset-size groups - all insured institutions, under USD 100 million, USD 100 million to 1 billion, and larger bands - and across community versus non-community status. Each aggregate carries the number of institutions reporting, so a ratio can be weighed by its base, and counts of unprofitable institutions expose how widely stress spreads beneath an average.
Regulator-grade line items. Provisions, net charge-offs, noninterest income and expense, deposit-insurance-fund trends, net interest margin context - defined the way supervisors define them, stacked more than 160 quarters deep since Q1 1986; see the FDIC Quarterly Banking Profile primer.
Where they're equivalent
More than their industries suggest. Both field dictionaries were verified during research, a bar not every record clears. Both observe at quarterly grain, placing them among the 122 of 1,744 cataloged datasets whose observations run quarterly. Both ship as tabular files with documented columns - 11 and 10 respectively - and both score well above the catalog's 7.81 average. Both publishers are official-sector statisticians, and both records sit on the industry brief's headline list of eight.
The verdict
Verdict: sample both, pick by fit - they are different instruments pointed at the same industry.
Take BIS Locational Banking Statistics (LBS) & BIS Data Portal if your question names a border. Japanese banks' yen positions, European claims on emerging-market counterparties, the currency mix of cross-border funding, intragroup flows inside global banking groups - anything keyed by who-lends-to-whom. Accept country-and-sector cells: no individual institution appears.
Take FDIC Quarterly Banking Profile (QBP) if your question names American bank economics. Margin direction, provisioning cycles, profitability by asset size, community-bank performance, problem-bank counts - the whole-industry P&L with cohort subtotals. Accept industry aggregates: no single bank is named either.
Investors and quants tend toward the first for exposure factors and backtests; market researchers and consultants toward the second for benchmarking work. Cut both samples to the same quarters and let returned rows decide.
Sample both, pick by fit. See BIS Locational Banking Statistics & BIS Data Portal · See FDIC Quarterly Banking Profile
Or take both in one feed
Yes - they stack because they occupy different layers of the same system. A defensible workflow: let the QBP set the domestic backdrop - margin direction, provisioning pace, profitability by size band - then read LBS for the cross-border structure behind it: where funding originates, which corridors grew, how dollar positions shifted.
Align on period and unit before joining. Both print amounts in millions of US dollars on quarterly grids, but LBS mixes growth and break measures alongside level stocks, so separate measures before summing anything. There is no shared identifier between them - one keys on country-by-country dimensions, the other on industry line items - so treat the pair as two lenses on one banking system, not one table. Browse the rest of the shelf at the diversified banks data hub.
Datadory ships either record alone or both merged onto one calendar, delivered daily, weekly, or hourly - your call. Or take both in one feed.
API, files, or your warehouse. Daily, weekly, or hourly.
Fair questions
Is BIS Locational Banking Statistics (LBS) & BIS Data Portal better than FDIC Quarterly Banking Profile (QBP)?
Better at different jobs. LBS wins whenever the question crosses a border: 609,065 series keyed by reporting country, counterparty country, sector, instrument and currency, running from 1977-Q4. QBP wins whenever the question is American bank economics: 1.26 percent ROA and USD 80.5 billion of aggregate net income in Q1 2026. Rubric scores: 10/10 against 9/10.
Do the two datasets cover the same ground?
One concept genuinely overlaps - the quarterly observation - and little else. LBS decomposes positions into dimensions down to counterparty country and currency denomination; QBP aggregates line items such as provisions and net charge-offs by asset-size band and community-bank status. One carries geography in its keys; the other carries a single country in its frame.
Which dataset reaches further back?
LBS runs quarterly stocks from 1977-Q4, one column per quarter through 2026-Q1 in the current panel. QBP stacks aggregates from the quarter ended March 31, 1986, more than 160 quarters deep. For global banking history before the mid-1980s, only one of the two exists.
Which should a regional-bank analyst sample first?
Start with QBP - regional banks are a tagged secondary industry on that record, and the asset-size and community-bank sheets read like a peer benchmark waiting to happen. Add LBS when the question turns wholesale: funding corridors, counterparty-country exposure, currency mix of US offices. Sample both and let returned rows settle it.
Can Datadory deliver both datasets together?
Yes - alone or merged onto one calendar, delivered daily, weekly, or hourly, your call. Each arrives normalized to its documented field dictionary (eleven fields on the LBS side, ten on QBP's) with sample rows attached for validation, and the pair joins on period once units are agreed. Or take both in one feed.