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Derived table · PPP

Top 500 PPP lenders by loan count

The 500 lenders with the most PPP loans, ranked, with a lender category, dollars, average loan, reported jobs, distinct borrowers, and loans per borrower.

Rows500
Columns12
Files1 · 53 KB
FormatCSV
Source vintageSBA PPP FOIA 2024-09-30
Published byPandemic Darlings
Acquired / built2026-07-10
Releasepandemic-darlings-data-v1-2026-07-10
Built fromSBA PPP FOIA loan-level files
SHA-2562696c92cc610c5f1c7312cd0ec2ad717a3fd43f829e6f135438557018bd9f5f0
RightsDerived from U.S. government public data; attribution to Pandemic Darlings requested for the compiled table.
Schema · dictionaryppp-top500-lenders-by-count.json · dictionary.csv

Download CSV 53 KBData dictionary CSVAt a glancePreviewColumnsHow to useBefore you quote a row

At a glance

The file as published folds nine partner lenders into two 'aggregator network' rows, so those nine lenders have no row of their own in it and the two network rows are not values of SBA's originating-lender field. The lender pages and rankings now rank every originating lender on its own and show the networks unranked beside them; a table rebuilt that way follows in the next data release. The lender index covers the 500 lenders with the largest approved-dollar books, so 110 of the 500 lenders in this file have no page there.

Measured on the served file on 2026-09-12; the checksum above is the file these numbers describe.

Rows500
Columns12
Keyrank · unique
Cells left blank0 of 6,000 · 0.0%
Loans in the 5009,418,934 · 82.1% of PPP
Approved dollars$642.5 billion
Distinct borrowers8,374,355
Loans per borrowermedian 1.10 · max 1.31
Lenders in the top 500 by category — counts rows of ppp-top500-lenders-by-count.csv by the category column.
Lenders in the top 500 by categoryHorizontal bars, one per lender category, length proportional to how many of the 500 lenders carry it.COMMUNITY_BANK404BIG_BANK32CREDIT_UNION25FINTECH21CDFI9OTHER7AGGREGATOR2
The numbers behind this chart
CategoryLenders
COMMUNITY_BANK404
BIG_BANK32
CREDIT_UNION25
FINTECH21
CDFI9
OTHER7
AGGREGATOR2
PPP loans made by each category of top-500 lender — sums the loans column of ppp-top500-lenders-by-count.csv by category.
PPP loans made by each category of top-500 lenderHorizontal bars, one per lender category, length proportional to the sum of loans across lenders in that category.BIG_BANK2.7MCOMMUNITY_BANK2.5MAGGREGATOR2.3MFINTECH1.7MCREDIT_UNION136KCDFI67KOTHER23K
The numbers behind this chart
CategoryLoans
BIG_BANK2.7M
COMMUNITY_BANK2.5M
AGGREGATOR2.3M
FINTECH1.7M
CREDIT_UNION136K
CDFI67K
OTHER23K

What it is

The top 500 rows of the per-lender totals table when ranked by number of loans. Three fields are added: a lender category, the number of distinct businesses the lender lent to, and loans_per_business. Loans per business runs above 1 where a lender made both a first-draw and a second-draw loan to the same borrower.

By category the 500 are 404 community banks, 32 big banks, 25 credit unions, 21 fintechs, 9 community development financial institutions, 7 others, and the 2 aggregator networks.

How it was built

The two network rows consolidate the whole PPP books of the Womply and Blueacorn partner lenders, so they bound rather than measure platform-sourced volume. Rows come from the per-lender totals table, so the aggregator consolidation and the field definitions are the same. Categories are assigned by lender name from a fixed classification list. Distinct businesses are counted by lower-cased borrower name plus five-digit ZIP within the lender's loans; for the two networks the count is taken across all partner lenders, so a business that borrowed through two Womply partners is one business.

This archive's Womply count is built differently and stands at more than 1,293,428 loans: court-record figures for three partner lenders plus the 2021 loans of four more, set out on Womply loan count. The Womply row in this file is the whole-book figure described above.

Preview

ranklendercategoryloanspct_program_loansdollarsavg_loanjobsjobs_per_loandollars_per_jobbusinessesloans_per_business
1Womply (aggregator network)AGGREGATOR141332312.323824196074246.2517119.9920028181.417112081.0110761471.313
2Blueacorn (aggregator network)AGGREGATOR8401397.325813063325741.1715549.018625101.026615145.718338001.008
3Bank of America, National AssociationBIG_BANK4910344.281734411968884.5970080.6242221598.59858150.334264771.151
4Cross River BankFINTECH4788664.175612894672292.9326927.5214383703.00378964.784352871.1
5JPMorgan Chase Bank, National AssociationBIG_BANK4528923.949144111851716.6997400.38710091215.6796212.144048921.119
6Wells Fargo Bank, National AssociationBIG_BANK2807172.447813777713764.6949080.4417472456.22427885.392538391.106
7Customers BankFINTECH2496612.1776330041848.5625354.557702473.08528218.22335571.069
8U.S. Bank, National AssociationBIG_BANK1748221.524410814946837.0161862.6212962067.41448343.541570791.113
9Itria Ventures LLCFINTECH1728311.5074867055202.5228160.784741872.743610264.01629491.061
10Celtic Bank CorporationFINTECH1672011.4584494635837.4826881.636233663.72827210.271547101.081

First 10 of 500 rows · cells longer than 60 characters are cut with an ellipsis · shown as text, unformatted.

Files

FileRowsSizeSHA-256
ppp-top500-lenders-by-count.csv
CSV, UTF-8, header row
50054,415 B2696c92cc610c5f1c7312cd0ec2ad717a3fd43f829e6f135438557018bd9f5f0Download ↓
dictionary.csv
data dictionary, 12 rows
12—built with this pageDownload ↓

Columns

ColumnType, measuredBlankDistinctRange / valuesMeaning
rankinteger05001 – 500 · median 250.50Position when sorted by loans, descending.
lendertext0500Lender name as in the SBA file, or an aggregator-network row.
categorytext07COMMUNITY_BANK (404), BIG_BANK (32), CREDIT_UNION (25), FINTECH (21), CDFI (9), OTHER (7)One of AGGREGATOR, BIG_BANK, COMMUNITY_BANK, CREDIT_UNION, FINTECH, CDFI, OTHER.
loansinteger04782K – 1.4M · median 4KNumber of PPP loans, both draws.
pct_program_loansnumber03640.02 – 12.32 · median 0.04Share of all 11,468,171 PPP loans, in percent.
dollarsnumber050032.1M – 44.1B · sum $642.5B · median $403.7MSum of current approved amounts, in dollars.
avg_loannumber05009K – 584K · sum $48.6M · median $86Kdollars ÷ loans.
jobsinteger04994K – 7.1M · median 49KSum of jobs reported on the applications.
jobs_per_loannumber05001.03 – 48.87 · median 9.99jobs ÷ loans.
dollars_per_jobnumber04994K – 16K · sum $4.4M · median $9Kdollars ÷ jobs.
businessesinteger04762K – 1.1M · median 4KDistinct borrowers (name + ZIP) among the lender's loans.
loans_per_businessnumber01631 – 1.31 · median 1.10loans ÷ businesses.

Type, blanks, distinct count, and range are measured on the file. The same table as CSV: dictionary.csv.

How to use it

Specific to this file, measured on it: keys, joins, encodings, units, and the values that will trip a naive count.

  • rank is the row key (1–500, no gaps); lender joins to the per-lender totals table by exact string, and every one of the 500 is present there.
  • category has 7 values: COMMUNITY_BANK (404), BIG_BANK (32), CREDIT_UNION (25), FINTECH (21), CDFI (9), OTHER (7), AGGREGATOR (2). It is assigned by name, so treat it as a label, not a charter type.
  • Money columns are in dollars (dollars, avg_loan, dollars_per_job); pct_program_loans is a percentage of all 11,468,171 PPP loans and sums to 82.1 for this table.
  • CRLF line endings, UTF-8, no byte-order mark; lender names are quoted because they contain commas.

Before you quote a row

  • Category is a name-based label, not a regulatory status; a lender that changed charter or name is classified as its name in the SBA file reads.
  • Borrower matching is by name and ZIP. A business that changed its name or address between draws counts twice; two businesses with one name in one ZIP count once.
Cite this table. Name the source vintage; the numbers depend on it.Top 500 PPP lenders by loan count, built from SBA PPP FOIA loan-level data (2024-09-30 vintage). Pandemic Darlings, release pandemic-darlings-data-v1-2026-07-10, https://pandemicdarlings.com/data/ppp-top500-lenders-by-count/, SHA-256 2696c92cc610c5f1c7312cd0ec2ad717a3fd43f829e6f135438557018bd9f5f0
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