Raymond James Bank is a nationwide lender of very large loans: its typical loan was $805,000, against $195,000 at similar lenders, and 42.8% of its loans were jumbo.
Jumbo loans across 50 states
Jumbo loans (larger than the conforming limit) were 42.8% of its lending, against 3.0% at similar lenders (state member banks making between half and twice as many loans); its typical loan was higher than at nearly all of them. It lent $1.85 billion, against peers' $450.6 million, across 50 states and 211 metros. It ranked 73 of 925 in Tampa-St. Petersburg-Clearwater, its home market, and 150 of 802 in New York-Newark-Jersey City.
Faster growth than most peers
Originations rose 26% to 1,712, against 7% at similar lenders and 10% for the whole market, higher than about nine in ten. Home purchases were 61.6% of its loans. It also bought 248 loans, where the typical peer bought none.
Few LMI borrowers
LMI (low- and moderate-income) borrowers took 1.2% of its loans, against 26.8% at peers, lower than nearly all of them, and down from 7.0% five years before. Loans in LMI areas were 5.0%, against 15.1%. The size of its loans is one possible reason: loans of this size tend to go to high-income borrowers. Its share in majority-minority areas, 7.9%, was near peers' 7.1%.
Lower rates than peers
Its typical rate was 5.38%, against 6.88% at similar lenders, lower than nearly all of them, and its higher-priced share (a rate well above the average for similar loans) was 0.1%, against 1.3%.
Questions the data can answer next
How does its jumbo lending in New York, Los Angeles and Miami compare with other jumbo lenders' there?
Similar lenders: same lender type, originations between half and twice the lender's in the data year.
Written from the 2025 HMDA data and checked figure by figure against it.
FIG. 1 — LOANS ORIGINATED, 2018–2025
1,712 loans in 2025, against a peak of 1,821 in 2022.
Originated means the loan was made: applications denied, withdrawn or not accepted are not counted. Raymond James Bank took 2,077 applications in 2025.
61.6% of its 2025 loans were purchase loans; 99.9% were Conventional.
Purchase 61.6% · Other 24.9% · Refinance 12.9% · Home improvement 0.6% Conventional 99.9% · FHA 0.1% · of 1,712 loans. Purchase: buying a home. Refinance: replacing an existing mortgage, including cash-out. FHA: insured by the Federal Housing Administration. VA: guaranteed by the Department of Veterans Affairs. Conventional: neither.
SOURCE: FFIEC HMDA 2025, LOANS ORIGINATED
Where it lends, 2025
50 states, 211 metros, 499 counties
State
Loans
Share
Florida
298
17.4%
Texas
142
8.3%
California
122
7.1%
North Carolina
99
5.8%
New York
75
4.4%
Colorado
74
4.3%
Tennessee
69
4.0%
Georgia
58
3.4%
South Carolina
54
3.2%
New Jersey
49
2.9%
Largest metro areas, 2025
Loans originated
Metro area
Loans
New York-Jersey City-White Plains
61
Los Angeles-Long Beach-Glendale
46
Tampa
44
Dallas-Plano-Irving
33
Nashville-Davidson--Murfreesboro--Franklin
33
Houston-Pasadena-The Woodlands
32
Phoenix-Mesa-Chandler
32
St. Petersburg-Clearwater-Largo
32
Atlanta-Sandy Springs-Roswell
28
Charlotte-Concord-Gastonia
27
Identifiers
LEI (Legal Entity Identifier, the global company code HMDA has used since 2018)
ZXMJHJK466PBZTM5F379
2018–2025
RSSD (the Federal Reserve's identifier for banks and their parents)
2193616
2004–2023
Respondent ID (the HMDA filer code before 2018)
412002
1996–2010
Respondent ID (the HMDA filer code before 2018)
1712002
2011–2012
Respondent ID (the HMDA filer code before 2018)
92193616
2013–2017
Established 6 May 1994. Reported under HMDA 1996-2025.
Raymond James Bank and its peers, 2018–2025: every application in the HMDA data, cleaned and corrected, as Parquet files, with the Jenner programs that made these pages.
Every mortgage application reported under HMDA from 1990 to 2025, cleaned and corrected, every lender followed across name changes and mergers, with the market-share and fair-lending tables behind these pages and the Jenner programs that built them: the warehouse and the datamart, as Parquet files.
Jenner runs programs written in the SAS language. It drew every chart on these pages and fitted the fair-lending model, PROC GLIMMIX on 3.5 million applications. Run the programs that come with the data, or your own.