TowneBank is a purchase lender with a large government-backed book, and in 2025 its share rose in its home Virginia Beach market and in Richmond.
Government lending well above peers
FHA (insured by the Federal Housing Administration) loans were 14.0% of its lending and VA (guaranteed by the Department of Veterans Affairs) loans 9.5%, against 4.5% and 2.0% at similar lenders (state non-member banks making between half and twice as many loans); its VA share was higher than about nine in ten of them. Purchases were 76.3% of its loans, and its typical loan was $315,000 against $240,000.
Gaining share at home and in Richmond
It ranks 8 of 577 lenders in Virginia Beach-Chesapeake-Norfolk, where its share rose to 3.1% from 2.8%, and in Richmond its share rose to 2.0% from 1.2%. Its 2025 mergers with Village Bank and Trust Financial and The Old Point National Bank of Phoebus, whose filings count as its own, may explain part of this. It also entered three Alabama markets in 2025.
Lower denial rates than peers
It turned down 3.4% of decided first-lien home-purchase applications on owner-occupied homes, against 7.4% at similar lenders, and 9.4% of refinance applications, against 15.7%, both among the lowest tenth.
Below its 2020 peak
Originations grew 15% to 5,837, near the middle of similar lenders, who grew 13%, but remain well below 15,004 five years before. Refinancing, now 11.3% of its loans, may have made up more of that earlier total.
Questions the data can answer next
Which Hampton Roads and Richmond counties carry its FHA and VA lending, and how do competitors' government shares compare 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
5,837 loans in 2025, against a peak of 15,004 in 2020.
Originated means the loan was made: applications denied, withdrawn or not accepted are not counted. TowneBank took 7,487 applications in 2025.
76.3% of its 2025 loans were purchase loans; 75.8% were Conventional.
Purchase 76.3% · Refinance 11.3% · Home improvement 8.6% · Other 3.8% Conventional 75.8% · FHA 14.0% · VA 9.5% · USDA (RHS or FSA) 0.7% · of 5,837 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
19 states, 101 metros, 310 counties
State
Loans
Share
Virginia
2,077
35.6%
North Carolina
1,749
30.0%
Maryland
1,552
26.6%
South Carolina
88
1.5%
Alabama
76
1.3%
Florida
62
1.1%
Pennsylvania
60
1.0%
Louisiana
41
0.7%
District of Columbia
36
0.6%
Delaware
22
0.4%
Largest metro areas, 2025
Loans originated
Metro area
Loans
Virginia Beach-Chesapeake-Norfolk
1,206
Baltimore-Columbia-Towson
722
Richmond
694
Raleigh-Cary
434
Charlotte-Concord-Gastonia
418
Frederick-Gaithersburg-Bethesda
365
Washington
285
Wilmington
153
Arlington-Alexandria-Reston
142
Greenville
132
Identifiers
LEI (Legal Entity Identifier, the global company code HMDA has used since 2018)
54930039UO39UJGI7078
2018–2025
RSSD (the Federal Reserve's identifier for banks and their parents)
2797724
2004–2023
Respondent ID (the HMDA filer code before 2018)
335095
2000–2017
Established 8 April 1999. Reported under HMDA 2000-2025.
Mergers, name changes, data editions and corrections: TowneBank's data.
The data and the software behind these pages
TowneBank's data
$215
TowneBank 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.