OCMBC grew 27% in 2025, faster than most similar lenders, and is the third-largest lender in Riverside-San Bernardino-Ontario, with a much larger share of its loans in majority-minority and LMI areas than its peers.
Growth well ahead of peers and the market
OCMBC made 16,337 loans, up from 12,877 the year before and 6,835 five years earlier. Its growth of 27% was higher than about two-thirds of similar lenders (independent non-bank lenders making between half and twice as many loans), whose typical growth was 14%, and than the whole market's 10%. Purchases were 60.5% of its loans and refinances 39.5%.
Third in Riverside-San Bernardino-Ontario
It ranked 3 of 707 lenders there, behind United Wholesale Mortgage and Rocket Mortgage, and its share rose to 2.9% from 2.4%. It has reported in the market since 2008, and in 2025 it entered smaller markets such as Tuscaloosa and Florence-Muscle Shoals.
Lending in minority and LMI areas, less to LMI borrowers
63.1% of its loans were in majority-minority areas and 34.6% in LMI (low- and moderate-income) areas, the highest shares among similar lenders, whose typical shares were 27.5% and 21.5%. Yet only 14.9% went to LMI borrowers, lower than about nine in ten peers. Larger loans are one possible reason, since its typical loan was $355,000 against $285,000 for peers; the mix of markets it serves could be another.
Mostly conventional loans
Conventional loans were 78.7% of the total, against 61.6% for peers, and FHA loans (insured by the Federal Housing Administration) were 19.3%, down from 30.2% five years earlier.
Questions the data can answer next
In which Riverside-San Bernardino-Ontario counties is its share growing fastest?
How do its loan sizes in majority-minority areas compare with its competitors'?
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
16,337 loans in 2025, its most in any year since 2018.
Originated means the loan was made: applications denied, withdrawn or not accepted are not counted. OCMBC took 29,739 applications in 2025.
60.5% of its 2025 loans were purchase loans; 78.7% were Conventional.
Purchase 60.5% · Refinance 39.5% Conventional 78.7% · FHA 19.3% · VA 2.0% · USDA (RHS or FSA) 0.0% · of 16,337 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
49 states, 332 metros, 950 counties
State
Loans
Share
California
7,327
44.8%
Florida
1,580
9.7%
Texas
1,270
7.8%
Maryland
564
3.5%
Illinois
454
2.8%
Arizona
439
2.7%
Georgia
412
2.5%
Nevada
368
2.3%
Massachusetts
335
2.1%
Virginia
312
1.9%
Largest metro areas, 2025
Loans originated
Metro area
Loans
Los Angeles-Long Beach-Glendale
2,632
Riverside-San Bernardino-Ontario
2,301
Houston-Pasadena-The Woodlands
498
Chicago-Naperville-Schaumburg
379
Anaheim-Santa Ana-Irvine
343
Bakersfield-Delano
321
Las Vegas-Henderson-North Las Vegas
310
Phoenix-Mesa-Chandler
308
Dallas-Plano-Irving
301
Miami-Miami Beach-Kendall
300
Identifiers
LEI (Legal Entity Identifier, the global company code HMDA has used since 2018)
549300J7I82PNDVU8H22
2018–2025
RSSD (the Federal Reserve's identifier for banks and their parents)
3955727
2010–2023
Respondent ID (the HMDA filer code before 2018)
7330962918
Established 9 March 2001. Reported under HMDA 2008-2025.
Mergers, name changes, data editions and corrections: OCMBC's data.
The data and the software behind these pages
OCMBC's data
$215
OCMBC 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.