Applications / Mortgage Analytics / Lenders / Pennsylvania / Greater Pittsburgh Police Federal Credit Union
Pittsburgh, PA · Credit union · NCUA · $109 million assets · 68 loans in 2025
Greater Pittsburgh Police Federal Credit Union's data, $215Buy the data, $2,110Get Jenner, the SAS-compatible software
68
loans originated, 2025
81
applications, 2025
1
states and territories
0
gaps bigger than at similar lenders
Our analysis, 2025
Greater Pittsburgh Police Federal Credit Union makes no home-purchase loans; it lends small sums for home improvement, refinancing and other purposes, and it has more than doubled its lending since 2020.
Home improvement made up 36.8% of its loans, refinances 32.4% and other purposes 30.9%. Its typical loan was $55,000, against $95,000 at similar lenders (credit unions making between half and twice as many loans), among the lowest twentieth of the group.
It made 68 loans in 2025, up 17% from 58, faster than nearly two-thirds of similar credit unions, whose lending rose 7%. In 2020 it made 31. In 2025 it merged with Allegheny Co. No. 1 Federal Credit Union, which may account for some of the latest rise.
Its typical rate was 5.25%, against 6.75% at similar credit unions, among the lowest of the group. It made no higher-priced loans, those with a rate well above the average for similar loans; at similar lenders they were 3.1%.
It ranks 200 of 571 lenders in Pittsburgh, its only metro, with a share that rounds to 0.0%. PNC Bank and Rocket Mortgage lead. Low- and moderate-income (LMI) borrowers took 35.3% of its loans, against 30.9% at similar credit unions.
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
Originated means the loan was made: applications denied, withdrawn or not accepted are not counted. Greater Pittsburgh Police Federal Credit Union took 81 applications in 2025.
SOURCE: FFIEC HMDA, LOANS ORIGINATED (ACTION TAKEN: LOAN ORIGINATED)
FIG. 2 — PRODUCT MIX, 2025
Home improvement 36.8% · Refinance 32.4% · Other 30.9%
Conventional 100.0% · of 68 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
| State | Loans | Share |
|---|---|---|
| Pennsylvania | 68 | 100.0% |
Largest metro areas, 2025
| Metro area | Loans |
|---|---|
| Pittsburgh | 68 |
Identifiers
| LEI (Legal Entity Identifier, the global company code HMDA has used since 2018) | 5493001XNU40KOITE062 | 2018–2025 |
| RSSD (the Federal Reserve's identifier for banks and their parents) | 552572 | 2004–2023 |
| Respondent ID (the HMDA filer code before 2018) | 524 | 1998–2004 |
| Respondent ID (the HMDA filer code before 2018) | 5240 | 2005–2017 |
Established 1 January 1935. Reported under HMDA 1998-2025.
Mergers, name changes, data editions and corrections: Greater Pittsburgh Police Federal Credit Union's data.
Greater Pittsburgh Police Federal Credit Union's data
$215
Greater Pittsburgh Police Federal Credit Union 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.
Buy Greater Pittsburgh Police Federal Credit Union's data, $215Jenner Mortgage Analytics: all the data
$2,110
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.
Buy the data, $2,110Jenner, the SAS-compatible software
See prices
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.
Get JennerQuestions, or the data and Jenner together: [email protected]