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Popular BPOP BPPR — Prior Years
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Where this comes from
Reported directly by Popular in its filing.
Tagged under the XBRL concept us-gaap:FinancingReceivableOriginatedFiveOrMoreYearsBeforeLatestFiscalYear.
The source filing: Popular’s 10-Q, filed August 7, 2026.
- Filed
- Aug 7, 2026, 4:14 PM EDT
- Fiscal quarter
- Q2 FY2026
- Calendar quarter
- Q2 2026
- Accession
- 0000763901-26-000019
| (In thousands) | Term Loans Amortized Cost Basis by Origination Year / 2026 | Term Loans Amortized Cost Basis by Origination Year / 2025 | Term Loans Amortized Cost Basis by Origination Year / 2024 | Term Loans Amortized Cost Basis by Origination Year / 2023 | Term Loans Amortized Cost Basis by Origination Year / 2022 | Term Loans Amortized Cost Basis by Origination Year / Prior Years | Revolving Loans Amortized Cost Basis | Revolving Loans Converted to Term Loans Amortized Cost Basis | Total |
|---|---|---|---|---|---|---|---|---|---|
| Year-to-Date gross write-offs | $603 | $9,305 | $11,182 | $8,032 | $3,535 | $1,265 | $- | $- | $33,922 |
| Other consumer | |||||||||
| Pass | $14,468 | $30,799 | $18,708 | $14,362 | $13,833 | $4,231 | $63,788 | $- | $160,189 |
| Substandard | - | - | 9 | 2,208 | 29 | 133 | 325 | - | 2,704 |
| Loss | - | - | - | - | 478 | 698 | - | - | 1,176 |
| Total Other | $14,468 | $30,799 | $18,717 | $16,570 | $14,340 | $5,062 | $64,113 | $- | $164,069 |
| Year-to-Date gross write-offs | $5 | $204 | $78 | $99 | $750 | $1,174 | $- | $- | $2,310 |
| Total BPPR | $3,010,768 | $5,327,207 | $3,992,638 | $2,703,305 | $2,615,044 | $7,119,456 | $3,174,994 | $33,424 | $27,976,836 |
Item 1. Financial Statements
FAQ
- What is Popular's BPPR — prior years?
- Popular (BPOP) reported BPPR — prior years of $7.12B in Q2 2026.
- What does BPPR — prior years mean?
- Represents the aggregate financial performance or asset balances for the Banco Popular de Puerto Rico segment for all periods preceding the current multi-year reporting window. This metric provides historical context necessary for benchmarking current performance against long-term averages. It helps analysts normalize data and identify structural shifts in the segment's historical performance.
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