DRCCLACBS: US Credit Card Delinquency Rate Quarterly from FRED (1991–2026)

The US Credit Card Delinquency Rate tracks the share of credit card balances at commercial banks at least 30 days past due, quarterly since 1991, from the Federal Reserve Board. It is the fastest-reacting gauge of household credit stress: unsecured, high-rate, and the first payment consumers miss. The range runs from 6.77% at the 2009 peak to 1.53% at the stimulus-era floor of 2021; after a post-2022 normalization that peaked at 3.22% in early 2024, the rate stood at 2.92% in early 2026.

Dataset: US Credit Card Delinquency Rate (1991–2026) · Updated 2026-01-01

Source: Board of Governors of the Federal Reserve System · FRED series DRCCLACBS

Macro Takeaway

Dataset Overview

Dataset Variables

The CSV and Excel files contain the following columns.

A value of 2.92 means 2.92% of credit card balances at commercial banks were at least 30 days past due.

Download the Complete Dataset

The full dataset is available in CSV and Excel formats.

FRED Direct CSV Access

The underlying data is available from FRED under series code DRCCLACBS:

https://fred.stlouisfed.org/graph/fredgraph.csv?id=DRCCLACBS

Direct CSV Access — Eco3min Structured Dataset

https://eco3min.fr/dataset/credit-card-delinquency.csv

This URL returns the complete dataset in CSV format. It can be used directly in pandas, R, curl, or any data tool.

Using the Dataset in Python

import pandas as pd

url = "https://eco3min.fr/dataset/credit-card-delinquency.csv"
df = pd.read_csv(url, parse_dates=["date"])

print(f"Latest: {df['cc_delinquency_rate'].iloc[-1]:.2f}% of balances 30+ days past due")
print(df.tail())

Using the Dataset in R

library(readr)

url <- "https://eco3min.fr/dataset/credit-card-delinquency.csv"
df <- read_csv(url)

tail(df)
summary(df$cc_delinquency_rate)

Both examples load the dataset directly from the URL — no download or API key required.

Methodology

The Federal Reserve Board computes delinquency rates from the quarterly Consolidated Reports of Condition and Income (“call reports”) filed by all US commercial banks. A loan is delinquent when 30 days or more past due (still accruing) or in nonaccrual status; the rate is delinquent balances over total balances, seasonally adjusted.

The series therefore measures bank-held card loans — it excludes cards issued by non-bank finance companies and securitized balances moved off bank balance sheets, a scope that has shifted over decades as issuance structures changed.

This dataset is updated daily (Mon–Sat, 08:00 UTC) via automated pull from the FRED API; new observations appear with each source release.

Data Quality & Provider Notes

• Release latency. Published ~2 months after quarter end with the Board’s charge-off and delinquency release.
• Revisions policy. Minor — call-report corrections occasionally adjust recent quarters by a few basis points.
• Universe. All US commercial banks; non-bank issuers and securitized pools excluded. Coverage of the card market varies over time with securitization practice.
• Alternative measures. NY Fed Consumer Credit Panel (all lenders, 90+ day, borrower-level) runs on a different definition and level; the two series can diverge for quarters at a time.
• Known gaps. None; continuous since Q1 1991.

Common Pitfalls When Using Card Delinquency Data

1. Reading normalization as deterioration. The 2022–2024 climb retraced an artificial stimulus floor; against the 1991–2007 range, the 2024 peak (3.22%) was unremarkable. Rate-of-change alarmism without level context misread this episode for two years.
2. Assuming full market coverage. Bank-held balances only. Subprime and non-bank stress — where post-2022 deterioration concentrated — is partly invisible here.
3. Confusing delinquency with charge-offs. Delinquency (30+ past due) leads charge-offs (written off, ~180 days) by roughly two quarters; the two rates answer different questions.
4. Treating it as a leading indicator. Card delinquency follows employment income; it confirms consumer stress rather than predicting the cycle.

Historical Regimes

1991–1997 — The first consumer credit wave. The rate climbed from ~4.5% toward 5.5% mid-decade as card penetration expanded faster than underwriting discipline — elevated delinquency in a growing economy.

1998–2007 — The 4–5% plateau. A structurally high but stable range; the 2001 recession barely registered — card stress was chronic, not cyclical.

2008–2009 — The GFC peak. Delinquency hit the series record of 6.77% (Q2 2009) as unemployment doubled — the only episode where the rate exceeded 6%.

2010–2019 — The great deleveraging. A decade-long decline to a 2.58% average in 2019: post-crisis underwriting (CARD Act, tighter scoring) structurally lowered the delinquency regime.

2020–2021 — The stimulus floor. Transfers, forbearance, and forced saving drove the rate to an all-time low of 1.53% (Q3 2021) — delinquency fell during a recession for the first time in the record.

2022–2026 — Normalization and plateau. A steep climb to 3.22% (Q1 2024) as stimulus effects faded and card rates hit records, then stabilization near 2.9% — above 2019, below every pre-2010 norm.

Related Macroeconomic Datasets

Card delinquency is the unsecured edge of household credit; the series below complete the balance-sheet picture.

Macroeconomic Dataset Hub

This dataset is part of the Eco3min macro-financial data repository.

Sources

• Board of Governors of the Federal Reserve System — Charge-Off and Delinquency Rates on Loans at Commercial Banks
• Federal Reserve Bank of St. Louis — FRED series DRCCLACBS

Dataset Reference