High-Risk Banks

About this dataset

High-Risk Banks is a Free dataset in the Risk & Failures group of the BankRegReports Data API. The response carries 27 documented fields, sourced from ML model.

Banks ranked by composite ML failure-risk screening score, highest first. The *_prob_* fields are uncalibrated screening scores that rank banks against each other; they are not probabilities of failure. Accuracy above about $10 billion in assets is not established. `prob_10yr` has not been validated out of sample (no 10-year test set has held both outcomes); each row says so in `field_notes`. Any signed-in account.

Endpoint

GET /api/v1/risk/high-risk-banks/

Parameters

Name	Required	Description
limit	optional	Max rows (default 25). e.g. 25

Response fields

Field	Type	Description
rssd_id	integer	RSSD ID (count)
legal_name	string	Legal Name (text)
hq_state	string, nullable	Headquarters State (text)
total_assets	number (double), nullable	Total Assets (USD thousands)
failure_probability	number (double), nullable
risk_tier	string, nullable
composite_risk_score	number (double), nullable
prob_1yr	number (double), nullable
prob_3yr	number (double), nullable
prob_5yr	number (double), nullable
prob_10yr	number (double), nullable	10-year screening score. Not validated out of sample: no 10-year test set has held both outcomes (failed and survived banks), so the accuracy of this score is untested.
distress_prob_1yr	number (double), nullable
distress_prob_3yr	number (double), nullable
distress_prob_5yr	number (double), nullable
acq_prob_1yr	number (double), nullable
acq_prob_3yr	number (double), nullable
acq_prob_5yr	number (double), nullable
field_notes	object	Machine-readable caveats for fields in this row. `prob_10yr` carries validated_out_of_sample=false.
rank_1yr	integer, nullable
percentile_1yr	number (double), nullable
rank	integer, nullable
rank_tied	boolean
peer_group	string, nullable
peer_rank_1yr	integer, nullable
peer_count	integer, nullable
prediction_date	string (date), nullable
report_date	string (date), nullable	Report Date (date)

Example request

curl "https://api.bankregreports.com/api/v1/risk/high-risk-banks/" \
  -H "Authorization: Bearer $BANKREG_API_TOKEN"

Responses are JSON in a {"data": ..., "meta": {...}} envelope. Get a token on the setup page.

Example response shape

A successful call returns HTTP 200 with a JSON body. Each row in data carries the fields below, shown with their documented types rather than sample values.

{
  "data": [
    {
      "rssd_id": "integer",
      "legal_name": "string",
      "hq_state": "string",
      "total_assets": "number (double)",
      "failure_probability": "number (double)",
      "risk_tier": "string",
      "composite_risk_score": "number (double)",
      "prob_1yr": "number (double)"
      ... 19 more fields
    }
  ],
  "meta": { ... }
}

When to use it

High-Risk Banks sits in the Risk & Failures group of the Data API. Reach for it when your work needs this data straight from the API: it comes back as JSON you can load into a notebook, a spreadsheet or a scheduled pipeline, with the dataset key high_risk_banks naming it the same way in the REST path, the Python SDK and the OpenAPI document.

Access and authentication

This dataset is in the Free tier. Send your API token in the Authorization header as a Bearer token, using a GET request to the endpoint above. The Free plan is the first plan that includes it. Check the plan comparison for request limits, and the data update schedule for when new filings reach the API.

Related datasets

• Failure Risk Score: Exploratory 1-year failure-risk screening score (not a calibrated probability) + safety verdict for one bank.
• Recent Failures: Most recent bank failures (FDIC).
• Failures by Year: Bank failure counts and total assets by year.
• Risk Tier Overview: Counts of banks by failure-risk tier (Critical/High/Elevated/Moderate/Low), from an exploratory screening score.

Keep going

Browse every dataset, follow the setup walkthrough to make a first call, use the Excel add-in for formulas, or connect an assistant through the MCP server.

Python SDK

Install with pip install bankregreports and set BANKREG_API_TOKEN to your key.

import bankregreports

brr = bankregreports.BankReg()  # reads BANKREG_API_TOKEN
result = brr.high_risk_banks()