Risk Tier Overview

About this dataset

Risk Tier Overview is a Free dataset in the Risk & Failures group of the BankRegReports Data API. The response carries 4 documented fields, sourced from BRR ML model.

Counts of banks by failure-risk tier (Critical / High / Elevated / Moderate / Low). Tiers come from an exploratory screening score that ranks relative risk; it is not a calibrated probability, a credit rating, or a CAMELS rating.

Endpoint

GET /api/v1/risk/overview/

Response fields

Field	Type	Description
tier	string
count	integer
pct_of_universe	number (double), nullable
prediction_date	string (date), nullable

Example request

curl "https://api.bankregreports.com/api/v1/risk/overview/" \
  -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": [
    {
      "tier": "string",
      "count": "integer",
      "pct_of_universe": "number (double)",
      "prediction_date": "string (date)"
    }
  ],
  "meta": { ... }
}

When to use it

Risk Tier Overview 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 risk_overview 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

• High-Risk Banks: Banks ranked by the exploratory failure-risk screening score (uncalibrated, not a probability of failure).
• 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.

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.dataset("risk_overview")