Failure Risk Score

About this dataset

Failure Risk Score is a Free dataset in the Risk & Failures group of the BankRegReports Data API. The response carries 6 documented fields, sourced from ML model.

Exploratory screening score for one bank. `failure_probability` is an uncalibrated model output that ranks relative failure risk; it is not a calibrated probability, a credit rating, or a CAMELS rating.

Endpoint

GET /api/v1/banks/{rssd_id}/prediction/

Parameters

Name	Required	Description
rssd_id	required	Federal Reserve RSSD id. e.g. 852218

Response fields

Field	Type	Description
rssd_id	integer	RSSD ID (count)
legal_name	string	Legal Name (text)
failure_probability	number (double), nullable
risk_tier	string, nullable
composite_risk_score	number (double), nullable
model_version	string, nullable

Example request

curl "https://api.bankregreports.com/api/v1/banks/852218/prediction/" \
  -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",
      "failure_probability": "number (double)",
      "risk_tier": "string",
      "composite_risk_score": "number (double)",
      "model_version": "string"
    }
  ],
  "meta": { ... }
}

When to use it

Failure Risk Score 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 prediction 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).
• 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
rssd_id = 852218  # JPMorgan Chase Bank, N.A.
result = brr.prediction(rssd_id=rssd_id)