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Bank Peer Ranks

Public

Pre-computed percentile ranks within the bank's asset-size cohort (all metrics).

About this dataset

Bank Peer Ranks is a Public dataset in the Banks group of the BankRegReports Data API. The response carries 9 documented fields, sourced from BankRegReports (derived).

Pre-computed rank/peer_n/percentile for one bank, optionally filtered to a single metric or quarter. Each row covers one (metric × scope × report_date) tuple, `scope` distinguishes 'overall' (entire universe) from 'asset_tier' (size band) etc. Responses are cached for up to 12 hours and refresh when new filings load.

Endpoint

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

Parameters

Name Required Description
rssd_id required Federal Reserve RSSD id. e.g. 852218
metric optional Metric id (see the `metrics` tool for valid ids). e.g. roa
report_date optional Quarter-end date, YYYY-MM-DD. Default: latest. e.g. 2026-06-30

Response fields

Field Type Description
brr_id string, nullable
report_date string (date), nullable Report Date (date)
metric string, nullable
scope string, nullable
scope_value string, nullable
value string (decimal), nullable
rank integer, nullable
peer_n integer, nullable
percentile string (decimal), nullable

Example request

curl "https://api.bankregreports.com/api/v1/banks/852218/ranks/" \
  -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": [
    {
      "brr_id": "string",
      "report_date": "string (date)",
      "metric": "string",
      "scope": "string",
      "scope_value": "string",
      "value": "string (decimal)",
      "rank": "integer",
      "peer_n": "integer"
      ... 1 more fields
    }
  ],
  "meta": { ... }
}

When to use it

Bank Peer Ranks sits in the Banks 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 bank_ranks naming it the same way in the REST path, the Python SDK and the OpenAPI document.

Access and authentication

This dataset is in the Public 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

  • Bank Directory: Directory of all FDIC-insured banks with identity + headline figures.
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  • Bank Trends: Quarterly time series of key metrics for one bank.
  • HMDA Mortgage-Lending Book: Per-bank Home Mortgage Disclosure Act book - applications, originations, denials, and USD volumes by activity year and state.

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.ranks(rssd_id=rssd_id)
Powered by BankRegReports API