About this dataset
M&A Target Screener is a Public dataset in the Screeners group of the BankRegReports Data API. The response carries 16 documented fields, sourced from BankRegReports (derived).
Find acquisition candidates ranked by the M&A score: 30% capital (CET1, capped at 30%), 30% asset quality (noncurrent loans, 0% to 10%), 25% core deposits and 15% profitability (ROA, -2% to 3%). The universe is commercial banks and savings institutions inside stated operating ranges; max_assets defaults to $10B.
Endpoint
GET /api/v1/screener/ma/ Parameters
| Name | Required | Description |
|---|---|---|
| state | optional | Two-letter state filter. e.g. GA |
| limit | optional | integer |
| max_assets | optional | number (double) USD thousands; default 10_000_000 (=$10B) |
| max_npl | optional | number (double) |
| min_assets | optional | number (double) USD thousands |
| min_cet1 | optional | number (double) |
| min_core_dep | optional | number (double) |
| min_roa | optional | number (double) |
Response fields
| Field | Type | Description |
|---|---|---|
| rssd_id | integer | RSSD ID (count) |
| legal_name | string | Legal Name (text) |
| hq_state | string, nullable | Headquarters State (text) |
| asset_tier | string, nullable | Asset Tier (text) |
| total_assets | number (double), nullable | Total Assets (USD thousands) |
| cet1_ratio | number (double), nullable | CET1 Capital Ratio (percent). Common Equity Tier 1 capital as a percentage of risk-weighted assets, the strictest measure of bank capital. The prompt corrective action "well capitalized" level is 6.5%; the 4.5% minimum plus the 2.5% conservation buffer is 7.0%, below which dividends and bonuses are limited. FFIEC 031 filers report it as RCFAP793 and FFIEC 041/051 filers as RCOAP793 (standardized approach). A bank under the advanced approaches also reports RCFWP793; the ratio shown is the lower of the two, the binding ratio FDIC publishes. Banks in the community bank leverage ratio framework do not report it. |
| npl_ratio | number (double), nullable | Non-Performing Loan Ratio (percent). Noncurrent loans (nonaccrual plus 90+ days past due and still accruing) as a percentage of total loans, the FDIC and UBPR definition; consolidated lines for FFIEC 031 filers. Performing modifications to borrowers in financial difficulty are not counted. Lower is better. The Healthy and Watch bands below are BankRegReports screening bands (2% and 5%), not regulatory triggers; no supervisory NPL threshold exists. |
| core_deposit_ratio | number (double), nullable | Core Deposit Ratio (percent) |
| roa | number (double), nullable | Return on Assets (percent). Net income, annualized, as a percentage of average total assets. The single most-cited profitability metric. 1.0%+ is strong for national banks; community banks often run 0.8 to 1.2%. |
| nim | number (double), nullable | |
| efficiency_ratio | number (double), nullable | Efficiency Ratio (percent). Non-interest expense divided by the sum of net interest income and non-interest income. Lower is better. Below 60% is excellent; above 75% raises operational-leverage concerns. |
| ma_score | number (double), nullable | |
| report_date | string, nullable | Report Date (date) |
| is_well_capitalized | boolean, nullable | |
| charter_type | string, nullable | |
| flags | array of string |
Example request
curl "https://api.bankregreports.com/api/v1/screener/ma/" \ -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",
"asset_tier": "string",
"total_assets": "number (double)",
"cet1_ratio": "number (double)",
"npl_ratio": "number (double)",
"core_deposit_ratio": "number (double)"
... 8 more fields
}
],
"meta": { ... }
} When to use it
M&A Target Screener sits in the Screeners 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 ma_screener 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 Screener: Every FDIC-insured bank with key ratios; filter, sort, paginate.
- Screener Dataset (full working set): The entire bank universe with screener columns in one response, for the paid client-side (in-browser) screener. Paid tier only; free callers page through the screener endpoint instead.
- Loan-Concentration Screener: Screen banks by loan-portfolio concentration.
- Custom Peer Groups: List or save the caller's custom peer groups.
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.ma_screener()