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Retrieve Summary of Demographic Data for FDIC-Insured Institutions

Source: R/get_demographics.R
get_demographics.Rd

Queries the /demographics endpoint of the FDIC BankFind Suite API, returning demographic data for FDIC-insured financial institutions.

Usage

get_demographics(
  api_key = Sys.getenv("FDIC_API_KEY"),
  filters = NULL,
  fields = NULL,
  sort_by = NULL,
  descending = FALSE,
  limit = 10000
)

Arguments

api_key

(String) Your FDIC API key. Required: the FDIC does not accept unauthenticated requests. Defaults to the value of the FDIC_API_KEY environment variable. Register for a free personal key (1,000 req/hr) at https://api.data.gov/signup/.

filters

(String) An optional Elasticsearch query string to filter results. All field names and values must be uppercase.

fields

(String or Character vector) Fields to include in the response. An ID column is always present, regardless of the fields requested. To retrieve the most recently published API definition for an endpoint, replace the get_ prefix in the function name with fdic_ (e.g., get_{endpoint}() to fdic_{endpoint}()).

sort_by

(String) Field name to sort results by. Defaults to the API default sort order for this endpoint.

descending

(Logical) Should results be sorted in descending order? Only applies when sort_by is specified. Defaults to FALSE.

limit

(Integer) Number of records to return. Must be between 1 and 10,000. Defaults to 10,000.

Value

A tibble containing demographic data for FDIC-insured institutions, with one row per institution.

Examples

# Return demographic data for a specific institution
suppressMessages(get_demographics(filters = "CERT:10002"))
#> # A tibble: 137 × 55
#>    ACTEVT BRANCH CALLYM  CALLYMD CBSANAME  CERT CLCODE CNTRYALP CNTRYNUM CNTYNUM
#>     <int>  <int>  <int>    <int> <chr>    <int>  <int> <chr>       <int>   <int>
#>  1     NA      1 198403 19840331 WHEELIN… 10002      3 US           1007      69
#>  2    810      1 198406 19840630 WHEELIN… 10002      3 US           1007      69
#>  3    810      1 198409 19840930 WHEELIN… 10002      3 US           1007      69
#>  4    810      1 198412 19841231 WHEELIN… 10002      3 US           1007      69
#>  5    810      1 198503 19850331 WHEELIN… 10002      3 US           1007      69
#>  6    810      1 198506 19850630 WHEELIN… 10002      3 US           1007      69
#>  7    810      1 198509 19850930 WHEELIN… 10002      3 US           1007      69
#>  8    810      1 198512 19851231 WHEELIN… 10002      3 US           1007      69
#>  9    810      1 198603 19860331 WHEELIN… 10002      3 US           1007      69
#> 10    810      1 198606 19860630 WHEELIN… 10002      3 US           1007      69
#> # ℹ 127 more rows
#> # ℹ 45 more variables: CSA <lgl>, DIVISION <int>, DOCKET <int>, FDICAREA <int>,
#> #   FDICTERR <chr>, FLDOFDCA <chr>, HCTNONE <lgl>, ID <chr>, INSAGNT2 <lgl>,
#> #   METRO <int>, MICRO <int>, MNRTYCDE <lgl>, MNRTYDTE <int>, OAKAR <int>,
#> #   OFFDMULT <int>, OFFNDOM <int>, OFFOTH <int>, OFFSOD <int>, OFFSTATE <int>,
#> #   OFFTOT <int>, OFFUSOA <int>, QTRNO <int>, REPDTE <int>, REPDTE_INT <lgl>,
#> #   RISKTERR <chr>, SASSER <int>, SIMS_LAT <dbl>, SIMS_LONG <dbl>, …

# Return specific fields only
suppressMessages(get_demographics(
  fields = c("CERT", "OFFSTATE", "OFFTOT", "REPDTE"),
  limit = 5
))
#> # A tibble: 5 × 5
#>    CERT ID             OFFSTATE OFFTOT   REPDTE
#>   <int> <chr>             <int>  <int>    <int>
#> 1 10002 10002_19840331        1      2 19840331
#> 2 10002 10002_19840630        1      3 19840630
#> 3 10002 10002_19840930        1      3 19840930
#> 4 10002 10002_19841231        1      3 19841231
#> 5 10002 10002_19850331        1      3 19850331

# Sort by report date in descending order
suppressMessages(get_demographics(
  fields = c("CERT", "OFFTOT", "REPDTE"),
  sort_by = "REPDTE",
  descending = TRUE,
  limit = 5
))
#> # A tibble: 5 × 4
#>    CERT ID             OFFTOT   REPDTE
#>   <int> <chr>           <int>    <int>
#> 1 10004 10004_20250630      5 20250630
#> 2 10011 10011_20250630      6 20250630
#> 3 10012 10012_20250630      4 20250630
#> 4 10015 10015_20250630      4 20250630
#> 5 10044 10044_20250630     34 20250630