fcall

R package for parsing Farm Credit Administration (“FCA”) Call Report data into tidy R data frames.

Installation

{fcall} can be installed from CRAN using install.packages("fcall"). Alternatively, you can install the development version from GitHub using {pak} like so:

# install.packages("pak")
pak::pak("ketchbrookanalytics/fcall")

Background

FCA publishes Call Report data on a quarterly basis at https://www.fca.gov/bank-oversight/call-report-data-for-download. Ketchbrook Analytics replicates these files in a public AWS S3 bucket, which {fcall} interacts with via its download_data() function.

As of September 2025, this data represents a set of 72 .TXT files. These files represent 36 datasets. The files prefixed with “D_” contain metadata (the column names, data types, etc.) of the associated file containing the raw, header-less comma-separated data. For example, the file that starts with “D_INST” contains the metadata for the file that starts with “INST_”.

Further, some of these datasets are structured in a way that makes data analysis difficult. In these cases, we chose to pivot the data to make it more analysis-friendly. See Metadata File Scenarios for a more in-depth discussion of when and how this pivoting took place.

This package provides 3 utility functions:

1. download_data() allows users to programmatically download (and unzip) data from a specific quarter
2. process_data() parses the data from these unzipped .TXT files into a list of R data frames containing the Call Report data and file metadata
3. compare_metadata() compares two sets of Call Report data from different quarters

Check out the Getting Started vignette to learn more about these three core functions.

Database

Ketchbrook Analytics has also created a PostgreSQL database to store historical FCA Call Report data in a traditional, relational schema that aligns with the output data frame structure resulting from running process_data(). This database allows users to execute SQL queries to easily analyze Call Report data across multiple quarters.

Please reach out to info@ketchbrookanalytics.com if you would like access to this database.