Download FCA Call Report Data and Unzip
Arguments
- year
(Integer) The year of the Call Report (e.g.,
2022)- month
(String) The month of the Call Report (e.g.,
"March"); you may also supply an integer (e.g.,3) representing the month numerically- dest
(String) The path to the directory where the data will be downloaded (and unzipped) into
- files
(Optional) Character vector, representing the names of the files in the .zip archive to be downloaded; default is
NULL, meaning all files will be downloaded- quiet
(Optional) Logical. Controls whether download progress messages are displayed in the console. Defaults to
TRUE.
Value
TRUE (invisibly) if the data was successfully downloaded and
unzipped, along with a console message informing the user where the
data was downloaded (and unzipped) into. If the data cannot be
downloaded (e.g., there is no internet connection, the resource is
unavailable, or there is no data for the requested year and month)
or unzipped, download_data() returns FALSE (invisibly) with an
informative console message, instead of throwing an error.
Details
FCA publishes Call Report data quarterly. These .zip files are
typically named "YYYYMarch.zip", "YYYYJune.zip", "YYYYSeptember.zip"
and "YYYYDecember.zip" (where YYYY represents the 4-digit year).
Therefore, valid values to the month argument should be limited to
c(3, 6, 9, 12), unless there is an anomaly in FCA's reporting/publishing.
Check https://www.fca.gov/bank-oversight/call-report-data-for-download to
ensure the data is available for the quarter you are interested in.
Ketchbrook Analytics downloads these files and stores them in a public AWS
S3 bucket, which is the location that download_data() retrieves them
from.
The files in the S3 bucket are identical to those published by FCA, with
one exception: the RCR7 data files in the March, June, September and
December 2024 .zip files have been corrected to add rows that are missing
from FCA's versions. Without these rows, process_data() fails on the
2024 data. See https://github.com/ketchbrookanalytics/fcall/issues/23
for details. If you need FCA's original 2024 files, download them directly
from the FCA website.
Examples
# \donttest{
path_1 <- tempfile("fcadata1")
dir.create(path_1)
download_data(
year = 2025,
month = "September", # using the name of the month
dest = path_1
)
#> Files successfully downloaded into /tmp/Rtmpz5Pxvy/fcadata13b2f737e50a
list.files(path_1)
#> [1] "D_INST.TXT" "D_RC.TXT"
#> [3] "D_RC1.TXT" "D_RCB.TXT"
#> [5] "D_RCB2.TXT" "D_RCB3.TXT"
#> [7] "D_RCB4.TXT" "D_RCB5.TXT"
#> [9] "D_RCF.TXT" "D_RCF1.TXT"
#> [11] "D_RCG.TXT" "D_RCH.TXT"
#> [13] "D_RCI1_2018.TXT" "D_RCI2A_2018.TXT"
#> [15] "D_RCI2B_2018.TXT" "D_RCI2C_2018.TXT"
#> [17] "D_RCI2D_2018.TXT" "D_RCK.TXT"
#> [19] "D_RCL.TXT" "D_RCM.TXT"
#> [21] "D_RCO.TXT" "D_RCR1.TXT"
#> [23] "D_RCR2.TXT" "D_RCR3.TXT"
#> [25] "D_RCR4.TXT" "D_RCR5.TXT"
#> [27] "D_RCR6.TXT" "D_RCR7.TXT"
#> [29] "D_RI.TXT" "D_RIA.TXT"
#> [31] "D_RIB.TXT" "D_RIC.TXT"
#> [33] "D_RIC1.TXT" "D_RID.TXT"
#> [35] "D_RIE1.TXT" "D_RIE2.TXT"
#> [37] "INST_Q202509_G20251112.TXT" "RC1_Q202509_G20251112.TXT"
#> [39] "RCB2_Q202509_G20251112.TXT" "RCB3_Q202509_G20251112.TXT"
#> [41] "RCB4_Q202509_G20251112.TXT" "RCB5_Q202509_G20251112.TXT"
#> [43] "RCB_Q202509_G20251112.TXT" "RCF1_Q202509_G20251112.TXT"
#> [45] "RCF_Q202509_G20251112.TXT" "RCG_Q202509_G20251112.TXT"
#> [47] "RCH_Q202509_G20251112.TXT" "RCI1_Q202509_G20251112.TXT"
#> [49] "RCI2A_Q202509_G20251112.TXT" "RCI2B_Q202509_G20251112.TXT"
#> [51] "RCI2C_Q202509_G20251112.TXT" "RCI2D_Q202509_G20251112.TXT"
#> [53] "RCK_Q202509_G20251112.TXT" "RCL_Q202509_G20251112.TXT"
#> [55] "RCM_Q202509_G20251112.TXT" "RCO_Q202509_G20251112.TXT"
#> [57] "RCR1_Q202509_G20251112.TXT" "RCR2_Q202509_G20251112.TXT"
#> [59] "RCR3_Q202509_G20251112.TXT" "RCR4_Q202509_G20251112.TXT"
#> [61] "RCR5_Q202509_G20251112.TXT" "RCR6_Q202509_G20251112.TXT"
#> [63] "RCR7_Q202509_G20251112.TXT" "RC_Q202509_G20251112.TXT"
#> [65] "RIA_Q202509_G20251112.TXT" "RIB_Q202509_G20251112.TXT"
#> [67] "RIC1_Q202509_G20251112.TXT" "RIC_Q202509_G20251112.TXT"
#> [69] "RID_Q202509_G20251112.TXT" "RIE1_Q202509_G20251112.TXT"
#> [71] "RIE2_Q202509_G20251112.TXT" "RI_Q202509_G20251112.TXT"
path_2 <- tempfile("fcadata2")
dir.create(path_2)
download_data(
year = 2025,
month = 9, # using the month number (to refer to September)
dest = path_2,
# only download the following files
files = c(
"D_INST.TXT",
"INST_Q202509_G20251112.TXT"
)
)
#> Files successfully downloaded into /tmp/Rtmpz5Pxvy/fcadata23b2f30f88cbf
list.files(path_2)
#> [1] "D_INST.TXT" "INST_Q202509_G20251112.TXT"
# }