The package provides an auditable R workflow for canonical risk-weighted asset data. Start by inspecting the two bundled profiles.
library(riskweightedassets)
list_reference_profiles()
#> profile_id profile_version base_as_of_date default_seed
#> 1 KSA_BANK 1.0.0 2026-08-31 5752026
#> 2 MID_SIZE_UNIVERSAL 1.0.0 2026-08-31 5752026
#> description
#> 1 Institutsneutrales KSA-Profil ohne IRB, Handelsbuch, CCR/CVA, Verbriefungen oder Großkreditüberschreitungen.
#> 2 Vollständige synthetische mittelständische Universalbank mit KSA, IRB, CCR, CVA, Verbriefung, Markt, OpRisk, IRRBB und ICAAP.
#> default_dataset_version
#> 1 v1.0.0-ksa
#> 2 v1.0.0Generate native R tables without writing files.
tables <- generate_synthetic_tables(bank_profile = "KSA_BANK")
length(tables)
#> [1] 68
names(tables)[1:12]
#> [1] "run_config" "rule_set" "official_designation"
#> [4] "legal_entity" "consolidation_scope" "scope_membership"
#> [7] "approach_permission" "party" "connected_client_group"
#> [10] "group_membership" "external_assessment" "rating_assignment"A full calculation is intentionally not executed while building this vignette because it calculates applied and fully-loaded views. Run it interactively:
result <- calculate_tables(tables)
print(result)
unlist(result$metrics[c("RWEA_KSA", "TREA", "CET1_RATIO")])For a spreadsheet workflow, write only below a controlled caller-owned path:
dataset <- generate_synthetic_dataset(
file.path(tempdir(), "rwa-runs"), bank_profile = "KSA_BANK"
)
validate_dataset(dataset)
result <- calculate_dataset(dataset)The data is synthetic, and the package is not regulatory or legal advice.