riskweightedassets

Version 1.2.3: UTC snapshot timestamp correction.

Retained from 1.2.2: Canonical default flags and regression cases.

Version 1.2.1: IRB default correction and API migration.

riskweightedassets is the R implementation of the RiskDataScience GmbH reference engine for CRR III risk-weighted assets, regulatory capital, IRRBB and ICAAP. It provides a stable R API, canonical Excel contracts, realistic synthetic portfolios, bitemporal snapshots, deterministic lineage and reconciliation controls. No Python runtime is required.

The package is intended for research, education, prototyping and independent model validation. It is not legal, supervisory, accounting or investment advice and is not a certified regulatory reporting system.

Functional scope

credit risk under the Standardised and IRB Approaches, CRM and output floor;
counterparty credit risk, SFT, CCP, securitisation, CVA and crypto exposures;
settlement, large exposures, legacy market risk, parallel FRTB and operational risk;
own funds, buffers, leverage, MREL/TLAC and capital headroom;
IRRBB/CSRBB and ICAAP economic and normative perspectives;
68 canonical input tables in 16 workbooks and 34 structured result tables;
applied and fully-loaded views from the same official snapshot;
two complete synthetic bank profiles and Python 1.0.0 golden-master parity.

Installation

During development, build and install the local source package:

install.packages("riskweightedassets_1.2.0.tar.gz", repos = NULL, type = "source")

After CRAN acceptance the standard command will be:

install.packages("riskweightedassets")

First in-memory calculation

library(riskweightedassets)

tables <- generate_synthetic_tables(bank_profile = "MID_SIZE_UNIVERSAL")
result <- calculate_tables(tables)
print(result)
result$metrics[c("RWEA_KSA", "RWEA_IRB", "TREA", "CET1_RATIO")]

Granular analyst API

The package exposes 77 documented public functions. Analysts can calculate an individual formula, inspect or override a regulatory weight, extract one result table, compare applied and fully-loaded metrics, or obtain a focused risk-domain analysis without using private package internals.

sa_exposure_value(100, 2, committed_undrawn = 40, annex_i_class = "CLASS_2")
irb_capital_requirement(.01, .45, .20, 2.5)

tables <- generate_synthetic_tables(bank_profile = "KSA_BANK")
override <- data.frame(
  parameter_key = "RWA_MULTIPLIER", dimension_1 = "PILLAR1",
  dimension_2 = "", parameter_value = 13
)
scenario_tables <- override_regulatory_parameters(
  tables, override, reason = "Sensitivity analysis", approved_by = "Model Risk"
)
parameter_overrides(scenario_tables)

See the bank-analyst API map for the complete functional inventory and governance rules.

Excel workflow

All writes go to a destination selected by the caller. Package resources are immutable.

root <- file.path(tempdir(), "rwa-runs")
dataset <- generate_synthetic_dataset(
  root,
  as_of = as.Date("2026-08-31"),
  version = "v1.0.0",
  bank_profile = "KSA_BANK"
)
validation <- validate_dataset(dataset)
result <- calculate_dataset(dataset)
result$output_files

calculate_dataset() writes six output workbooks and a machine-readable run manifest below outputs/<deterministic-run-id>/. For integration without spreadsheets, calculate_tables() accepts and returns ordinary R objects.

Synthetic data and external-source boundary

The package contains synthetic data only. It contains neither customer data nor downloaded regulations, standards, PDFs or other third-party publications. regulatory_sources() returns official URLs and archival SHA-256 values; the documents remain outside the distribution.

Documentation

Within R, start with help(package = "riskweightedassets") and the vignettes:

browseVignettes("riskweightedassets")

License and legal information

Credit supporting factors (1.2.0)

Four new public functions cover SME, infrastructure, combined support and complete IRB RWEA. See supporting-factor documentation for inputs, eligibility, compatibility and audit output.