Manuals
Documentation and walkthroughs for each component of the toolkit — how it works, what data it uses, and what decisions shaped its design.
Showing 1–5 of 9 articles
The Beneish M-Score, Reimplemented for Korean IFRS The Beneish M-Score is a 27-year-old fraud-screening formula calibrated on 1990s US GAAP filers. Apply it to Korean IFRS data and ~19% of KOSDAQ companies break the math. This library handles the structural differences. Read article Pricing Convertible-Bond Dilution Without SEIBRO: Black-Scholes on the DART Filing Korean convertible bonds and bonds with warrants are a known dilution vector on KOSDAQ. The natural data source for analyzing them — SEIBRO — is gated behind a separate API key that has been broken since early 2026. This library reframes the question as an option-pricing problem and answers it from DART data alone. With caveats. Read article Splitting a Forensic-Finance Monolith into Four Repos: Why and How What started as one repo grew into a coupled mess of ETL, scoring, and statistical validation. The split into four targeted libraries — kr-forensic-core, kr-dart-pipeline, kr-anomaly-scoring, kr-stat-tests — was about being honest with the dependency graph. Read article Sixteen Years of Forensic Accounting Research, in One JSON File The Journal of Forensic & Investigative Accounting has published 469 articles since 2009. None of them are indexed in a way a researcher can search programmatically. Until now. Read article Detectlets: Compiling Forensic Accounting Research Into Computable Detection Modules A 'detectlet' is what an academic paper turns into when you extract its detection rule and make it runnable. This library defines the schema, ships four reference implementations grounded in JFIA literature, and makes the question 'which papers does this rule come from?' answerable in one query. Read article