Korean Forensic Finance

Featured Ongoing
Builder · 2026 Korean Forensic Accounting Toolkit A 13-repo, 749-test forensic accounting platform that screens Korean DART filings for earnings manipulation and convertible bond dilution — from raw government data to investigative-grade output, automated end to end. Each component is independently published, MIT-licensed, and accompanied by a stand-alone write-up.
Python ≥3.11uv, hatchling, pytestDART OpenAPI (primary filings data)pykrx (KRX price and volume) +6
View case study
Ongoing
Builder · 2026 KOSDAQ CB/BW Dilution Screen 2,934 KOSDAQ CB/BW issuances scored across four calibration runs; flag rate reduced from 49.3% to 33.1% after resolving a systematic denomination mismatch between split-adjusted prices and DART exercise prices. Four cases confirmed as genuine extreme ITM at above 10x moneyness.
kr-derivatives (Black-Scholes option pricing, CBSpec schema)pykrx (KRX price and volume data)scipy.stats.norm (Black-Scholes CDF computation)DART OpenAPI (crDecsn.json, stockTotqySttus.json, cb_bw_events.parquet) +2
View case study
Ongoing
Builder · 2026 Korean Beneish M-Score (kr-beneish) Korean IFRS adaptation of the 8-variable Beneish M-Score calibrated against a 50-case labeled dataset (17 FSS/SFC fraud, 13 clean, 20 auto-controls); Korean threshold -2.45 vs. US -1.78; flags ~1,250 of 7,447 KOSDAQ company-years (2018–2023).
Python ≥3.11, uvpandas, numpyscipy.stats (bootstrap sampling, confidence intervals)scikit-learn (RandomForestClassifier, cross-validation) +2
View case study
Featured
Builder · 2026 Korean Accounting Enforcement Dataset 240 Korean accounting violations coded across FSS and SFC enforcement records, DART-linked and validated through a five-phase bias audit — the first open, reproducible Korean enforcement dataset with machine-readable violation taxonomy and Beneish ratio coverage for named companies.
Python ≥3.11, uvpdfplumber, pypdfium2 (PDF extraction)Anthropic SDK (claude-haiku-4-5, claude-sonnet-4-6, claude-opus-4-6)DART OpenAPI (financial statements for Beneish computation) +2
View case study
Builder · 2026 JFIA Article Catalog Structured JSON index of all 469 articles published in the Journal of Forensic & Investigative Accounting (2009–2025) across 46 issues — titles, authors, abstracts, keywords, and direct PDF links. The only machine-readable catalog of JFIA; upstream data source for jfia-forensic detectlet schemas and krff-shell natural-language search.
PythonrequestsBeautifulSoup4 (HTML parsing)json (stdlib) +1
View case study
Ongoing
Builder · 2026 krff-shell — Natural Language Finance Shell 11-tool MCP server exposing the Korean forensic finance toolkit as natural-language queries via Claude Desktop — DuckDB query layer, parameterized SQL (injection-safe), per-company self-contained HTML reports (Plotly), optional Claude narrative synthesis. FastAPI REST endpoints mirror all 11 MCP tools. 317 tests.
Python ≥3.11, uvMCP SDK (Anthropic)FastAPI + uvicornDuckDB +5
View case study

Korean Real Estate

Featured Ongoing
Builder · 2026 Korean District Credit Risk Index A 16-year, 228-district time-series of Korean housing credit risk built from public court registry data — tracking the five registration types that lead and lag residential foreclosure, with a statistically consistent 17-month cascade from lease-lien onset to forced auction.
Python 3.11DuckDB (fact table + analytics)SQLite (idempotency state log)IROS 등기정보광장 OpenAPI (5 service keys) +1
View case study
Ongoing
Builder · 2026 Korean Apartment Transaction Anomaly Screen A statistical screen using only public MOLIT data to flag apartment buildings where coordinated transaction cancellations suggest price manipulation. Demo: 강남구 2024 — 3,754 transactions analyzed, 33 buildings flagged. Sector findings cross-validated against public FSS and 국토부 investigation records.
Python 3.11MOLIT 실거래가 OpenAPI (국토부, data.go.kr)pandaspytest
View case study
Ongoing
Builder · 2026 Korean Housing Risk — Public Dataset The public storefront for the Korean District Credit Risk Index — sample district reports, a national 16-year trend chart, and methodology documentation, published under CC BY-NC 4.0. The first publicly available 시군구-level court registry time series covering 228 Korean districts.
Python (pipeline, report generation — in parent project district-credit-risk)PDF (district snapshot reports)PNG (national trend chart)Markdown (methodology documentation) +1
View case study
Ongoing
Builder · 2026 Korean Presale Transfer Window Scanner A data pipeline that crosses 청약홈 presale lottery records with K-APT construction permit data to surface apartments where 분양권 전매제한 (presale transfer restrictions) have expired — a transaction window that 청약홈 never surfaces directly. 6 APIs confirmed live. 10/10 join test passed.
Python 3.11청약홈 APT 분양정보 OpenAPI (15101046)K-APT 공동주택 단지목록 / 기본정보 API주택인허가 기본개요 API (15136560) +4
View case study
Ongoing
Builder · 2026 Korean Lease Risk Engine V0 CLI proof-of-concept: resolves a Korean rental address to a district-level distress band using 16 years of court registry data, positioning the district on the 17-month 임차권→강제경매 cascade timeline. Not calibrated for paying-tenant decisions — V0.5 required for property-level analysis.
Python 3.11DuckDB (read-only, from district-credit-risk)pandasJinja2 (markdown report rendering) +2
View case study
Ongoing
Researcher · 2026 Korean Public Auction Intelligence Market research and product specification for a Korean public auction scoring tool targeting KAMCO's 온비드 platform. 86,875 unsold listings in 2024 — 2× the 2023 count. Primary signal: 유찰횟수 (failed auction rounds), which depresses reserve prices in a structured, predictable pattern. All four scoring fields confirmed in the KAMCO API. One API test away from build decision.
Python 3.11KAMCO 온비드 OpenAPI (USCBD_CNT field)PublicDataReader (field name verification source)pandas
View case study
Ongoing
Builder · 2026 Korean Real Estate Tax Screen Screens Korean apartment transaction records for cancellation-cluster anomalies associated with price manipulation and tax evasion, using the MOLIT 실거래가 public API. Module A is live with 37 passing tests.
Python 3.11MOLIT 실거래가 OpenAPI (국토부 실거래가 공개시스템)pandas, requestsShared column constants: _shared/code/kr_re_data/columns/molit.py +1
View case study
Ongoing
Policy Researcher · 2026 Korean Tenant Transaction Assurance — Policy Research A policy proposal for 임차인단독의뢰형 공공거래확인제도 — a public registry verification service allowing tenants to independently order official property checks before signing a lease, without landlord cooperation. Submitted to the 한국부동산원 Housing-Rights Idea Competition (2026-05-08). The proposal directly motivated the technical development of lease-risk-engine as a working proof-of-concept.
Policy research and legal framework analysis주택임대차보호법, 변호사법 §109, 개인정보보호법HUG and 한국부동산원 mandate reviewlease-risk-engine V0 (technical proof-of-concept)
View case study
Ongoing
Researcher · 2026 Korean Appraisal Tech — Market Research Systematic market research into software opportunities in the Korean real estate appraisal sector. Four hypotheses evaluated across six research rounds using an invalidation-first method. Hypothesis A produced a working demo — now the independent fraud-screen project. Hypothesis B (solo 감정평가사 workflow tool) is research-more, pending one practitioner interview.
Research methodology (6-round adversarial deep research)Competitive analysis (7 AVM + appraisal-adjacent competitors)API assessment (실거래가, 공동주택공시가격, Landvisor)감정평가에 관한 규칙 §9 (statutory framework)
View case study

Korean Procurement Analytics

US Procurement Analytics