forensic-accounting

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on J…

A public benchmark for evaluating the data processing, reconciliation, and forensic reasoning capabilities of AI agents in a financial context.

Detecting corporate accounting anomalies using Benford’s Law.

Public lite version of a personal multi-disciplinary ontology spanning forensic accounting, integrated data science, and valuation. Licensed under CC BY-NC-SA 4.0

Python pipeline for Benford's Law analysis on SEC EDGAR 10-K filings. Chi-Square & MAD-based anomaly detection, suspicion scoring, heatmap visualizations, and ReportLab PDF audit reports for 30 US companies across 5 sectors.

An unsupervised deep learning model (Autoencoder) for detecting accounting fraud and General Ledger anomalies using categorical embeddings.

AI-powered financial audit desktop app for retail (Windows). Independent math verification with traffic-light indicator, Analyst & Forensic modes, DeepSeek V4 Pro, Word export. Commercial product.

The ultimate Python package for Benford's Law analysis in forensic accounting and fraud detection

Institutional-grade LLM evaluation, red-teaming & telemetry framework for financial AI. Tracks 56 AI ecosystem tickers with an 18-kernel audit architecture; 10 production auditors live.

Claude Agent Skill for rigorous, sector-relative fundamental analysis of listed companies - India-first (NSE/BSE, Ind-AS), works globally. Document-first, never-invent-a-number. Research, not investment advice.

Integrated company analysis of Mahindra & Mahindra Ltd. covering financial statement analysis, revenue quality assessment, forensic accounting analysis, and corporate governance.

End-to-End Python scalable forensic accounting toolkit implementing Benford's Law analysis for FTSE financial data. Delivers automated anomaly detection with Chi-Squared/MAD testing, comprehensive validation pipelines, and risk-based prioritization of investigative resources. Replicates Ausloos et al.'s (2025) methodology with full reproducibility.

Python → SQL Server → dbt → Power BI pipeline that normalizes multi-bank statements and flags suspicious transactions

Financial and Forensic Using python and jypyter noteboook

An Excel-based forensic analytics tool that leverages Benford’s Law to identify digit patterns in transaction data. Includes first-digit, second-digit, first-two-digit, last-two-digit, and duplication tests with automated tables and visualizations for audit and fraud-risk screening.

Institutional-grade Power BI Portfolio | 12 dashboards | 179 visuals | 98 DAX measures | Financial Analytics | Credit Risk | FP&A | Treasury | ESG | SQL Star Schema

Forensic financial analytics on the Deloitte Bags Medical Devices commission fraud case. Pattern detection and data-driven fraud investigation in R. VCU FIRE 540.

Interactive WOE (Weight of Evidence) and IV (Information Value) binning web tool for credit risk scoring, segmentation, and transparent scorecard development.

AI-assisted forensic AP review for healthcare finance. Detects ghost vendors, FX/IAS 21 misallocations, split-PO patterns, and duplicate invoices, then generates AU-C 240/IAS 21 audit memos via Claude. Built with Streamlit + Python.