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...
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.
A public benchmark for evaluating the data processing, reconciliation, and forensic reasoning capabilities of AI agents in a financial context.
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.
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
Free, open-source, no API key CLI that surfaces forensic risk signals from a US micro-cap's SEC filings: distress & accounting quality scores, dilution, insider activity, 8-K events, delisting & trading-suspension risk, each traced to the filing. Evidence for your own due diligence, not advice.
An unsupervised deep learning model (Autoencoder) for detecting accounting fraud and General Ledger anomalies using categorical embeddings.
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.
Free Financial Intelligence & Market Analysis Starter Pack for CORTEX — forensic accounting, market surveillance, insider trading detection, AML/KYC compliance
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.
Free Fraud Detection & Financial Intelligence Starter Pack for CORTEX — transaction analysis, money laundering detection, insurance fraud patterns
Institutional-grade Power BI Portfolio | 12 dashboards | 179 visuals | 98 DAX measures | Financial Analytics | Credit Risk | FP&A | Treasury | ESG | SQL Star Schema
Institutional-grade Power BI Portfolio | 12 dashboards | 179 visuals | 98 DAX measures | Financial Analytics | Credit Risk | FP&A | Treasury | ESG | SQL Star Schema
AI forensic-research platform for Indian smallcap equities — deterministic forensic signals, a retrieval-backed LangGraph agent mesh, and a feed-first analysis UX. Research only, not investment advice.
The ultimate Python package for Benford's Law analysis in forensic accounting and fraud detection
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.
Interactive WOE (Weight of Evidence) and IV (Information Value) binning web tool for credit risk scoring, segmentation, and transparent scorecard development.
Forensic financial analytics on the Deloitte Bags Medical Devices commission fraud case. Pattern detection and data-driven fraud investigation in R. VCU FIRE 540.
Financial and Forensic Using python and jypyter noteboook
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