audit-analytics

Repository for CQA: Audit market concentration in the EU. Reproducible Empirical Accounting Research. Ass I

NAAIL OpenLab™ — Evidence-governed AI research and education for accounting, auditing, finance and sustainability. Reproducible benchmarks, multi-agent prototypes and human-reviewed analysis.

Audit Analytics projects

Financial audit risk analytics dashboard built with Python and Excel — anomaly detection, risk segmentation, and executive visualisation

End-to-end financial transaction anomaly detection system built with Python and Power BI. Flags 3.2% of 284,807 transactions as high-risk using Isolation Forest, Z-Score, and IQR methods with 91% precision. Simulates real-world Big 4 audit analytics workflows.

Audit analytics: Benford's Law, rule-based red flags and Isolation Forest over a 1M-row transaction ledger, validated against a synthetic anomaly set

AAAS — Accrual Anomaly Audit Screening. Forensic screening for U.S. public-company filings: Beneish M-Score, Altman Z, Dechow F, Jones discretionary accruals, REM and an SEC-enforcement-trained ML ensemble. Free during early access. Proprietary, not open source.

This Python script generates a dataset of fake financial transactions, designed for audit training and testing purposes. It creates a CSV file containing a mix of normal transactions and various types of irregularities, ranging from simple anomalies to sophisticated patterns that require advanced analytical techniques to detect.

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

Procurement risk analytics platform built in R/Shiny using Polish public procurement data (Atlas Przetargów). Features Benford screening, buyer & vendor risk scoring, relationship analytics, concentration monitoring and Dockerized deployment. Developed as an end-to-end analytics product for procurement risk screening and audit support.

SQL-based fraud analysis of a 6M+ financial transaction dataset using PostgreSQL. The project follows audit-style workflows, preserves raw data integrity, applies performance indexing, and identifies systemic fraud patterns, balance inconsistencies, and high-risk transaction channels.

Financial anomaly detection and audit analytics: nine audit procedures, Benford's Law, Isolation Forest, and a 0-100 explainable risk score over a synthetic journal ledger. Streamlit dashboard + SQLite warehouse.

Practical guide and templates for applying data analysis in internal audit

Power BI dashboard analysing audit observations, risk ratings, and audit progress using real-world audit data.

Audit & accounting risk analytics: data validation, Isolation Forest anomaly detection, risk scoring, PostgreSQL and a Power BI dashboard

Profile README — Yasser Soliman. Chief Strategy Officer, Executive & Board Advisor. 25+ years across ICT, FinTech and credit risk; now building forensic accounting and credit-scoring analytics at Cappross.

Checked a year of San Francisco's vendor payments ($6.1B) for duplicate payments, duplicate vendor records, and bills paid more often than they should be. Python, SQL, Excel.

Ranking flagged journal entries for audit review: cross-test risk scoring on synthetic general ledgers, with a Caseware IDEA side joined on a row ID.

Synthetic internal audit analytics case study featuring control design, SQL/Python reconciliation, evidence classification, and executive communication.

Fraud risk triage and audit analytics with PaySim, machine learning, anomaly detection, policy grounding, LLM evaluation, and Streamlit.