Audit Analytics
Audit analytics for monitoring, testing, issue follow-up, and risk-based review.
Interactive dashboards and audit testing applications designed to improve coverage, identify exceptions, support targeted testing, and make audit results easier to review.
Demo note: This project is for demonstration and discussion purposes only. It uses generalized, synthetic, or public data. No proprietary company data, confidential audit documentation, internal systems, or client information are included.
Analytics overview
Designed around practical audit monitoring and testing needs.
Monitor risk
Use dashboards to identify overdue issues, high-risk transactions, unusual patterns, and follow-up priorities.
Target testing
Support risk-based testing through exception analysis, sampling, anomaly screening, and population review.
Communicate results
Translate audit data into clear visuals that improve management reporting, review, and decision-making.
Interactive dashboard
Internal Audit Issue Tracker
Interactive Power BI dashboard for tracking audit findings, management action plans, issue aging, ownership, and follow-up status.
Tracking open issues and management action plans across audits can become fragmented, manual, and difficult to summarize.
Centralized issue tracking with status, aging, ownership, follow-up views, and management reporting visuals.
Improves follow-up discipline, management reporting, and visibility into overdue or high-priority issues.
Embedded interactive Power BI report using demo data.
Audit monitoring dashboard
Vendor Payments Monitoring
Risk-focused Power BI dashboard for analyzing payment patterns, vendor behavior, duplicate indicators, split payments, and unusual transaction activity.
High-volume vendor payments make it difficult to identify duplicate, split, unusual, or higher-risk transactions through manual review alone.
Built a risk-focused dashboard highlighting payment patterns, vendor behavior, and anomalies for targeted audit testing.
Enables focused audit testing and continuous monitoring of transactions that may warrant additional review.
Embedded interactive Power BI report using demo data.
Audit testing applications
Streamlit apps for sampling, anomaly screening, and compliance analytics.
These applications demonstrate how Python and Streamlit can support repeatable audit procedures, sample selection, anomaly analysis, and risk-based review.
Audit Sampling Tool
Interactive sampling app with filtering, random selection, and exportable results for reproducible audit testing.
Benford’s Law Audit Tool
Benford’s Law analysis with visual diagnostics and anomaly flagging to support rapid triage of high-risk datasets.
Fair Lending Analysis
Simulator using synthetic data, interactive controls, and statistical analysis to demonstrate fair lending review concepts.
Audit Sampling Tool interface for filtering populations and generating sample selections.
Benford’s Law tool showing visual diagnostics and anomaly screening results.
Fair lending simulator using synthetic data and statistical testing concepts.
Important limitation: Benford’s Law and similar analytics are screening techniques, not proof of fraud or noncompliance. Results should be used to identify transactions or populations that may warrant additional audit procedures.
Additional BI examples
Business intelligence examples with audit-style analytical value.
These examples are not formal audit datasets, but they demonstrate the same techniques used in audit analytics: data modeling, trend review, outlier identification, segmentation, and management reporting.
Adventure Works – Sales & Operations Dashboard
End-to-end dashboard development using a multi-table operational dataset with revenue trends, product performance, and operational drivers.
Embedded interactive Power BI report using demo data.
Property Management Dashboard
Portfolio-level dashboard for reviewing property performance, filtering locations, and identifying outliers or underperforming assets.
Embedded interactive Power BI report using demo data.
Audit analytics
Analytics that support better audit coverage, clearer testing, and more focused follow-up.
Explore the audit tools page, view data projects, or connect with me on LinkedIn.