Audit Analytics · Data-Driven Assurance · Regulated Sectors
I help organisations find what their data is hiding — building the analytical infrastructure that makes financial and operational risk visible.
What I work on
Using SQL and data pipelines to test entire datasets rather than samples — surfacing control failures, anomalies, and financial risk that manual audit testing would never find. Every record, not thirty.
Building Power BI frameworks that give audit teams and leadership real-time visibility of where risk is concentrating — turning audit findings into decision-ready intelligence rather than static reports.
Automating the data extraction, validation, and testing workflows that slow audit functions down — reducing time from data to finding and improving consistency of evidence across every engagement.
Impact highlights
Inherited an $11.1M income variance. Executed population-level data reconciliation across 130,000+ records — identifying patterns of systematic control failure that sample-based testing would not have detected. Designed a data-driven remediation framework that recovered $3.1M within 8 months.
Read the full case study →Monthly automated KPI analysis across the full compliance dataset identified a control gap that periodic manual review had missed for years. Audited the programme at 30% compliance, diagnosed the root cause through structured data analysis, and built the SLA framework that drove compliance above 75%.
Read the full case study →The procurement function had no automated monitoring of financial commitments against contractor capacity — a control gap creating $1.3M annual budget exposure. Built a data pipeline and Power BI dashboard that eliminated the control weakness through automated monitoring rather than manual review.
Read the full case study →Led the evidence and controls strategy ahead of a statutory regulatory inspection. Validated compliance across all business areas using structured audit methodology, coordinated corrective actions across departments, and achieved a 4-star regulatory rating — avoiding regulatory cost sanctions.
Read the full case study →Colleagues say
My approach
Before building any model I map the business process, the controls that should be operating, and the risks they're designed to mitigate. Understanding the full system means I'm testing the right things — not just running queries against the obvious.
I use SQL and data pipelines to test entire datasets. Every transaction, every record, every exception. Anomalies that live outside a 30-item sample — the ones that represent the real risk — become visible when you look at everything.
Once anomalies are identified I build the quantitative case — what is the financial exposure, what is the probability of recurrence, what does the control weakness actually cost the organisation? Findings without numbers are observations. Findings with numbers are evidence.
An audit report that sits on a shelf has failed. I build the Power BI visualisations, the executive summaries, and the recommendation frameworks that make findings impossible to ignore — turning audit work into organisational action.
On the side
"I write about building a career without a map — leaving Nigeria at 24, navigating immigration, and figuring out how to grow in systems not designed with you in mind."
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Audit analytics professional open to financial services, healthcare, utilities, and regulated sector environments across the United States.