All Work
FintechAI & Data
Deploying automated financial auditing using machine learning models
Key Outcome
18k hrs
Manual Audit Effort Saved Annually
01. The Challenge
Finance teams were spending thousands of manual hours per quarter cross-referencing transaction records for audit compliance. Error rates from manual checks were increasing as volumes scaled, creating growing regulatory risk.
02. Engineering Approach
Built high-throughput ETL data pipelines using PyTorch and pgvector databases. Enabled semantic audit cross-referencing that flags outliers with a low false-positive rate. A reviewer dashboard allows finance leads to inspect flagged transactions with full reasoning traces from the model.
18k hrsManual Effort Saved
0.3%False Positive Rate
6×Audit Speed Increase
"This AI solution essentially acts as a tireless, ultra-accurate analyst on our team. It caught discrepancies we didn't even know existed."
Marcus Vance
VP of Data & Analytics
