Machine learning for finance controls
Finance use cases spanning intelligent matching, anomaly detection, predictive analytics and duplicate prevention.
Similarity logic across 2M+ purchase orders
The problem
High-volume finance processes need better prioritization and pattern detection without weakening human review, controls or explainability.
My contribution
I contributed to the design and assessment of the use cases, aligned business and technical teams, and communicated value and risk reduction.
Approach
Start with the decision and control need, validate trusted inputs, test the analytical logic, keep exceptions visible, and define how people will adopt and measure the workflow.
What changed
Machine-learning similarity logic assessing more than 2 million purchase orders, alongside matching, anomaly, predictive and duplicate-prevention use cases.
Tools and platforms