This case study intentionally stays at a high level. Fraud-detection thresholds, identifiers, investigative methods, confidential controls, and production business rules are not published.
The business problem
Fraud-related package activity can create USPS assessment exposure and financial risk. The business needed better visibility into emerging patterns and a governed analytical framework for identifying, investigating, and responding to those risks.
My role
I develop analytical concepts and SQL logic in Databricks, propose new classifications and reporting approaches, and design the Power BI reporting experience. I am expected to bring ideas forward rather than simply execute pre-defined rules.
Governance & approval
- Develop an analytical idea or business rule based on patterns observed in the data.
- Review the logic with my manager and refine it through discussion and testing.
- Present the recommendation to the executive sponsor for additional feedback and approval.
- Make changes based on stakeholder feedback before anything is incorporated into the production solution.
This strict review process is important because fraud and assessment logic can have direct financial and operational consequences.
Power BI & architecture
I am responsible for designing how risk indicators, trends, summary information, and package-level supporting detail are presented in Power BI. The current development flow uses Databricks SQL with exported results connected to Power BI. The future-state solution will be incorporated into the enterprise Data Lake and exposed as a governed materialized object for direct Power BI consumption.
Approximate value of approved USPS refunds already supported by the analytics.
Impact
The solution is already creating measurable financial wins while improving visibility into emerging fraud patterns, assessment exposure, and broader financial risk. At the same time, it is establishing a controlled and repeatable framework for future fraud-related analytics.
What this demonstrates
Independent analytical thinking paired with disciplined governance: developing ideas, translating patterns into testable logic, collaborating with management and an executive sponsor, designing Power BI reporting, and connecting analytics to measurable financial recovery.