Financial Transaction Analysis (SQL)

 1. Situation (Project Overview):

"I worked on a Financial Transaction Analysis project where the goal was to detect spending trends, identify anomalies, and support monthly financial reporting for a fintech client."

2. Task (Your Responsibility):

"My role was to extract insights from large volumes of transactional data using SQL, and prepare clean datasets for reporting and fraud detection analysis."

3. Action (How You Did It):

"I worked with tables like Transactions, Accounts, Customers, and Branches. My main SQL tasks included:

• Performed JOINS across these tables to build a comprehensive view of customer activity.

• Used WHERE and CASE statements to flag unusual transactions (e.g., large withdrawals, off-hour activity).

• Created calculated fields such as daily average spending, transaction frequency, and balance changes.

• Used Window Functions (like ROW_NUMBER and LAG) to identify duplicate or back-to-back transactions and spot trends over time.

• Built CTEs to modularize complex logic, such as comparing current vs. previous month’s average transaction size.

• Developed views and summary tables for monthly dashboards used by finance and compliance teams."

4. Result (Outcome/Impact):

"The project helped reduce the manual workload for financial reporting by 40% and flagged 200+ potential fraud cases within the first quarter. My SQL scripts were integrated into a recurring ETL process for monthly reporting."