My Portfolio

Sunshine Resort Customers Analysis

This was a unique project, because it had a lot of customers coming in from various parts of the world like Portugal, Spain, Italy etc. We discovered through thorough analysis and visualisation. The suggestion we gave was to improve customer experience by personalising services based on their preferences. This helped the resort to reduce churning rate by 10%. This analysis was performed using Microsoft Power BI.

Bank Fraud Detection Analysis Using SQL

This project focused on identifying fraudulent banking transactions by analyzing large datasets using SQL. Data was queried to detect unusual patterns such as high-frequency transactions, abnormal transaction amounts, and activities occurring outside typical user behavior.

Advanced SQL techniques including joins, aggregations, window functions, and conditional filtering were used to segment customers and flag suspicious activities. Transactions were compared against historical behavior to highlight anomalies and potential fraud cases.

Based on the findings, recommendations were made to implement real-time monitoring rules, transaction limits, and automated alerts for high-risk activities.

Result: The analysis improved fraud detection accuracy, reduced false positives, and enabled faster identification of suspicious transactions, contributing to enhanced security and risk management.

April 22, 2017