SQL queries for fraud detection

SQL-based risk analytics portfolio: fraud patterns, credit scoring signals, and transaction anomaly detection across fintech datasets

Bank Fraud Analysis SQL Project Portfolio

A portfolio of SQL queries for fraud analysis and data projects

A portfolio project with SQL queries for credit card fraud and analytics.

Portfolio of fraud detection and risk analytics projects using Python, SQL, and Streamlit.

"Projet d'analyse de fraudes bancaires avec SQL (BigQuery) et Power BI pour portfolio."

Financial database analytics: customer segmentation, fraud detection, loan portfolio, and executive dashboards using advanced SQL

Fraud investigation portfolio: 6 case studies, SQL detection queries, and OSINT playbooks demonstrating fraud prevention through pattern analysis and behavioral anomaly detection.

End-to-end AML/Fraud alerting portfolio using BigQuery (SQL), synthetic transaction data, and Tableau dashboards.

SQL portfolio focused on Anti-Money Laundering (AML), Fraud Detection, and Risk Analytics in the iGaming sector.

End-to-end Python + SQL + Power BI case study analyzing credit card portfolio: spend behavior, fraud risk, rewards, profitability

🏦 SQL Banking Fraud Detection Project A complete end-to-end SQL project using PostgreSQL on a synthetic banking transactions dataset (500 records). This project showcases fraud detection, customer analytics, merchant insights, window functions, and advanced SQL techniques for portfolio and resume use.

NeoBank Risk & Revenue Lab — Portfolio project (PostgreSQL + SQL + Python) that simulates data from a neobank to practice SQL at a foundational→intermediate level with interview-style cases (cohorts, funnel, unit economics, fraud) and train ML models (fraud/churn/default) using a feature store generated in SQL. Reproducible with Docker.

End-to-end analytics portfolio featuring SQL Server data models, Power BI dashboards, and business insights for workforce, financial fraud, and retail operations.

SQL-based credit decision and portfolio risk monitoring framework demonstrating underwriting rule logic, risk segmentation, delinquency roll analysis, fraud detection, and audit-ready transformations.

End-to-end data science portfolio featuring churn prediction, credit risk modeling, demand forecasting, fraud detection, and recommendation systems built with Python, SQL, and scikit-learn.

A comprehensive SQL portfolio analyzing insurance claims risk, customer lifetime value (LTV), and fraud detection. Features advanced PostgreSQL techniques including Window Functions, CTEs, and Data Validation.

Power Platform portfolio showcasing 3 banking automation projects. Loan processing (72h→15min), CRM cases (60d→3h), fraud detection (48h→2.3s). Includes workflows, conditional logic, SQL/JSON samples, and business impact metrics.

A curated portfolio of end-to-end data analytics projects showcasing my work across geospatial mapping, real-time fraud detection, migration dashboards, and public transport accessibility. Built using tools like Python, R, PySpark, Kafka, SQL, and Shiny

AML Data Engineering Path — Portfolio focused on AML/PLD, financial crime analysis, SQL pipelines, Python automation, risk scoring, fraud detection, and crypto/on-chain analytics. Built to demonstrate my skills for roles in banking, fintech, and compliance.

# FinTech Portfolio This repository contains my learning journey and projects in FinTech, Data, and Product. ## Current Focus - Python for Data - SQL fundamentals - Payments & Digital Banking basics ## Upcoming Projects - Credit Scoring Model (Python) - Fraud Detection Analysis - Digital Wallet Case Study

🛡️ End-to-end Financial Analytics & Risk Portfolio. 💳 Features a Medallion-structured Behavioral Risk pipeline (Bot Detection) and a Strategic Credit Card Intelligence module. 📈 Leveraging T-SQL, Window Functions, and Statistical Baselines to drive financial growth and mitigate fraud.

Portfolio of capstone and hands-on data analytics projects completed as part of the Purdue University Post Graduate Program in Data Analytics (Simplilearn). Includes Healthcare Readmission Analysis, Retail marketing Analytics, and Financial fraud Detection using Python, SQL, Tableau, and Excel.

SURE Trust SQL & Power BI portfolio: Python automation for Google Forms-MySQL integration, Power BI dashboards for bank loan risk analysis & fraud detection, enterprise customer complaints BI solution. Features real-time sync, advanced DAX, star schema modeling, KPI tracking & interactive visualizations.

End-to-end BI project on a simulated motor insurance portfolio (1M policies). Built data in Python, analyzed in SQL, visualized in Jupyter. Found 187% loss ratio (₹2.93B premium vs ₹5.49B claims). Key issues: luxury underpricing, fraud (15% payouts), long-term liability