AML Checker detection and analysis tools for cryptocurrency transactions using machine learning and blockchain data. Ensuring compliance and reducing money laundering risks.

📊 Interactive Power BI dashboard analyzing PhonePe transactions, users, and regional trends across India.

Real-time intent decoding and risk engine for Ethereum wallet interactions powering ENSight’s safety layer.

A CLI tool for analyzing MySQL ROW binlog files to quickly identify hot tables, large transactions, write spikes, and workload patterns.

A simplified tool that analyzes mock banking transaction data, identifies spending patterns, categorizes expenses, and visualizes results clearly.

A complete end-to-end Bank Analytics project analyzing loan data and credit/debit transactions. Includes dashboards in Excel, Power BI, Tableau, SQL-based analysis, and a detailed presentation. Datasets are confidential and not uploaded.

The project involves developing a Python script for the Fintech DataLab Challenge23, utilizing a linear regression model to forecast client transactions and predict transaction amounts based on historical data for a leading fintech company.

Applying SQL skills to analyze historical credit card transactions and consumption patterns in order to identify possible fraudulent transactions.

The goal of this blockchain exploration project is to utilize BigQuery to explore the blockchain of a chosen cryptocurrency (BTC).

Real-time Ethereum wallet interceptor that explains transaction intent, surfaces risk, and adds inline context in the browser.

Advanced SQL project analyzing financial transaction datasets to uncover fraud patterns, suspicious transfers, balance inconsistencies, and high-risk accounts using CTEs, recursive queries, and window functions.

A machine learning project that classifies blockchain transactions into categories such as sales, purchases, transfers, scams, and phishing attempts. The project leverages models like Random Forest, KNN, and AdaBoost, with advanced preprocessing techniques to improve accuracy and address class imbalance.

The Natixis Fraud Account Detection Workflow - Dataset Preparation & Algorithm

TradeSphere is a cryptocurrency trading platform with real-time price updates, wallet management, facial recognition security, and AI-powered market insights.

End-to-end financial data pipeline using Python, Pandas, SQL & Excel — generates revenue reports and detects data discrepancies from transaction datasets.

Bitcoin blockchain analysis platform with Neo4j, GraphQL, and Python tools

"A comprehensive SQL-based analysis of a banking database for 'The Big Bank'. This project explores customer banking behavior, transaction trends, and account management. The analysis aims to optimize banking operations, enhance fraud detection, improve customer segmentation, and increase revenue using data-driven insights."

Hybrid fraud and scam tracing platform with off-chain transaction indexing, graph analysis, and Kadena blockchain anchoring for immutable case records.

End-to-end analytics project simulating real-world digital payment data, performing EDA & data engineering in Python, and building an executive-level Power BI dashboard for transaction success, failure, and peak-time risk intelligence.

Optimized Bitcoin blockchain analysis platform with shared volume architecture. Neo4j graph database, GraphQL API with Redis caching, and Python analysis tools.