An Ethereum Dynamic Analyzer, a.k.a, open-sourced transaction explorer similar to Phalcon/EthTx/TxTracer

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.

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.

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

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.

Local-first recurring charge audit desk that detects subscriptions, price creep, renewals, and cancellation priorities from statement exports.

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.

A demo showing how we can replicate exploit transactions from one EVM-compatible blockchain to another EVM-compatible blockchain

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.

Detects and analyzes sandwich attack patterns in Ethereum mempool transactions

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.

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.

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

The Natixis Fraud Account Detection Workflow - Dataset Preparation & Algorithm

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