Nihal Girish@nihalgirish122
1
Events attended
1
Submissions made
1 year of experience
About me
I’m a computer science undergraduate who enjoys building things and figuring out how they actually work. Most of my time is split between university coursework, internships, and research, where I’ve been getting hands-on experience with machine learning and problem-solving in real settings. I like fast, practical environments where ideas turn into something usable, which is why hackathons appeal to me. I’m comfortable learning on the fly, experimenting, and working closely with a team to push an idea forward under time pressure. I’m applying to this hackathon to build something meaningful, learn from other motivated people, and challenge myself beyond normal classes or assignments.
🤝 Top Collaborators
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🤓 Latest Submissions
REDLINE AI - your fraud monitoring system
RedLine AI: Automated Fraud Detection & Analytics RedLine AI is a specialized security application designed to help financial analysts detect fraudulent activity within large transaction datasets. Built using Python and Streamlit, the platform replaces slow manual auditing with an automated risk-scoring engine that processes data in seconds. How It Works The system evaluates every transaction against a custom logic engine comprising three specific security checks: Merchant Risk: The app cross-references payees against a watchlist of high-risk entities. Transactions involving known money-laundering fronts (e.g., shell companies, offshore casinos) are immediately flagged with a high severity score. Geospatial Analysis: Using coordinate data, the system calculates the physical distance between the transaction location and the user’s registered office. Transactions occurring at improbable distances trigger a "Geo-Risk" alert. Velocity Tracking: The engine monitors the frequency of spending. Rapid sequences of high-value transfers—often a sign of account compromise—are detected and highlighted. Key Features Batch Processing: Analysts can upload raw CSV or Excel logs to instantly visualize risk distribution. The dashboard separates "Clean" data from "Critical" threats using clear visual indicators. Live Intercept Mode: Beyond historical data, the app features a real-time monitoring mode. It simulates a direct connection to a payment gateway, analyzing JSON transaction packets with sub-second latency to catch fraud as it occurs.
7 Feb 2026
