UBS LauzHack Hackathon Challenge (24 hours)

This project, developed during a 24-hour UBS hackathon, addresses the challenge of identifying identical users within a massive set of banking transaction data. By leveraging advanced data processing and matching algorithms, our solution efficiently detects and connects user profiles across multiple transactions, ensuring accuracy and scalability.

• High-performance data parsing and analysis for large-scale datasets.
• Intelligent matching algorithms to identify duplicate users based on transaction patterns, metadata, and identifiers.
• Scalable and adaptable for integration into banking systems.

• Transactions Processed: 1,450,000
• Time Taken: 90 seconds
• Matching Accuracy: 66%

This hackathon project was collaboratively developed by

• Yonyc (Arnaud)
• jdecorte (John)
• dspilleb (Dan)
• MVPee (Marius)