NATIONAL FRAUD PREVENTION CHALLENGE

About the Challenge: The National Fraud Prevention Challenge (NFPC) is a multi-stage hackathon launched by RBIH along with IIT Delhi TRYST as a partner to tap into India’s top AI/ML talent and accelerate innovation on the MuleHunter.ai™ /Digital payments intelligence platform, an advanced AI system built to detect mule accounts used in financial fraud. This is not just a competition. It’s a gateway to real-world impact, elite employment opportunities, and national-level recognition. Objectives: Enhance and expand AI/ML capabilities for MuleHunter AI and DPIP. Identify top AI/ML talent specializing in fraud analytics, anomaly detection, and advanced ML research. Encourage academic and research institutions to collaborate on real-world financial security challenges. Build a pipeline of interns/employees for RBIH's AI team. Promote long-term partnerships with leading universities and research group Phase 1 Objectives for Participating in Teams: Selected participants will be given a labelled synthetic dataset and are required to: Perform Exploratory Data Analysis (EDA) Design features (both supervised & unsupervised) to capture anomalous behavior of mule accounts Demonstrate the ability to think creatively and analytically with real-world fraud patterns Who Can Apply?: Each team must consist of 2 to 4 members, and can include: 3rd, or 4th Year UG/PG students. PhD scholars. Professors or Researchers. Specialized AI Labs or Campus Fintech Clubs. Prizes & Incentives: Cash Prizes: ₹10L (1st), ₹5L (2nd), ₹2.5L (3rd) Employment Offer: Selected participants will receive guaranteed roles/internships at Reserve Bank Innovation Hub to work on the MuleHunter/DPIP platform. Submission Requirements (per team): Cover Letter (PDF or DOCX) Brief introduction of the team Motivation for participating in the NFPC Team Composition Details Names, roles (e.g., Team Lead, ML Lead, etc.), and email IDs Educational background (Year, Degree, Department) Qualification Summary Summary of each member’s relevant experience in: Machine Learning / Deep Learning Financial analytics or fraud detection (if any) Projects, publications, or competitions (e.g., Kaggle, IEEE papers, GitHub links) Note: Each team must register in unstop before submission. Timelines: Registration valid till 15th February 2026. Phase 1 will be in 24th February 2026 (online mode). Phase 2 (final round) for the selected teams from Phase 1 will be held between 27th February to 1st March 2026 on IIT Delhi campus. Additional Information: For more detailes, read the brochure or contact POC.