RegTech KYC/AML Anomaly Detection and Compliance Dashboard for Indian Fintech

Objective: To develop an automated dashboard that identifies KYC/AML anomalies and supports compliance monitoring for Indian fintech firms.

Problem & Context: Indian fintech companies face complex regulatory requirements for KYC (Know Your Customer) and AML (Anti-Money Laundering) compliance as mandated by RBI and SEBI. Manual processes are error-prone and inefficient, leading to missed anomalies and compliance gaps.

Approach & Methodology: The project involves gathering anonymized KYC/AML transaction data, analyzing patterns, applying machine learning models for anomaly detection, and creating a dashboard for real-time compliance monitoring. Regulatory guidelines and case studies from Indian fintechs will inform the methodology.

Deliverables & Analysis: The student team will deliver a working dashboard prototype, a report detailing statistical and ML anomaly detection methods, sample flagged cases, and a compliance checklist mapped to Indian regulations.

Business Impact: The project aids compliance officers in identifying suspicious transactions and regulatory breaches, reducing risk, improving audit readiness, and supporting decision-making for regulatory reporting in the Indian fintech context.