Assessfy Industry Projects Lab Advanced 6 milestones 100 marks

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

Industry: Fintech Industry: Fintech Function: Data Analytics Type: Industry-vertical applied project Team: up to 4 Assessment: 6 milestones (100 marks)

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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About this project

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.

Milestones

1. Problem Definition & Business Case

10 marks 14d

Submit a brief outlining the business case for KYC/AML anomaly detection in Indian fintech, including regulatory context and project scope. Reviewed via presentation and written summary.

2. Domain Research & Data Gathering

10 marks 21d

Conduct literature review on Indian KYC/AML norms, gather anonymized data (public datasets/RBI sandbox), and define key compliance metrics. Reviewed via annotated bibliography and data summary.

3. Solution Design / Methodology

15 marks 21d

Draft methodology document outlining chosen ML/statistical anomaly detection techniques, dashboard components, and regulatory mapping. Reviewed via technical report and stakeholder feedback.

4. Build / Analysis & Implementation

30 marks 35d

Develop and implement anomaly detection models and dashboard prototype; perform exploratory analysis and flag sample anomalies. Reviewed via code review, dashboard demo, and interim report.

5. Validation & Results

25 marks 28d

Validate models using test cases, summarize results (precision/recall, compliance accuracy), and iterate with stakeholder input. Reviewed via validation report and stakeholder review session.

6. Final Report & Presentation

10 marks 21d

Prepare comprehensive final report, including business impact assessment, methodology, results, dashboard screenshots, and recommendations. Reviewed via final presentation and written submission.

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Skills you'll learn

FintechData AnalyticsIndian fintech regulatory knowledge (RBI/SEBI KYC/AML norms)Data preprocessing and cleaningStatistical and machine learning anomaly detectionDashboard design and visualizationPython programming (PandasScikit-learn)SQL querying for data extractionEffective business communicationRequirements gathering from compliance stakeholders

Tools used

Python (PandasScikit-learnMatplotlib/Plotly)SQL (MySQL/PostgreSQL)Power BI or Tableau for dashboardingExcel for preliminary analysisPublic KYC/AML datasets (e.g.RBI sandboxKaggle AML datasets)RegTech frameworks (e.g.SEBI/RBI guidelines)Jupyter Notebook for prototyping

Prerequisites

Database Management SystemsStatistics and ProbabilityBusiness Analytics or Data AnalysisPython programming basicsUnderstanding of Indian regulatory environment

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You'll earn — Certificate (PDF)

AICTE-aligned Project Completion Certificate

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