Fraudsheild AI Lab Workshop
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Course Overview
Program Syllabus
Module 1
About This Course
This course is designed for professionals in finance, tech, and security, providing a comprehensive overview of AI’s role in combating fraud. Each day consists of a 90-minute session (60 minutes of lecture/discussion + 30 minutes of lab assessment). Sessions assume basic knowledge of banking and tech; no advanced coding required, but labs use accessible tools like Python notebooks or simulation platforms (e.g., via Google Colab or pre-set environments). Labs include assessments via quizzes, practical exercises, and self-evaluations to reinforce learning.
Module 2
Aim
The aim of this workshop is to equip professionals with the knowledge and skills to leverage AI in preventing fraud within the FinTech and banking sectors, focusing on practical tools, ethical considerations, and emerging trends.
Module 3
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Application Details
FraudShield AI Lab is a hands-on learning platform for the “AI in Fraud Prevention” workshop. It lets participants experiment with AI-powered tools for transaction anomaly detection, phishing classification, identity verification, and voice biometrics, while following a structured curriculum supported by an AI tutor. Through interactive quizzes, real-world challenges, and rich visualizations (including 3D transaction network graphs), financial professionals, security analysts, developers, and students can build practical skills to design more secure, AI-driven financial systems.
Lead Instructor
Dr. Sarah Chen
PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.
Limited SeatsClosing Soon
Fraudsheild AI Lab Workshop
Professional Certification Program
🎥
FormatLive + Recorded
📅
Duration8 Weeks
📜
CertificationVerified
Module 4
Workshop Structure
Module 5
📅 Day 1 – Fundamentals of Fraud in FinTech and Banking
- Introduction to fraud types: Identity theft, payment fraud, money laundering, and emerging threats like deepfakes
- Overview of FinTech and banking vulnerabilities: Digital transactions, APIs, and regulatory challenges (e.g., PSD2, GDPR)
- Historical evolution of fraud prevention: From rule-based systems to AI-driven approaches
Module 6
📅 Day 2 – Introduction to AI and Machine Learning in Fraud Prevention
- Basics of AI/ML: Supervised vs. unsupervised learning, key algorithms (e.g., decision trees, neural networks)
- AI in transaction monitoring: Real-time detection using features like behavioral biometrics and geolocation
- Case studies: How banks like JPMorgan use ML for credit card fraud reduction
Module 7
📅 Day 3 – Advanced AI Techniques for Anomaly Detection
- Anomaly detection: Autoencoders, isolation forests, and graph-based analysis for network fraud
- NLP and AI in anti-money laundering: Sentiment analysis on communications and entity recognition
- Integration with blockchain and federated learning for secure data sharing
Module 8
📅 Day 4 – Implementation and Ethical Considerations in AI Fraud Systems
- System integration: APIs, cloud deployment (e.g., AWS Fraud Detector), and hybrid human-AI workflows
- Challenges: Bias in AI models, false positives, and regulatory compliance (e.g., explainable AI under EU AI Act)
- Best practices: Data privacy, model auditing, and scaling for high-volume transactions
Module 9
📅 Day 5 – Emerging Trends and the Future of AI in Banking Security
- Future trends: Quantum-resistant AI, generative AI for fraud simulation, and zero-trust architectures
- Global perspectives: AI in decentralized finance (DeFi) and cross-border fraud prevention
- Wrap-up: Career opportunities, ongoing research, and building resilient systems
Module 10
Who Should Enrol?
This workshop is intended for professionals in the finance, technology, and security sectors, including those involved in fraud prevention, risk management, and AI implementation. A basic understanding of banking and technology is recommended, but no advanced coding skills are required.
Module 11
Important Dates
Module 12
Registration Ends
12/02/2025
IST 6 PM
Module 13
Workshop Dates
12/02/2025 – 12/06/2025
IST 7 PM
Module 14
Workshop Outcomes
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Hands-on experience with AI tools for fraud prevention.
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In-depth understanding of fraud risks in FinTech and banking.
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Practical application of AI models in real-world scenarios.
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Knowledge of AI ethics and regulatory compliance.
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Career-ready skills for roles in financial security and AI.
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Ability to design innovative fraud prevention strategies.
Module 16
Fee Structure
Module 17
Student
₹4999 | $149
Module 18
Ph.D. Scholar / Researcher
₹5999 | $199
Module 19
Academician / Faculty
₹6999 | $249
Module 20
Industry Professional
₹7999 | $349
Module 21
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
Module 22
Join Our Hall of Fame!
Take your research to the next level with NanoSchool.
Module 23
Publication Opportunity
Get published in a prestigious open-access journal.
Module 24
Centre of Excellence
Become part of an elite research community.
Module 25
Networking & Learning
Connect with global researchers and mentors.
Module 26
Global Recognition
Worth ₹20,000 / $1,000 in academic value.
Module 27
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