Fraudsheild AI Lab Workshop
“Unlock the Future of Fraud Prevention: Mastering AI for Secure FinTech and Banking
Skills you will gain:
About Program:
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.
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.
Program Objectives:
What you will learn?
📅 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
📅 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
📅 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
📅 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
📅 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
Mentor Profile
Fee Plan
Get an e-Certificate of Participation!
Intended For :
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.
Career Supporting Skills
Program Outcomes
-
Hands-on experience with AI tools for fraud prevention.
-
In-depth understanding of fraud risks in FinTech and banking.
-
Practical application of AI models in real-world scenarios.
-
Knowledge of AI ethics and regulatory compliance.
-
Career-ready skills for roles in financial security and AI.
-
Ability to design innovative fraud prevention strategies.