Money in the Multiverse: Simulating Fraud across Parallel Payment Realities
“Unlock the Future of Fraud Prevention: Mastering AI for Secure FinTech and Banking
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.
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.
Workshop Structure
📅 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
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.
Important Dates
Registration Ends
11/01/2025
IST 6 PM
Workshop Dates
11/01/2025 – 11/05/2025
IST 7 PM
Workshop 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.
Meet Your Mentor(s)
Fee Structure
Student Fee
₹2999 | $75
Ph.D. Scholar / Researcher Fee
₹3999 | $85
Academician / Faculty Fee
₹4999 | $95
Industry Professional Fee
₹6999 | $115
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
Join Our Hall of Fame!
Take your research to the next level with NanoSchool.
Publication Opportunity
Get published in a prestigious open-access journal.
Centre of Excellence
Become part of an elite research community.
Networking & Learning
Connect with global researchers and mentors.
Global Recognition
Worth ₹20,000 / $1,000 in academic value.
View All Feedbacks →