AI for Finance: Forecasting & Fraud Training in Thimphu, Bhutan

This course focuses on applying Artificial Intelligence (AI) and Machine Learning (ML) to two critical areas in finance: forecasting (market trends, risk modeling, credit scoring) and fraud detection (transaction monitoring, anomaly detection, insider threats). Participants will gain both conceptual knowledge and hands-on experience in designing, implementing, and evaluating AI-driven financial solutions.

AI Foundations in Finance

Introduction to AI in Finance

• AI applications in financial services

• Overview of forecasting and fraud detection challenges

Data for AI in Finance

• Financial datasets (transactions, credit, time series)

• Data preprocessing and feature engineering

• Handling imbalanced and anomalous data

Forecasting with AI

• Time series analysis with AI/ML (ARIMA vs. LSTM, RNNs, Transformers)

• Use cases: revenue forecasting, stock trend prediction, credit scoring

Fraud Detection & Risk Management

Fraud Detection using AI

• Fraud detection methods: supervised, unsupervised, and hybrid approaches

• Anomaly detection (autoencoders, clustering, statistical models)

• Real-time fraud detection in payments and banking

Case Studies in AI for Fraud

• Credit card fraud detection

• Insider trading monitoring

• AML (Anti-Money Laundering) with AI

Risk, Compliance, and Ethics

• Regulatory frameworks: Basel III, AML/KYC norms, GDPR

• Model interpretability & explainability in finance AI

• Managing bias, fairness, and transparency

Hands-on Exercises

Summary and Conclusion