AI in Fraud Detection and Risk Management

AI in Fraud Detection and Risk Management

Course Objectives:
By the end of this course, participants will:
• Understand AI’s role in fraud detection and risk management.
• Learn key AI techniques for fraud detection and risk assessment.
• Apply machine learning to identify and mitigate fraud and risks.

Introduction to AI in Fraud Detection and Risk Management
• Overview of AI and its applications in fraud detection and risk management.
• Key fraud types (financial fraud, identity theft, etc.) and AI’s role in combating them.
• Benefits of using AI tools in risk management.

Fraud Detection Techniques Using AI
• Introduction to machine learning in fraud detection.
• Supervised learning for fraud identification: basic algorithms like decision trees and logistic regression.
• Anomaly detection using AI to spot unusual behavior or outliers in data.

Machine Learning Models for Fraud Detection
• Key algorithms for fraud detection: Random Forests, Support Vector Machines (SVM).
• Data preprocessing for training AI models.
• Evaluation of model performance: accuracy, precision, recall, and F1-score.

AI in Risk Assessment
• Using AI to assess and predict risks: financial, operational, and credit risks.
• Real-time risk mitigation with AI tools.
• Risk prediction models and their application in various industries.

DATE:
1ST BATCH:14th – 17th Apr, 2025
2ND BATCH: 28th – 31st Oct, 2025