• views: 28
• date: 10 January 2025
• posted by: AD-TEAM

Master Payment Risk and Fraud Prevention with AI

What you'll learn

Gain a comprehensive understanding of payment systems, fraud types, and key risk management strategies used in the industry.

Discover the basics of AI and how to apply machine learning techniques to detect and prevent payment fraud effectively.

Complete hands-on projects to apply AI tools and techniques to real payment risk scenarios, giving you practical, job-ready skills.

Learn how to leverage AI to stay ahead of fraud trends, positioning yourself as a forward-thinking professional in the payment risk space.

Requirements

No requirements. This is a beginner's guide

Description

In today's fast-paced digital world, payment fraud is evolving rapidly, and AI is at the forefront of combating these risks. This course is your gateway to mastering both payment risk management and artificial intelligence, giving you the tools to stay ahead in the fight against fraud.Led by Sean, a Certified Fraud Examiner with experience at top companies like Google and PayPal, this course combines real-world payment risk strategies with cutting-edge AI techniques. You'll gain a deep understanding of both fields and learn how to apply AI to solve real-world fraud challenges.What You'll Learn:The fundamentals of payment systems and payment risksThe basics of artificial intelligence and its applicationsHands-on projects applying AI to real payment risk scenariosOptional deep-dive into the math behind AI for those interestedWhy Take This Course?Payment fraud costs businesses billions each year. Knowing how to leverage AI for fraud prevention can set you apart as a top professional in this growing field. This course not only covers theory but also equips you with practical skills through project-based learning.Who Is This Course For?Payment risk professionals looking to advance their careersFraud prevention specialists interested in AI applicationsBeginners in the payments industry seeking practical skillsAnyone curious about how AI is transforming fraud preventionBy the end of this course, you'll have a clear understanding of how AI can solve payment risk problems, empowering you to protect businesses and customers from fraud.Ready to stay ahead of the curve? Enroll now and take the first step toward becoming an expert in Payment Risk and AI!

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Introduction to AI

Lecture 2 What's AI

Lecture 3 An example of how AI can help solve a problem without any coding knowledge

Lecture 4 AI History

Lecture 5 Key concepts and terminology: Generative AI, Predictive AI, NLP and LLM

Lecture 6 Key concepts and terminology: Token, Transformer and Fine-Tuning

Lecture 7 Key concepts and terminology: Prompt and Prompt Engineering

Lecture 8 AI agents

Section 3: Payment Introduction

Lecture 9 payment overview

Lecture 10 card system

Lecture 11 chargeback and refund

Lecture 12 ACH system

Lecture 13 3DS2.0

Lecture 14 card network fraud programs

Lecture 15 Reg e and Reg z

Section 4: Payment Risk Introduction

Lecture 16 payment risk overview

Lecture 17 Third party fraud: ATO risk

Lecture 18 Third party fraud: How to identify ATO

Lecture 19 Third party fraud: NSF and SF

Lecture 20 Third party fraud: How to identify NSF & SF

Lecture 21 Third party fraud: merchant risk

Lecture 22 Third party fraud: how to identify merchant risk

Lecture 23 First party fraud: Family and friend fraud

Lecture 24 First party fraud: how to identify family and friend fraud

Section 5: The math behind AI

Lecture 25 Neural Network

Lecture 26 Word Embeddings

Lecture 27 Transformer, Encoder and Decoder

Section 6: AI Project 1: Let's build a decision tree model with AI

Lecture 28 Decision Tree model for payment fraud

Lecture 29 How to use GPT to build the model for us

Section 7: AI Project 2: Let's build an AI-enpowered expert for Visa rules

Lecture 30 Visa chargeback rules

Lecture 31 Let's build a visa chargeback GPT

Section 8: The math behind ML (Optional)

Lecture 32 ML basics

Lecture 33 regression 101

Lecture 34 regression 102

Lecture 35 regression 103

Lecture 36 linear regression 104

Lecture 37 logistic regression 101

Lecture 38 logistic regression 102

Lecture 39 decision tree 101

Lecture 40 decision tree 102

Lecture 41 random forest 101

Lecture 42 random forest 102

Lecture 43 gradient boosting decision tree 101

Lecture 44 gradient boosting decision tree 102

Lecture 45 xgboost 101

Lecture 46 xgboost 102

Lecture 47 testing and validation

Section 9: Congratulations

Lecture 48 congratulations!

Fraud Analysts and Investigators,AI Enthusiasts Interested in Payments,Beginners in the Payments Industry,Career Changers and Tech Professionals who are interested in payment risk/fraud,Data analysts in payment risk/fraud,beginners who are interested in payment risk data science and AI




   
   
   

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