Payment Risk And Fraud with AI: A Beginner's Guide from Udemy

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 risks
The basics of artificial intelligence and its applications
Hands-on projects applying AI to real payment risk scenarios
Optional deep-dive into the math behind AI for those interested

Why 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 careers
Fraud prevention specialists interested in AI applications
Beginners in the payments industry seeking practical skills
Anyone curious about how AI is transforming fraud prevention

By 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.

What's inside

Learning objectives

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.

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.

Syllabus

Introduction

Introduction to AI

What’s AI

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

AI History

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

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

Key concepts and terminology: Prompt and Prompt Engineering

AI agents

Payment Introduction

payment overview

card system

chargeback and refund

ACH system

3DS2.0

card network fraud programs

Reg e and Reg z

payment quiz

Payment Risk Introduction

payment risk overview

Third party fraud: ATO risk

Third party fraud: How to identify ATO

Third party fraud: NSF and SF

Third party fraud: How to identify NSF & SF

Third party fraud: merchant risk

Third party fraud: how to identify merchant risk

First party fraud: Family and friend fraud

First party fraud: how to identify family and friend fraud

payment risk quiz

The math behind AI

Neural Network

Word Embeddings

Transformer, Encoder and Decoder

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

Decision Tree model for payment fraud

How to use GPT to build the model for us

AI Project 2: Let’s build an AI-enpowered expert for Visa rules

Visa chargeback rules

Let's build a visa chargeback GPT

The math behind ML (Optional)

ML basics

regression 101

regression 102

regression 103

linear regression 104

logistic regression 101

logistic regression 102

decision tree 101

decision tree 102

random forest 101

random forest 102

gradient boosting decision tree 101

gradient boosting decision tree 102

xgboost 101

xgboost 102

testing and validation

Congratulations

If you have any questions, please feel free to reach out at talkaboutfraudandscam@gmail.com

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Payment Risk And Fraud with AI: A Beginner's Guide with these activities:

Review Payment Systems Fundamentals

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Solidify your understanding of payment systems to better grasp the fraud risks and AI solutions discussed in the course.

Browse courses on Payment Systems

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Review the different types of payment systems.
Understand the flow of funds in each system.
Identify potential vulnerabilities in each system.

Review 'Fraud Prevention for Dummies'

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Gain a broader understanding of fraud prevention strategies to contextualize the AI-driven approaches taught in the course.

View Putting Knowledge to Work on Amazon

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Read the chapters related to payment fraud.
Identify common fraud schemes and prevention methods.
Note areas where AI could enhance prevention efforts.

Analyze a Real-World Fraud Case

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Apply your knowledge of payment systems, fraud risks, and AI to analyze a real-world fraud case and propose AI-driven solutions.

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Find a publicly available fraud case study.
Identify the vulnerabilities exploited by the fraudster.
Propose AI-based solutions to prevent similar fraud.
Document your analysis and proposed solutions.

Four other activities

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Create a Presentation on AI in Payment Fraud Detection

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Synthesize your learning by creating a presentation that explains how AI can be used to detect and prevent payment fraud.

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Research different AI techniques used in fraud detection.
Prepare slides explaining the techniques and their benefits.
Include real-world examples of AI-driven fraud detection.
Practice your presentation.

Follow AI/ML Tutorials for Fraud Detection

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Deepen your understanding of AI/ML by following tutorials focused on fraud detection and implementing the techniques learned.

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Find tutorials on AI/ML for fraud detection.
Follow the tutorials and implement the code.
Experiment with different parameters and datasets.
Document your findings and insights.

Review 'Machine Learning for Fraud Detection'

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Enhance your understanding of machine learning algorithms used in fraud detection and their practical applications.

View Putting Knowledge to Work on Amazon

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Read the chapters related to specific ML algorithms.
Understand the strengths and weaknesses of each algorithm.
Consider how these algorithms can be applied to payment fraud.

Contribute to an Open Source Fraud Detection Project

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Apply your skills and knowledge by contributing to an open-source project focused on fraud detection, gaining practical experience and collaborating with other experts.

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Find an open-source fraud detection project.
Identify areas where you can contribute.
Contribute code, documentation, or testing.
Participate in community discussions.

Career center

Learners who complete Payment Risk And Fraud with AI: A Beginner's Guide will develop knowledge and skills that may be useful to these careers:

Fraud Prevention Specialist

Fraud Prevention Specialists are at the forefront of protecting organizations from fraudulent activities. This role involves implementing and managing fraud prevention systems, analyzing data to identify potential fraud, and developing strategies to mitigate risks. This course is designed to help one become a Fraud Prevention Specialist, equipping one with practical skills in payment risk management and AI-driven fraud detection. The course content covers the fundamentals of payment systems, fraud types, and the application of machine learning techniques. The coverage of AI tools and techniques gives job-ready skills that Fraud Prevention Specialists can use to combat fraud.

See salaries and explore the career path for Fraud Prevention Specialist

Fraud Analyst

The role of a Fraud Analyst is critical in protecting organizations from financial losses due to fraudulent activities. This position involves analyzing transactions, identifying suspicious patterns, and implementing preventative measures. This course directly addresses the core skills needed to excel as a Fraud Analyst, providing a solid foundation in understanding payment systems, risk management, and the latest AI techniques for fraud detection. The course's coverage of chargebacks, refunds, and fraud programs directly translates to the analytical tasks of identifying and mitigating fraud. The hands-on AI projects also help the analyst to stay ahead of emerging fraud trends. The course provides a practical approach to problem-solving in payment risk.

See salaries and explore the career path for Fraud Analyst

Risk Manager

Risk Managers are responsible for identifying and mitigating potential risks within an organization. This includes financial, operational, and compliance risks, making a Risk Manager essential for maintaining stability and security. This course provides an understanding of payment systems, various fraud types and risk management strategies, all of which are crucial to a Risk Manager's toolkit. The course helps Risk Managers stay ahead of emerging threats by integrating AI techniques for identifying and preventing payment fraud. By mastering these skills, Risk Managers can more effectively protect their organizations from financial losses and reputational damage. The course also covers key concepts such as chargeback, refund, and fraud programs.

See salaries and explore the career path for Risk Manager

Payment Systems Manager

A Payment Systems Manager oversees the operations and security of an organization's payment processing infrastructure. The Payment Systems Manager ensures seamless and secure transactions, and the Payment Systems Manager must understand the intricacies of payment systems and fraud prevention techniques. This course provides a foundational understanding of payment systems, including card systems, chargebacks, refunds, and relevant regulations. The course also explores the application of AI in combating fraud, which can greatly enhance the security and efficiency of payment processing systems. The material on AI-powered fraud detection in the course prepares one to manage modern payment systems.

See salaries and explore the career path for Payment Systems Manager

Compliance Officer

Compliance Officers ensure that an organization adheres to relevant laws, regulations, and internal policies. This role requires a keen understanding of the legal and regulatory landscape. This course addresses the compliance aspects of payment systems and fraud prevention by covering topics such as regulations and card network fraud programs. The course may be particularly beneficial for compliance officers who need to understand payment systems and fraud risks. This knowledge supports the officers in developing and implementing effective compliance strategies.

See salaries and explore the career path for Compliance Officer

Data Analyst

Data Analysts collect, process, and analyze data to extract meaningful insights and support decision-making. This course provides a good introduction for Data Analysts interested in specializing in payment risk and fraud prevention. The course covers AI and machine learning techniques used to detect and prevent payment fraud, the course helps analysts develop practical, job-ready skills. The Data Analyst can take advantage of the AI training for fraud detection.

See salaries and explore the career path for Data Analyst

AI Developer

AI Developers are the people who specialize in creating artificial intelligence models. The AI developer will be expected to have some familiarity with payment methods, fraud risk, and third party fraud. The AI Developer builds models to assist fraud analysts, compliance officers, and Risk Managers. Additionally, AI Developers create agents, prompts, and tools that others will use at an organization. An organization developing in-house AI tools may benefit from hiring an AI developer.

See salaries and explore the career path for AI Developer

Actuary

Actuaries apply mathematical and statistical principles to assess risk and uncertainty in the insurance and finance industries. Actuaries need a deep understanding of risk assessment and modeling. This course helps actuaries learn about fraud types, key trends, risk management strategies, and AI implementation for the same. The coverage of machine learning techniques prepares an actuary for the challenges of predicting fraud. This knowledge helps actuaries in assessing and managing the financial risks.

See salaries and explore the career path for Actuary

Data Scientist

Data Scientists analyze complex datasets to extract meaningful insights and develop predictive models, particularly in industries dealing with high volumes of transactions. This course may be useful for Data Scientists looking to specialize in fraud detection within the payment industry. The course covers AI and machine learning techniques relevant to identifying and preventing payment fraud. The hands-on AI projects also allow Data Scientists to apply their analytical skills to real-world scenarios, making this course a good way to enter payment fraud.

See salaries and explore the career path for Data Scientist

Business Intelligence Analyst

Business Intelligence Analysts analyze data to identify trends and insights that can help organizations make better business decisions. This course might be helpful for Business Intelligence Analysts in the financial or e-commerce sectors. The Business Intelligence Analyst gain insight into payment systems and fraud risks. This course also assists in making data-driven recommendations to improve fraud prevention and risk management strategies. The course also exposes Business Intelligence Analysts to AI-powered fraud detection techniques.

See salaries and explore the career path for Business Intelligence Analyst

Financial Crime Investigator

Financial Crime Investigators work to detect, investigate, and prevent financial crimes such as fraud, money laundering, and terrorist financing. This course may be helpful as it equips investigators with a strong foundation in understanding payment systems, fraud types, and risk management strategies. The knowledge gained from this course may allow a Financial Crime Investigator to better identify and investigate payment-related fraud cases. A Financial Crime Investigator who takes this course will also learn how to leverage AI-powered fraud detection tools.

See salaries and explore the career path for Financial Crime Investigator

Security Consultant

Security Consultants advise organizations on how to protect their assets and data from security threats. This can involve assessing vulnerabilities, developing security strategies, and implementing security measures. This course may benefit Security Consultants working with clients in the financial or e-commerce sectors, since this course provides a solid understanding of payment systems, fraud risks, and AI-driven security solutions. This knowledge helps Security Consultants offer informed recommendations and implement effective security strategies to protect against payment fraud. The Security Consultant will gain familiarity with the ways AI can assist the field.

See salaries and explore the career path for Security Consultant

Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning models and algorithms. This course may be helpful for those wanting to apply their skills to the specific problem of payment fraud detection. The course introduces the basics of AI and its applications in payment risk management. The hands-on projects, focused on applying AI to real payment risk scenarios, provide practical experience that Machine Learning Engineers can leverage in their roles. In particular, knowledge of decision trees, gradient boosting, and XGBoost may offer practical benefits.

See salaries and explore the career path for Machine Learning Engineer

Bank Teller

Bank tellers are the primary point of contact for customers at a bank. A bank teller typically needs to be able to identify fraud, security concerns, and other issues. Therefore, a bank teller needs to be aware of ATO risk, NSF, SF, and other fraud types. Even a basic familiarity with chargebacks, refunds, and fraud programs is useful. For a teller who wishes to rise through the ranks, this course provides background for the next stage of a banking career.

See salaries and explore the career path for Bank Teller

Underwriter

Underwriters assess and evaluate the risk involved in providing loans, insurance, or other financial products. They analyze financial data and other relevant information to determine the likelihood of losses and set appropriate terms and conditions. This course may be helpful for Underwriters working in industries where payment fraud is a concern. By understanding payment systems, fraud risks, and AI-driven fraud prevention techniques, Underwriters can better assess the risk associated with different transactions and make informed decisions. The concepts of chargeback and refund may be of particular interest.

See salaries and explore the career path for Underwriter

Reading list

We've selected one books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Payment Risk And Fraud with AI: A Beginner's Guide.

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Provides a broad overview of fraud prevention techniques, including those relevant to payment systems. It good starting point for beginners to understand the landscape of fraud and the various methods used to combat it. While not focused specifically on AI, it provides valuable context for understanding the problems that AI-based solutions aim to solve. This book is more valuable as additional reading than as a current reference.

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Payment Risk And Fraud with AI

A Beginner's Guide

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