5 Best Fraud Analytics Courses Online in 2024
In the dynamic world of digital transactions and interconnected financial landscapes, the specter of fraud looms large. As technology advances, so do the methods of deception employed by those seeking to exploit vulnerabilities in systems and organizations. It's a cat-and-mouse game where the defenders need to stay ahead, and that's where the intriguing realm of fraud analytics comes into play.
Imagine yourself as a digital detective who uncovers hidden patterns, decodes anomalies, and protects businesses from financial fraud. Get ready to fight fraud like a vigilant guardian with these online fraud analytics courses. Let's dive into the world of data-driven detective work and empower ourselves to unmask deception.
Top Fraud Analytics Courses List
- Fraud Prevention, Dispute Resolution, and PCI-DSS Masterclass
- Forensic Accounting and Fraud Examination
- Fraud Risk Analytics (Excel & AI-based tools) and Prevention
- Payment Risk 101
- Real-time Credit card Fraud Detection using Spark 2.2
Disclosure: We're supported by the learners and may get a commission when you purchase via the link.
1. Fraud Prevention, Dispute Resolution, and PCI-DSS Masterclass
In the digital age, where transactions and interactions occur at the speed of light, the importance of safeguarding against fraud cannot be overstated. This course emerges as a beacon of knowledge in the realm of digital deception. Crafted by experts in the field, this course is designed to empower you with the skills and insights necessary to detect, prevent, and combat fraud effectively.
In this fraud analytics course, you will learn the following:
- Learn about general and specific approaches to fraud, from social engineering to card block fraud, convenience fraud, and many others by different actors.
- Learn an extensive list of dispute chargeback codes, from fraudulent processing to invalid core, invalid data, late presentment, and many others.
- Learn an extensive list of fraud prevention techniques: Hotlists, velocity checks, device identification, out-of-wallet checks, fraud scores, etc.
- Learn about the dispute resolution flow for banks (acquiring + issuing), with three main steps: Retrieval request, chargeback, and 2nd chargeback.
- Learn about how a fraud monitoring strategy is assembled, based on merchant risk and transaction volume, as well as data processing/usage considerations.
- Learn about ADR (Alternative Dispute Resolution), and its three main types: negotiation, mediation, and arbitration, as well as their differences.
Throughout the course, you will delve into the intricacies of fraud, understanding its various forms and the methodologies employed by fraudsters. From traditional scams to sophisticated digital fraud, you'll explore the entire spectrum. The curriculum combines theoretical foundations with hands-on practical applications, ensuring that you not only grasp the concepts but also develop the proficiency to apply them in real-world scenarios.
By the end of the course, you will not only be equipped with the theoretical foundations of fraud prevention but will also possess the practical skills needed to navigate the complex landscape of digital security.
- Course rating: 4.5 out of 5.0 (853 rating total)
- Duration: 17.5 Hours
- Certification: Certificate upon completion
2. Forensic Accounting and Fraud Examination
In the relentless battle against fraud, businesses face constant threats from a spectrum of wrongdoers. The course offers a comprehensive exploration of the who, why, and how of fraudulent activities. Beginning with an examination of accidental fraudsters and the profound costs of fraud, the modules delve into the tactics of "predator" fraudsters, providing insights into internal controls for detection and prevention.
In this fraud analytics course, you will learn the following:
- Identify and understand the characteristics of "accidental" fraudsters.
- Grasp the basic elements of fraud and recognize the significant costs associated with fraudulent activities.
- Gain insights into the nature of "predator" fraudsters and explore internal control concepts for detection and prevention.
- Acquire practical skills in data analysis, including the use of Benford analysis and other tools to identify fraudulent activities in big data.
- Develop a comprehensive understanding of money laundering, including objectives, stages, and basic techniques.
- Recognize the importance of whistleblowing in fraud prevention and understand the challenges faced by whistleblowers.
- Build a holistic skill set to effectively contribute to the identification, detection, and prevention of fraud in various organizational contexts.
Unveiling the intricate world of money laundering, participants gain insights into the objectives, stages, and techniques used in this illicit practice. The course further equips learners with essential tools like data analysis and Benford analysis to identify fraudulent activities in the realm of big data.
The course culminates with a focus on whistleblowing, emphasizing its importance and the challenges faced by those who take on this crucial role in the fight against fraud. Throughout, learners acquire practical skills to understand, detect, and prevent fraud, contributing to a safer and more secure business landscape.
- Course rating: 4.7 out of 5.0 (5,370 rating total)
- Duration: 6 Hours
- Certification: Certificate upon completion
3. Fraud Risk Analytics (Excel & AI-based tools) and Prevention
This comprehensive course delves into the intricacies of fraud detection and prevention strategies. Developed to equip learners with essential skills in recognizing, analyzing, and preventing fraudulent activities, the course covers a broad spectrum of topics. From understanding the psychology and motivations behind fraud to exploring advanced analytics techniques for risk assessment, participants will gain practical insights.
In this fraud analytics course, you will learn the following:
- What is fraud?
- How to detect fraud.
- How to prevent fraud.
- What is the fraud triangle?
- What is Benford Law?
- How to use Excel to detect fraud.
- How AI is helping in detecting fraud.
- How to assess an organization for its maturity in fraud prevention
- How to find anomalies in a dataset.
- How to programmatically detect fraud.
- How to apply unsupervised learning to detect fraud.
- How to apply supervised learning to detect fraud.
- What is image analytics and how it is used to detect fraud?
The course encompasses modules on big data analytics, fraud risk management frameworks, and the implementation of preventive measures. By the end, students will be well-versed in fraud risk analytics and equipped to contribute effectively to fraud prevention efforts within various organizational contexts.
- Course rating: 4.2 out of 5.0 (853 rating total)
- Duration: 4.5 Hours
- Certification: Certificate upon completion
4. Payment Risk 101
The course offers a deep dive into the world of payment systems and the associated fraud risks. It is designed to provide a comprehensive understanding of payment mechanisms, as well as the methods employed by fraudsters to commit payment fraud. Participants will gain insights into payment processing technologies, identify vulnerabilities, and learn effective strategies to prevent and combat payment fraud.
In this fraud analytics course, you will learn the following:
- Understand the fundamentals of Payment.
- Understand the fundamentals of Payment Risk and Fraud.
- Family Fraud, Account Takeover (ATO), stolen credit card, nonsufficient funds (NSF).
- Understand how the card system and ACH system work.
- Know how fraudsters conduct payment attacks.
- Work with real-life examples to design risk rules.
- Learn how to design data-driven risk strategies.
- Learn what variables we can use for fraud-fighting.
- Understand how the payment system works like pull/push payments.
- confusion matrix, false positive, precision, recall.
- payment risk-related statistics knowledge.
- confidence interval, confidence level, sampling method.
- payment risk modeling like a decision tree and random forest.
- type 1 and type 2 error
- 3DS2.0, PSD2 and SCA
The course covers essential topics such as card fraud, online payment risks, and the role of technology in securing payment transactions. Whether you are a financial professional, business owner, or someone interested in the intricacies of payment security, this course equips you with valuable knowledge to navigate the evolving landscape of payment systems and fraud prevention.
- Course rating: 4.3 out of 5.0 (787 rating total)
- Duration: 3.5 Hours
- Certification: Certificate upon completion
5. Real-time Credit card Fraud Detection using Spark 2.2
This course provides hands-on experience in implementing fraud detection models using Apache Spark, a powerful distributed computing framework. Participants will learn the fundamentals of credit card fraud, explore real-time data processing with Spark Streaming, and understand how machine learning algorithms can enhance fraud detection accuracy.
In this fraud analytics course, you will learn the following:
- Build end-to-end big data projects using Spark, Kafka, Cassandra, Scala, and Java.
The course covers practical aspects of working with large datasets, implementing feature engineering, and deploying machine learning models for fraud detection. Whether you're a data scientist, developer, or professional in the financial industry, this course offers valuable insights and technical skills to proactively combat credit card fraud in real-time.
- Course rating: 4.4 out of 5.0 (707 rating total)
- Duration: 3 Hours
- Certification: Certificate upon completion
Hey! If you have made it this far then certainly you are willing to learn more and here at Coursesity, it is our duty to enlighten people with knowledge on topics they are willing to learn. Here are some more topics that we think will be interesting for you!