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  1. Courses
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  3. GenAI for Fraud Detection and Compliance

GenAI for Fraud Detection and Compliance

Uncover how generative AI can transform fraud detection and compliance. This course equips professionals with practical skills to detect fraud, enhance monitoring, and stay ahead of evolving threats in the financial industry.

Karlis Zars
Karlis Zars
Data Science | intermediate | 1 hour |   Published: Apr 2025
In partnership with:  Coursera

    Discussions

Overview

1kSTUDENTS*
98.7%RECOMMEND*
  • 1 hour of on-demand video  
  • Certificate of completion  
  • Direct access/chat with the instructor 
  • 100% self-paced online 

Imagine you're a compliance officer who just uncovered a major fraud scheme that traditional systems missed. How do you stay ahead? Generative AI for Fraud Detection and Compliance is a focused course that equips professionals with the skills to leverage AI for identifying complex fraud and strengthening compliance frameworks. Through real-world examples, like a fintech firm uncovering hidden money laundering with AI, this course shows how generative tools can transform detection strategies. Spanning three progressive modules, it covers AI basics, detection challenges, and advanced anomaly monitoring techniques—ensuring you’re prepared to lead with innovation, ethics, and impact in the financial world.

Skills You Will Gain

Generative AI
Ethical AI
Sequence Modelling
AI governance
Compliance

Learning Outcomes (At the end of this program you will be able to)

  • Demonstrate an understanding of the fundamentals of generative AI and its applications in fraud detection and compliance. 
  • Implement  techniques to develop and utilize generative AI models  in fraud detection and compliance workflows. 
  • Evaluate the role of AI governance in ensuring ethical compliance. 
  • Design  strategies to incorporate generative AI for evolving fraud detection and compliance challenges. 

Prerequisites

Imagine uncovering a major fraud scheme that traditional systems missed. Generative AI for Fraud Detection and Compliance is a practical course that teaches professionals how to use AI to detect complex fraud and strengthen compliance. Through real-world examples and three focused modules, you’ll learn AI fundamentals, explore detection challenges, and apply advanced strategies for monitoring and compliance preparing you to lead ethically and effectively in today’s fast-changing financial landscape.

Who Should Attend

This course is ideal for finance professionals, compliance officers, IT security specialists, data scientists, AI enthusiasts, risk management professionals, and regulatory analysts. It caters to anyone looking to enhance their understanding of how generative AI can be effectively applied to detect fraud, ensure compliance, and manage risk in today’s complex financial environment.

Curriculum

Instructors

Frequently Asked Questions

How much do the courses at Starweaver cost?

We offer flexible payment options to make learning accessible for everyone. With our Pay-As-You-Go plan, you can pay for each course individually. Alternatively, our Subscription-Based plan provides you with unlimited access to all courses for a monthly or yearly fee.

Do you offer any certifications upon completion of a course at Starweaver?

Yes, we do offer a certification upon completion of our course to showcase your newly acquired skills and expertise.

Does Starweaver offer any free courses or trials?

No, we don't offer any free courses, but we do offer 5-day trial only on our subscriptions-based plans.

Are Starweaver's courses designed for beginners or advanced students?

Our course is designed with three levels to cater to your learning needs - Core, Intermediate, and Advanced. You can choose the level that best suits your knowledge and skillset to enhance your learning experience.

What payment options are available for Starweaver courses?

We accept various payment methods such as major credit cards, PayPal, wire transfer, and company purchase orders. For more information related to payments contact customer support.

Do you offer refunds?

Yes, we do offer a 100% refund guarantee for our courses within a specified time frame. If you are not satisfied with the course, contact our customer support team to request a refund with your order details. Some restrictions may apply.

*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
1Module 1: Decoding GenAI and Fraud Detection
2Module 2: Employing Generative AI Techniques in Fraud Detection
3Module 3: Assessing Future Trends in Fraud Detection
Karlis Zars

Karlis Zars

Karlis is a dedicated professional committed to shaping the next generation of software developers. With over seven years of experience, he serves as a JAVA Trainer at Software Development Academy, where he mentors aspiring developers and equips them with the skills needed to thrive in the fast-paced tech industry.

Beyond the classroom, Karlis is deeply involved in cutting-edge research as a PhD student in Computer Science at the University of Latvia. His research focuses on artificial intelligence and machine learning, exploring innovative applications that drive industry advancements.

Karlis began his journey in technology with hands-on experience as a Robotic Process Automation Developer at Rimi Baltic Group, where he designed and implemented automated solutions that transformed business processes. His previous roles as a Developer at ELVA and a Junior Software Developer at D8 Corporation allowed him to hone his expertise in Java, JavaScript, Linux, and Flutter, contributing to his well-rounded understanding of software development.

Throughout his career, Karlis has remained committed to delivering high-quality, user-friendly solutions that address complex challenges. His experience as a System Administrator at Lauku Avīze AS and a Software Tester at Lattelecom helped cultivate a diverse skill set and a keen eye for detail.

Karlis’ academic journey at Latvijas Universitāte, where he is pursuing a Doctor of Philosophy in Computer Science, has further enriched his knowledge and reinforced his commitment to excellence in both academia and industry.

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Segment 05:Analyzing Advanced Fraud Detection with Generative AI Techniques

Segment 09: Implementing Strategies for Ethical Compliance

Segment 10: Evaluating Emerging Trends of Fraud and Compliance

Segment 11: Congratulations and Continuous Learning Journey (1)

Segment 05: Creating Synthetic Data for Fraud Detection

Segment 06: Implementing Generative AI in a Compliance Workflow final

Segment 07: Using Generative AI For Automated Anomaly Detection

Segment 01: Introduction and Welcome

Segment 02: Decoding Principles of GenAI Applications 2

Segment 03: Evaluating Fraud Detection with Generative AI 2

Segment 04: Integrating Generative AI in Compliance