Building Fair AI for Fraud Detection & Marketplace Safety

Hosted by Mahesh Yadav and Madhumita Mantri

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618 students

What you'll learn

Enhancing Fraud Detection with AI

Using prompt engineering and synthetic data generation to enhance fraud detection without compromising user security

Building trust with transparent AI explanations

Providing clear explanations of how the AI identifies fraudulent listings, reducing "black-box" decision making.

Ensuring Fariness with Unbiased AI models

Developing AI models that are unbiased and avoid discriminatory outcomes, ensuring equitable protection for all users.

Why this topic matters

Fraud poses a serious threat to marketplace trust, harming users and businesses while eroding confidence in digital platforms. By leveraging responsible generative AI, we can enhance safety, promote fairness, and ensure transparency in fraud detection, fostering a secure and equitable environment for all stakeholders.

You'll learn from

Mahesh Yadav

GenAI Product Lead at Google, Ex-Meta, Ex-Amazon & Ex-Microsoft l AI PM Mentor

Mahesh has 20 years of experience in building products at Meta, Microsoft and AWS AI teams. Mahesh has worked in all layers of the AI stack from AI chips to LLM and has a deep understanding of how GenAI companies ship value to customers. His work on AI has been featured in the Nvidia GTC conference, Microsoft Build, and Meta blogs.


His mentorship has helped various students in building Real time products & Career in GenAI PM.

Madhumita Mantri

Staff Product Manager@Walmart Marketplace | Paypal | Linkedin l Yahoo

Madhumita is a seasoned Staff Product Manager at Walmart Marketplace, With over 20 years of experience in technology and 7+ years in product management, Madhumita has built her own GenAI Products which are of crucial value in Marketplace security domain.

She is passionate about product innovation, strategy execution, and solving complex problems. Madhumita is also a Product Management Coach, guiding others with her extensive expertise.

Worked with

Google
Meta
Amazon Web Services
Microsoft
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