D E F E N D

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Virtual Event Series for Risk and Fraud Leaders

Why Join us?

In this session, we will host expert practitioners, Carolina Rincon. Sr. Product Manager, OLX , Mark Leung, Director of Trust and Safety at Letgo and Hao Li, Head of Customer Success at DataVisor to discuss how trust and safety is changing for online marketplaces and ecommerce platforms as the world moves increasingly digital in the post-covid era.

Panelists 

About DataVisor

DataVisor is the leading fraud and risk management platform powered by transformational AI technology. Using proprietary machine learning algorithms, DataVisor restores trust in digital commerce by enabling organizations to proactively detect and act on fast-evolving fraud patterns, and prevent future attacks before they happen. Combining advanced analytics and an intelligence network of more than 4B global user accounts, DataVisor protects against financial losses and reputational damage across a variety of industries, including financial services, insurance, marketplaces, ecommerce, and internet platforms.

OLX Group

Expert Guidance From

Expert Guidance

Hao LI, Head of customer Success, DataVisor
Priya Rajan, VP Marketing, DataVisor

VP of Marketing

PRIYA RAJAN

HAO LI

Head of Customer Success & Support

DataVisor

DataVisor

WATCH ON-DEMAND

All-Star Fraud Fighters: Learn how these leaders are keeping up with fraud in the new normal

Carolina Rincon
Sr. Product Manager @ OLX Group

CAROLINA RINCON

Sr. Product Manager

OLX Group

WATCH NOW
Mark Leung, Director of Trust and Safety, Letgo

Letgo

Director of Trust and Safety

MARK LEUNG

JOIN THE CONVERSATION

Hear from these frontline leaders on the new fraud patterns they are seeing in the post-covid world  and how they are adapting to these changes

Actionable Tips

Learn common pitfalls with adopting machine learning for fraud prevention and how you can overcome them

Common solution methodologies 

Learn how you can leverage technology to accelerate detection, improve investigation and stay ahead of emerging attacks.