Simility has developed a fraud prevention solution to solve the constantly mutating problem that plagues today’s evolving digital businesses for developers, analysts, product managers and business managers across industries like Banking, Payments, FinTech, Marketplaces, and E-commerce using advanced artificial intelligence that can be quickly adapted to specific scenarios.
Fraud Mutates – Detect, Understand and Block It
Fraudsters are conjuring up new techniques to compromise systems, and today’s digital businesses are constantly evolving. In this environment of change, you need a fraud prevention solution that can effectively adapt to both the changing and evolving threat vectors as well as take into account the evolving business scenarios.
In this session, we will demonstrate how a combination of flexible data ingestion and signal analysis bolstered by advanced machine learning models in combination of human analysis can provide an adaptive fraud prevention solution.
What You’ll Learn
- Understand fraud trends in your business.
- How to do feature engineering and build real-time fraud detection pipelines. Leverage Simility’s rich ML model library or build your own.
- Using Simility’s platform to prevent fraud across issues like account takeover, new account origination, wire transfer, money laundering and overall user risk.
Kedar Samant, CTO & Co-Founder
As CTO of Simility, Kedar Samant and his co-founders are leveraging their experience and artificial intelligence to build a platform that adapts to mutating fraud. Prior to this, Kedar was Sr. Manager of Google’s Fraud, Trust and Safety team, where his team developed a sophisticated, scalable and flexible fraud prevention platform.
Ravi Sandepudi, Head of Engineering
At Simility, Ravi manages engineering. His specific interests lie in device and user behavior analytics. Ravi was a lead engineer at Google’s Trust and Safety team where he built a large scale offline click fraud detection/prevention system and log analysis.