Hear from 4 CEOs about ACH fraud, how it has changed, and how to stop it. This video is part of the Finnovation Online Series by Sila.

Laura Spiekerman, Co-Founder & Chief Revenue Officer, Alloy
Eli Polanco, Founder & CEO, Nivelo
Ohad Samet, Co-Founder & CEO, True Accord and Author of “Introduction to Online Payments Risk Management”
Shamir Karkal, Co-Founder & CEO, Sila

Goal:
Learn the tools, patterns, techniques, and technologies employed by fintech by fintech experts to detect and reduce fraud.

Topics:

Fintech Fraud Prevention 101: What are the most common fraud tactics and what best practices should companies have in place in their organization?

Anti-Fraud Metrics: What are the KPIs and benchmarks for implementing a robust anti-fraud program for a Fintech Startup Vs. Fintech at Scale.

Humans Vs. Bots: What roles are required to support a technology-led anti-fraud program.

User Experience: How do you tune User Experience with Anti-Fraud requirements to maximize registration and usability.

SEON offers fraud prevention based on three key principles: better data, real-time monitoring, and Machine Learning intelligence. See how it can help your business today.

Want to learn more about SEON?
https://seon.io/

Wanna see how SEON can help your business reduce fraud?

Try it for FREE here:
https://seon.io/try-for-free/

Prefer a snappy tailored demo?
https://seon.io/get-a-demo/

Find SEON on:

• Facebook: https://www.facebook.com/SEON.FraudFighters
• LinkedIn: https://linkedin.com/company/seon-tech
• Twitter: https://twitter.com/seon_tech
• Github: https://github.com/seontechnologies
• TikTok: https://www.tiktok.com/@seon.fraudfighters

Can AI be used for fraud prevention? Yes! In this video, we’ll go over the history of fraud prevention techniques, then talk about some recent AI startups that are helping business reduce credit card fraud. We’ll break down what the different AI models that help with fraud prevention look like (decision trees, logistic regression, neural networks) and finally, we’ll try it out on a transaction dataset.

Code for this video:
https://github.com/llSourcell/AI_for_Financial_Data

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More learning resources:
https://medium.com/mlreview/a-simple-deep-learning-model-for-stock-price-prediction-using-tensorflow-30505541d877
https://www.youtube.com/watch?v=GlV_QO5B2eU
https://cloud.google.com/solutions/machine-learning-with-financial-time-series-data
https://pythonprogramming.net/python-programming-finance-machine-learning-framework/
https://gist.github.com/yhilpisch/648565d3d5d70663b7dc418db1b81676
https://www.quantopian.com/posts/simple-machine-learning-example

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