How to Choose a Machine Learning Platform to Detect and Prevent Financial Crime

We get it. Banks and financial institutions (FIs) constantly face a tough balancing act. On the one hand, your FI’s top priority is to deliver a top-notch customer experience. At the same time, you can’t afford to let fraudsters blend in among legitimate customers and use your platform to commit financial crimes – exposing your institution to financial losses, regulatory oversight, and reputational harm.
 

At this point, you realize that machine learning is the key to both delivering seamless customer experiences and stopping financial crime, including fraud and money laundering activities. So where do you go from here? Especially when there are so many machine learning solutions to choose from.
 

Choosing the right machine learning solution for your FI can feel intimidating. But the good news is you don’t have to do it alone. This guide is designed to help make the machine learning selection process easier for you by outlining the questions you should ask a vendor, red flags to watch for, how to ensure the system makes fair and ethical decisions, and more.
 

Download the full whitepaper to learn how to make your machine learning selection as informed as possible.
 

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Every year, Feedzai’s risk management platform scores trillions of dollars of transactions to protect the world’s largest companies. Fully AI-enabled to stay ahead of emerging financial crime and money laundering patterns, Feedzai mitigates even the most deceptive criminals so that banks, issuers, acquirers, and merchants can focus on growth.

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