AI Best Practices to Improve Enterprise Risk Outcomes
As fraud grows in complexity and the payments landscape evolves, organizations need to stay informed to make the right decisions and successfully navigate a digitally-transformed world.
Listen in as Richard Harris, SVP at Feedzai, discusses big data and real-time processing with The Paypers and Aite Group to enable organizations to mitigate risk, improve their reputations, and achieve their goals.
How do I bring all of that data from a transactional point of view, from a behavioral analytics point of view in terms of login and usage of mobile and device and biometric data that’s coming in? And how do I do that across the different problem areas within the banks, and how do I do that to deal with fraud across different payment channels? How do I do that to manage financial crime challenges, anti-money laundering challenges, whether that’s in specific movement of payments or whether it’s in the setting up of accounts and provision of mule accounts? And how do I actually do ongoing monitoring across the institution as well?
So bringing all those different streams of data together and really doing that on a platform that allows you to do that in a real-time way. Because that’s really the change with the entire payments landscape globally, moving towards money moving much faster in most cases around the world, as you showed in that fantastic slide around faster payments. Increasingly this is a real-time issue. You don’t have the opportunity to do this on a batch basis and check things once every 24 hours. You have to do this on a payment-by-payment level, and that really requires you to build a completely different architecture of software system to deal with the data involved.
Want to see more? Watch the full webinar.
Latest posts by Ken Bui (see all)
- EU Fifth AML Directive: How Banks Can Prepare for Five Key Changes - November 18, 2019
- AI Best Practices to Improve Enterprise Risk Outcomes - October 22, 2019
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