Check Fraud Prevention
We’re pleased to announce that our ORBOIMPACT VIRTUAL CONFERENCE, a two-day online event which covered Healthcare Payments on Thursday, October 29, and Banking & Payments on Friday, October 30, was a huge success! Industry speakers coupled with OrboGraph experts focused on AI innovation and payment strategy helped drive strong attendance, while innovative polling encouraged attendee…
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Hopefully you’ve already registered for the ORBOIMPACT VIRTUAL CONFERENCE scheduled for October 29th and 30th. If not, what are you waiting for?
ORBOIMPACT will explore AI innovation in the fields of check payments, check fraud, and healthcare remittance automation. The event is FREE and is accepting a limited number of virtual attendees , so register today if you haven’t already!
Check out our star-studded lineup of speakers!
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Even as we see our industry create and adopt newer and better, more precise tools for improving check processing and preventing fraud (we proclaimed 2019, remember, the Year of AI and Modernization), it’s important to be aware of how to most effectively integrate new technology the current ecosystem in a manner that maximizes return on investment.
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Predicting an economic recovery in today’s COVID-19 environment is far more complex than reading traditional individual economic indicators. As seen by the recent run in the stock market, there are certain market components somewhat disassociated from traditional indicators, i.e. unemployment rate, GDP growth, etc.
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In a little over a month, OrboGraph will be hosting it’s first virtual conference since 2014: ORBOIMPACT Virtual Conference: AI Innovation for Check Payments, Check Fraud, and Healthcare Remittance Automation.
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Rachel Woolley, global director of Financial Crime at Fenergo, tells FinTech Futures that penalties against financial institutions have come “fast and furious” over the past few years.
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In a summary of Mercator Advisory Group’s new Insight Summary Report, 2020 Small Business PaymentsInsights, COVID-19 and B2B Payments & Cards – The Result of the Pandemic, PaymentsJournal.com summarizes their findings.
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By now, many of you have heard of the arguments between utilize GPU vs CPU. towardsdatascience.com provides a simple explanation on the reasoning behind the need for GPUs for machine learning:
GPUs are optimized for training artificial intelligence and deep learning models as they can process multiple computations simultaneously.
They have a large number of cores, which allows for better computation of multiple parallel processes. Additionally, computations in deep learning need to handle huge amounts of data — this makes a GPU’s memory bandwidth most suitable.
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Pymnts.com explores the various hurdles banks face when taking that big — and increasingly necessary — step. They note that migrating to the cloud is a vital tool traditional financial institutions (FIs’) will need in order to compete with digital-native FinTechs.
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To the layman, much of the language in the AI space can be mystifying, particularly in deep learning. Take for example one of the core elements; the node. A deep learning node is “a computational unit that has one or more weighted input connections, a transfer function that combines the inputs in some way, and an output connection. Nodes are then organized into layers to comprise a network.”
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