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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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The “death knell” for checks has been sending false alarms for a decade; year after year we are told it’s time for checks to fade away, and 2020 is no different. However, the paper check hangs on and remains undeniably popular in spite of the frequency with which it is derided.
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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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Check writers and depositors have become accustomed to a next day or two day check clearing process for the majority of items. But when an extended clearing process does happen, i.e. 2-3 days, it becomes a real inconvenience, especially for millennials accustomed to instant digital payments, or for those folks who still get payroll checks. There are many other examples.
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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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