APFIC 2017: Testing, Testing… Firms Employ Trial and Error, AI to Identify Data Value for Analytics
Refining and cleaning data may be time-consuming, but is essential to helping financial institutions perform better analysis on data, panelists in Hong Kong said. Wei-Shen Wong reports.
“The challenge is that you don’t know which data is going to provide the value until you get exposed to the data and have a chance to try it. And that’s a challenge because we need to work with vendors that can provide us with data that we can start to use and see if it’s going to make sense to us. And if it does make sense, we will want to use that and start production of it. But without testing it you don’t really know for sure,” said John Pies, customer insights and analytics director for Asi
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Waters Wavelength Podcast Episode 117: Machine Learning, Chatbots & Fintechs
Anthony and James examine some of the key themes that will be on display at the inaugural North American Innovation Summit.
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