Artificial intelligence is changing how we're evaluated for loans and credit cards as many lenders use it to evaluate credit worthiness on much more data than your credit history.
That's right. When you apply for a loan, a credit card, or a mortgage, many lenders are using artificial intelligence to evaluate your credit worthiness on much more data than your credit history.
The Federal Reserve Consumer Compliance Outlook reports lenders can also use AI to gather what's called Big Data or Fringe Data, often from social media platforms, like your browsing history, shopping habits, occupation, education, as well as the places you visit that are tracked by your cell phone. FOX 26 Houston is now on the FOX LOCAL app available through Apple TV, Amazon FireTV, Roku and Google Android TV!
Österreich Neuesten Nachrichten, Österreich Schlagzeilen
Similar News:Sie können auch ähnliche Nachrichten wie diese lesen, die wir aus anderen Nachrichtenquellen gesammelt haben.
Artificial Intelligence Could Finally Let Us Talk with AnimalsAI is poised to revolutionize our understanding of animal communication
Weiterlesen »
Artificial Intelligence May Be Humanity’s Most Ingenious Invention—And Its Last?Silicon Valley is barreling ahead with AI technology that could unlock novel forms of creativity, art, and medicine, and potentially, wipe out all mankind. As one AI engineer warns, “We’re creating God.”
Weiterlesen »
The UN's top tech official discusses AI, bringing the world together and what keeps him up at nightThis fall, the United Nations is to convene an advisory group on artificial intelligence.
Weiterlesen »
The UN's top tech official discusses AI, bringing the world together and what keeps him up at nightThis fall, the United Nations is to convene an advisory group on artificial intelligence.
Weiterlesen »
Efficient training for artificial intelligenceNew physics-based self-learning machines could replace the current artificial neural networks and save energy.
Weiterlesen »
Images of simulated cities help artificial intelligence to understand real streetscapesTo address the lack of suitable training data for deep-learning semantic segmentation models in urban landscaping, researchers developed a method that generates a training dataset without the need for real images or a model of an existing city. The method, which is based on procedural modelling and image-to-image techniques, enables segmentation models to achieve comparable performance under some conditions at a fraction of the cost of real dataset generation.
Weiterlesen »