Banking's One-to-One Future is Finally Possible


Almost a quarter century ago, a book was written about how organizations would focus on share of customer as opposed to share of market, building a personalized collaboration driven by big data. Instead of watching as non-banking organizations or fintech start-ups set expectations, the banking industry can now offer individualized engagement, integrating advanced analytics, artificial intelligence, machine learning, robotics and even blockchains to build a cognitive bank. The banking industry continues to be challenged be a low interest rate environment, intense competition from new market entrants, and heightened consumer experience expectations set by highly digital non-bank organizations. It is also proposed that cognitive systems can continually build knowledge and learning, providing the insight needed to increase efficiency and effectiveness throughout the organization.

Google and other tech giants grapple with the ethical concerns raised by the AI boom


Companies in the vanguard of developing and deploying machine learning and AI are now starting to talk openly about ethical challenges raised by their increasingly smart creations. "We're here at an inflection point for AI," said Eric Horvitz, managing director of Microsoft Research, at MIT Technology Review's EmTech conference this week. Maya Gupta, a researcher at Google, called for the industry to work harder on developing processes to ensure data used to train algorithms isn't skewed. In the past year, many efforts to research the ethical challenges of machine learning and AI have sprung up in academia and industry.