Bringing AI into the Enterprise: A Machine Learning Primer
|発行||Mercator Advisory Group, Inc.||商品コード||545435|
|出版日||ページ情報||英文 41 Pages
|銀行へのAIの導入：機械学習の手引き Bringing AI into the Enterprise: A Machine Learning Primer|
|出版日: 2017年08月21日||ページ情報: 英文 41 Pages||
AI's impact on banking will be broader and faster than the impact of the internet.
New research from Mercator Advisory Group shows how machine learning, a.k.a. AI, has changed consumer behavior and expectations and will evolve to alter all aspects of bank operations.
A new research report from Mercator Advisory Group titled Bringing AI into the Enterprise: A Machine Learning Primer provides an analysis of the impact machine learning will have on bank operations and payments and how it is already shifting consumer behavior. Consumers increasingly expect their smartphone will answer their questions, give them directions, and warn them when accidents will slow them down. Over time, machine learning will become as prevalent within banks as software systems are today. Eventually every software application will be reconstructed to accommodate machine learning - it's simply a matter of time.
This report provides an analysis of the current state of machine learning with a deep dive into existing technologies and breakthroughs that represent new deployment opportunities, such as deep learning, adversarial networks, and transfer learning. The report identifies the incredible breadth of business processes that are impacted by machine learning and recommends areas that should be targeted first. It recommends an approach to enterprise deployment and identifies the important differences between deploying a machine learning solution and deploying traditional software and provides recommendations that will prevent silos of machine learning that would limit the ability of machine learning tools to collaborate.
"The impact of machine learning on the enterprise is breathtaking. It is lowering costs, creating amazing new market opportunities for those willing to innovate, and altering the ways in which consumers behave. As consumers become familiar with an environment that responds to their needs, they will increasingly expect their service providers (including their financial services providers) to become more proactive. Authentication and fraud management have already been affected by machine learning and can save the institution several basis points in fraud costs. But financial institutions should evaluate the impact of machine learning much more broadly," commented Tim Sloane, Vice President of Payments Innovation and Director of Mercator Advisory Group's Emerging Technology Advisory Service, who is the author of the report. "It took software decades to escape the water-cooled computer room, but the evolution of machine learning will be much faster. Mobile phones and cloud computing will enable machine learning to impact a much broader range of processes in a much shorter time, and even computing hardware and the cloud itself will feel the impact."
Companies mentioned are: Amazon, Cisco, Clinc, Facebook, FIS, Google, IBM, Microsoft, OpenAI, Oracle, Salesforce, Slack, Twilio, Unit 4, USAA, and x.ai.