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Bringing AI into the Enterprise:
A Machine Learning Primer
August 2017
 2017 Mercator Advisory Group
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.
New research from Mercator Advisory Group shows how machine
learning, a.k.a. AI, will evolve to alter all aspects of bank operations
 2017 Mercator Advisory Group
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.
AI’s impact on banking will be broader and faster than the impact of
the internet
 2017 Mercator Advisory Group
"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 Technologies 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.”
Tim Sloane
VP Payments Innovation,
tsloane@mercatoradvisorygroup
 2017 Mercator Advisory Group
• Like software, machine learning can be applied to an extremely wide range of
specific problems across all business domains. Although the technology can
be used in a defensive fashion to lower costs, understanding how to use
machine learning in offense to expand business opportunities is far more
important.
• Machine learning is used today to greatly improve fraud detection while
simultaneously reducing false positives, it has changed how consumer
behavior is predicted, and it is fundamental to behavioral biometrics, which is
disrupting the traditional authentication market.
• Perhaps most important, machine learning has changed how consumers
interact with their smartphone and service providers by enabling natural
language interfaces, contextual commerce, and automated agents.
continued
Highlights of the research report:
 2017 Mercator Advisory Group
• Mercator Advisory Group suggests that the most productive and accurate
way to think of machine learning is as a software savant that is “a software
system designed specifically to analyze and act on data and signals within a
specialized domain (as in transactional fraud, detection of emotional state, or
discovering objects or faces in a picture).”
• The cloud infrastructure will be a battleground for machine learning
dominance, demanding an entirely new infrastructure for building, training,
deploying, and managing these new general-purpose platforms.
Highlights of the research report, continued:
 2017 Mercator Advisory Group
One of the 13 exhibits included in this research report:
Figure 11: Establishing a Working Model and Continuing to
Train It Has an Impact on Deployment
© 2017 Mercator Advisory Group
Source: Mercator Advisory Group
Train
Model
Production
Server
Test Data
and
Algorithms
Monitor and
Collect
Training
Data
About the research report:
 2017 Mercator Advisory Group
This research report contains 41 pages and 13 exhibits.
Companies mentioned in this report include: Amazon, Cisco, Clinc, Facebook,
FIS, Google, IBM, Microsoft, OpenAI, Oracle, Salesforce, Slack, Twilio, Unit 4, USAA,
and x.ai.
Members of Mercator Advisory Group’s Emerging Technologies Advisory
Service have access to these reports as well as the upcoming research for the year
ahead, presentations, analyst access, and other membership benefits.
For more information and media inquiries, please call Mercator Advisory Group's main
line: 1-781-419-1700; send email to media@mercatoradvisorygroup.com.
For free industry news, opinions, research, company information and more, visit us at
www.PaymentsJournal.com.
Follow us on Twitter @ http://twitter.com/MercatorAdvisor.
About Mercator Advisory Group
Mercator Advisory Group is the leading independent research and advisory
services firm exclusively focused on the payments and banking industries. We
deliver pragmatic and timely research and advice designed to help our clients
uncover the most lucrative opportunities to maximize revenue growth and
contain costs.
Our clients range from the world's largest payment issuers, acquirers,
processors, merchants and associations to leading technology providers and
investors. Mercator Advisory Group is also the publisher of the online payments
and banking news and information portal PaymentsJournal.com.
 2017 Mercator Advisory Group

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Bringing AI into the Enterprise: A Machine Learning Primer

  • 1. Bringing AI into the Enterprise: A Machine Learning Primer August 2017
  • 2.  2017 Mercator Advisory Group 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. New research from Mercator Advisory Group shows how machine learning, a.k.a. AI, will evolve to alter all aspects of bank operations
  • 3.  2017 Mercator Advisory Group 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. AI’s impact on banking will be broader and faster than the impact of the internet
  • 4.  2017 Mercator Advisory Group "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 Technologies 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.” Tim Sloane VP Payments Innovation, tsloane@mercatoradvisorygroup
  • 5.  2017 Mercator Advisory Group • Like software, machine learning can be applied to an extremely wide range of specific problems across all business domains. Although the technology can be used in a defensive fashion to lower costs, understanding how to use machine learning in offense to expand business opportunities is far more important. • Machine learning is used today to greatly improve fraud detection while simultaneously reducing false positives, it has changed how consumer behavior is predicted, and it is fundamental to behavioral biometrics, which is disrupting the traditional authentication market. • Perhaps most important, machine learning has changed how consumers interact with their smartphone and service providers by enabling natural language interfaces, contextual commerce, and automated agents. continued Highlights of the research report:
  • 6.  2017 Mercator Advisory Group • Mercator Advisory Group suggests that the most productive and accurate way to think of machine learning is as a software savant that is “a software system designed specifically to analyze and act on data and signals within a specialized domain (as in transactional fraud, detection of emotional state, or discovering objects or faces in a picture).” • The cloud infrastructure will be a battleground for machine learning dominance, demanding an entirely new infrastructure for building, training, deploying, and managing these new general-purpose platforms. Highlights of the research report, continued:
  • 7.  2017 Mercator Advisory Group One of the 13 exhibits included in this research report: Figure 11: Establishing a Working Model and Continuing to Train It Has an Impact on Deployment © 2017 Mercator Advisory Group Source: Mercator Advisory Group Train Model Production Server Test Data and Algorithms Monitor and Collect Training Data
  • 8. About the research report:  2017 Mercator Advisory Group This research report contains 41 pages and 13 exhibits. Companies mentioned in this report include: Amazon, Cisco, Clinc, Facebook, FIS, Google, IBM, Microsoft, OpenAI, Oracle, Salesforce, Slack, Twilio, Unit 4, USAA, and x.ai. Members of Mercator Advisory Group’s Emerging Technologies Advisory Service have access to these reports as well as the upcoming research for the year ahead, presentations, analyst access, and other membership benefits. For more information and media inquiries, please call Mercator Advisory Group's main line: 1-781-419-1700; send email to media@mercatoradvisorygroup.com. For free industry news, opinions, research, company information and more, visit us at www.PaymentsJournal.com. Follow us on Twitter @ http://twitter.com/MercatorAdvisor.
  • 9. About Mercator Advisory Group Mercator Advisory Group is the leading independent research and advisory services firm exclusively focused on the payments and banking industries. We deliver pragmatic and timely research and advice designed to help our clients uncover the most lucrative opportunities to maximize revenue growth and contain costs. Our clients range from the world's largest payment issuers, acquirers, processors, merchants and associations to leading technology providers and investors. Mercator Advisory Group is also the publisher of the online payments and banking news and information portal PaymentsJournal.com.  2017 Mercator Advisory Group