New market entrants are shifting the way the financial sector operates, new business models are changing customer expectations, and ever-changing client demographics are forcing businesses to adapt the way they work.
As we move into a decade of artificial intelligence (AI) and digital innovation, huge opportunities are opening up for the financial sector to combat these changes. But with this comes new challenges, and exponential increases in available information must be accompanied by smart tools and processes to make sense of it, ensure regulatory compliance, and add real value to clients.
To find out more, download this ebook!
Omnichannel isn’t just another buzzword you can ignore. In fact, today’s most successful marketing strategies all take an omnichannel track that puts customers at the center of a diverse network of interactions and engagements.
In this white paper, you’ll learn:
• How email can serve as the foundation of your omnichannel strategy
• How Artificial intelligence marketing (AIM) can make it possible to not only achieve true 1:1 personalization, but also scale it
• How to apply a step-by-step roadmap to your brand’s pursuit of omnichannel excellence
NICE, the leader in workforce management, introduces the most advanced forecasting
tools on the market with WFM 7.0. Building on its recognition as the industry standard,
NICE WFM 7.0 Forecasting with Artificial Intelligence chooses the optimal daily forecast
model to provide staffing levels and budgeting that are more accurate than those
delivered by any other WFM solution.
NICE WFM 7.0’s Forecaster unlocks a high level of transparency into interaction history, allowing you to centrally forecast, schedule and manage contacts between multiple locations and ensure that site- and enterpriselevel objectives are met. With more than two thousand customers and two million users depending on its unparalleled ability to fine-tune the most precise forecasts, Forecaster allows you to plan and respond to the peaks and valleys of customer history through automatic collection of key historical data from all types of contact sources:
• Automatic call distributors (ACDs)
• Outbound dialers • Multi-channel routing platforms
• Back-office employee desktops
Download today to learn more.
Robots play a major role in making manufacturing processes more efficient and
less labor intensive. They can help control costs and improve quality, as well as
increase productivity. The complexity of robotic system design, however, creates
obstacles for many manufacturers, and this is made more difficult by the need to
identify and integrate subsystems from multiple vendors.
NexCOBOT, a NEXCOM company, offers a flexible, modular robotics solution
integrating artificial intelligence (AI) with machine vision and powered by the
new Intel® Vision Accelerator Design products. The solution brings together
the insight of artificial intelligence, the mobility of robotics, and the capabilities
of machine vision, providing a new level of precision and optimization for
manufacturing and industrial implementations
Did you know that organizations with advanced finance teams are more likely to have a compelling digital customer experience? The driver behind this trend? A digital, customer-first way of working with greater investment in talent, innovation, and advanced technologies such as artificial intelligence (AI) and machine learning (ML).
While finance has long taken advantage of technology to help drive productivity and collaboration, the goalposts have recently moved. Today’s organizations must adopt an agile finance operating model— powered by emerging digital technologies and skillsets—to better support the demands of an economy driven by continuous innovation.
Published By: CheckMarx
Published Date: Jun 07, 2019
Artificial Intelligence (AI) software is everywhere being leveraged by many industries such as healthcare, fintech, and e-commerce. But how does AI impact the security space? Join Maty Siman, Checkmarx Founder and CTO, to get both a white hat and black hat perspective to AI and security.
In our recent report, we look into the reasons why HR feel less than confident in their ability to manage the volume of data securely and ethically.
From extracting the right type of insights to improving employee productivity and engagement to managing the skills pipeline.
We look forwards to how HR can improve their systems by using automated technologies such as artificial intelligence and machine learning.
Read the survey today to see how your organisation compares to your peers.
Published By: DataCore
Published Date: Apr 23, 2019
The emphasis on fast flash technology concentrates much attention on hot, frequently accessed data. However, budget pressures preclude consuming such premium-priced capacity when the access frequency diminishes. Yet many organizations do just that, unable to migrate effectively to lower cost secondary storage on a regular basis.
In this white paper, explore:
• How the relative proportion of hot, warm, and cooler data changes over time
• New machine learning (ML) techniques that sense the cooling temperature of data throughout its half-life
• The role of artificial intelligence (AI) in migrating data to the most cost-effective tier.
Published By: Infosys
Published Date: Jun 14, 2019
Cloud along with other technologies such as Big Data, Internet of Things, Artificial Intelligence and Blockchain have made it possible for enterprises to have bolder visions for the future. The new technologies motivate them to accelerate tier digital transformation journey and deliver more rewarding experiences to clients.
Published By: FICO EMEA
Published Date: May 31, 2019
: FICO commissioned an independent research study by TM Forum to look at how global telecommunication providers are using (and plan to use) machine learning and advanced analytics to improve the customer experience in credit risk and beyond. This in-depth report includes key insights from a global survey as well as executive interviews with leading communication service providers such as Telstra, Vodafone, Sky, Globe Telecom, and BT on their vision for leveraging artificial intelligence to stop fraud, better engage customers across channels, improve risk management, and drive collection results.
Read this report to understand:
o What CSPs see as the biggest drivers for deploying advanced analytics over the next two years
o How and where BT, Globe Telecom, Vodafone UK, Sky and Telstra are using analytics, from marketing through origination
o The opportunities and pitfalls around financing devices as opposed to or in addition to subsidising them
o The scope for analytics to improve c
With more data to analyze than ever before, companies are finding new ways to quickly find meaning in their data with artificial intelligence (AI). Natural Language Generation (NLG) technologies deployed on Amazon Web Services (AWS) can enable organizations to free their employees from manual data analysis and interpretation tasks. NLG transforms data into easy-to-understand, data-driven narratives with context and relevance.
Many business leaders know that Artificial Intelligence (AI) and Machine Learning (ML) are critical to their future but don’t know where to start. Those who do have an AI/ML strategy struggle to find qualified data scientists; and once they find them, even advanced data scientists need a lot of time—even months—to build and deploy ML models. These challenges put significant limits on the range and number of problems a business can solve.
In this webinar, learn how H2O Driverless AI on Amazon Web Services (AWS) automates the best practices of leading data scientists to create advanced machine learning models automatically. With these production-ready models, relative newcomers to AI/ML can generate reliable results and scale-up AI programs that anticipate and capitalize on trends, optimize supply chains, understand customer demand, match consumers with goods and services, and much more.
Download our webinar to learn
Implement ML successfully with minimal data science expertise.
Common daily media broadcaster tasks such as ad verification are slow and costly. Done manually, they may also introduce inefficiencies that can interfere with transparency and payment accountability—and impact your bottom line. Meanwhile, recent and archived media lies idle when you could repurpose it to increase brand exposure and generate revenue.
Learn how Veritone, Inc. used its aiWARE Operating System, building on Amazon Web Services (AWS), to help Westwood One, Inc., a large audio broadcasting network in the United States, develop Artificial Intelligence (AI) and Machine Learning (ML) solutions designed for ad verification and monetizing archived media.
Download our webinar to learn how you can
Automate ad verification and reporting tasks.
Enhance archive content to make media searchable and reusable.
Use AI and ML in the cloud for near real-time media intelligence.
Start applying machine learning tools.
Defense and intelligence agencies want to leverage the data they collect so they can use artificial intelligence to enhance readiness – but most who run these programs don’t know how to get started and find it difficult to make the business case to their leadership. In this research report, created by GovLoop in partnership with IBM, which provides innovative technology solutions for national security and military intelligence, you’re going to learn where your peers stand—and some practical tips on how to get started—even if you think your data is “dirty” or not ready for advanced applications.
Knowledge workers today have a rich portfolio of team collaboration tools to help them get their jobs done, starting with email and encompassing texting, file sharing, online chat and message boards, social media and video conferencing. Yet collaboration across these tools can be a frustrating experience, due to the complexity of the technology and lack of integration. The good news: the application of emerging technologies and artificial intelligence (AI) enables more people to connect when and how they need to. And that makes for more productive teams.
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
As digital business evolves, however, we’re finding that the best form of security and enablement will likely remove any real responsibility from users. They will not be required to carry tokens, recall passwords or execute on any security routines. Leveraging machine learning, artificial intelligence, device identity and other technologies will make security stronger, yet far more transparent. From a security standpoint, this will lead to better outcomes for enterprises in terms of breach prevention and data protection. Just as important, however, it will enable authorized users in new ways. They will be able to access the networks, data and collaboration tools they need without friction, saving time and frustration. More time drives increased employee productivity and frictionless access to critical data leads to business agility. Leveraging cloud, mobile and Internet of Things (IoT) infrastructures, enterprises will be able to transform key metrics such as productivity, profitabilit
Global corporate enterprise AI practitioners are clearly still dealing with infrastructure issues related to talent and technology. End-to-end processes remain stubbornly carbon-based. Rule-based automation is truly not yet globally scaled across the majority of organizations.
Double the AI
And yet, the AI & Intelligent Automation Network members went from 21%, having deployed Intelligent Enterprise solutions to over 44% in just one year’s time.
Over 4/5 expect to deploy AI in under two years
The stated goal for deployment is just under 83% by the end of 2020. Considering the fact that they’ve essentially got two years, and those ranks have doubled in one year – doubling again in two years is achievable. Incidentally, that same number was only 67% a year ago.
50% expect to be established, globally scaling or refining AI in under two years
Global corporate enterprise is in fact slowly but surely transforming into the intelligent enterprise of tomorrow. Having said that, it will be
Who among us has not recoiled before the horror of a terrible
Interactive Voice Response (IVR) experience? IVR technology was
created to save businesses money, but it has mutated into a timesucking,
customer experience-crushing monster!
If connecting with a customer in this day of customer experience is
the goal, there’s a better way! Contain the IVR before it kills another
customer relationship. Can we bring the technology to heel and
bend it to our will? And can we stop its rampage before artificial
intelligence makes it too powerful to be stopped?
Published By: Lenovo UK
Published Date: Mar 14, 2019
In today’s workplace, work happens where we are, not where we go. To support this you need the four pillars of dynamic IT
Download this infographic to find out how Lenovo can help you deliver the dynamic IT your workforce requires.
Published By: Lenovo UK
Published Date: Mar 14, 2019
Lenovo commissioned Cebr to research the changing dynamics of workplaces around
the UK. The report quantifies the potential gains from remote working and looks at
issues such as: What attributes do people at the start of their careers look for in an
employer? Will there be a continued shift towards remote working? And how much
importance do people place on flexible working hours?
"Managing infrastructure has always brought with it frustration, headaches and wasted time. That’s because IT professionals have to spend their days, nights and weekends dealing with problems that are
disruptive to their applications and organization and manually tune their infrastructure. And, the challenges increase as the number of applications and reliance on infrastructure continues to grow.
Luckily, there is a better way. HPE InfoSight is artificial intelligence (AI) that predicts and prevents problems across the infrastructure stack and ensures optimal performance and efficient resource use.
Discover how HPE is responding to the massive growth in enterprise data with intelligent storage. Data helps enterprises find new ways to reach and serve customers to grow profitability, but only when it is available at the right place and the right time. The growing complexity of managing and securing data prevents businesses from gaining its full value. Hewlett Packard Enterprise delivers the world’s most intelligent storage for the hybrid cloud world by providing storage that is driven by artificial intelligence, built for the cloud, and delivered as a service.
Managing infrastructure has always brought frustration, headaches, and wasted time. That’s because IT professionals have to spend their days, nights, and weekends dealing with problems and manually tuning their infrastructure.
Traditional monitoring and support are too far removed from infrastructure, resulting in an endless cycle of break-fix-tune-repeat. Infrastructure powered by artificial intelligence, however, can overcome the limitations of humans and traditional tools.
This white paper explores how HPE InfoSight with its recommendation engine paves the path for an autonomous data center your Hybrid Cloud World.