Disruptions to global supply chains and labor markets are bringing digital transformation to the retail space at breathtaking speed. Retailers with solid digital foundations are turning these challenges into opportunities to delight customers and make shopping fun.
As an on-going celebration of growth, innovation, and acceleration across the finance industry, this year’s Money Management Institute Summit focused on The Value-Add Imperative — how financial service providers can go beyond their traditional services to positively impact the lives of their customers. In this time of COVID-19 Summit’s core goal of empowering attendees with
Companies across the Financial Sector are using AI and Machine Learning to model customer behaviors, avoid risk, and streamline critical business processes. Consequently, building and testing Machine Learning models has become an important discipline for many financial institutions. Traditionally, the success of Machine Learning models, and often AI algorithms, is measured by key metrics that
Whether they’re self-selected, HR mandated, passed on by old leadership or insisted on by the CIO, the tools we use every day shape our productivity. As financial service firms big and small actively search for balance in a COVID-19 environment, it’s become more important than ever that those resources are accessible, integrated, and cloud-connected if
As I work with customers across the US, I hear that many find the “promise of AI” to be somewhat overwhelming, with a variety of questions about where to start. In reality, the majority of SaaS offerings that we offer at Microsoft already include some AI capabilities, and the Azure platform has a wide variety of options available to analyze images, comprehend speech, interact with data in natural ways, and
David Koscheski | Director of Industry, Banking Ten years ago, it would have been tough to imagine today’s banking landscape. With rapidly evolving technological innovations and changing customer expectations, competition from fintech, Big Tech, and smaller, niche institutions has turned up the heat on the industry as a whole. The future is here, but many
Many insurers are realizing a need for transitioning their call centers to operate under remote work models. The technological challenges associated with this type of undertaking are compounded by the need to drive those workloads under compressed timelines. Fortunately, this evolution can be managed quickly and with the equivalent security, agent experience, and customer experience
As Artificial Intelligence and Machine Learning continue to cement themselves as foundational resources for growth and transformation across the financial services industry, organizations must account for the added influx of data flooding into their enterprises. Every data science achievement must also account for how we secure and protect that data, making embedded data security risk management a far more pronounced need
Recently at Adobe Summit Valerie Beaulieu gave a breakout session highlighting Microsoft’s journey to become a marketing leader in the digital landscape we all live in today. Below are 5 key learnings Valerie uses to frame the Microsoft story. If you’d like to learn more download the eBook How to demystify data and extract impactful
It would be an understatement to say that the COVID-19 pandemic has changed our lives, both personally and professionally. All of us are having to adjust to working remotely, while deploying new technologies to address COVID-19, as we collectively work to protect the health of all Americans. Government employees across states, cities, and counties are
Today, more than ever, we recognize the need for secure technology that can support our government leaders in responding quickly, and with agility, to rapid changes in the global landscape. At Microsoft we are committed to developing solutions that enable our government stakeholders to capitalize on opportunities at the accelerated pace required to deliver modern
Financial institutions are finding it difficult to insert AI into their financial risk products at scale. Financial institutions have been hiring data scientists, acquiring technology, doing POCs, in short, playing around with AI. While they understand it in theory, and may even put an AI project into production, getting it to run scale is another
As we enter the new decade, one thing is clear: the explosive growth of data science and AI has made the effective application of them a critical differentiator for any enterprise. Despite the near-universal acknowledgement of this phenomenon and the major investments being made, many enterprises struggle to deliver sustained value on their data science
