Artificial Intelligence in the financial sector: 13 key challenges of the future

whitePaper | July 31, 2020

The current COVID pandemic has paralyzed large parts of our industry with significant movement limitations, occupancy restrictions, and in some cases complete shutdowns. Now, as the initial threat seems to be subsiding, governments and businesses must determine what is required to get back to some sense of normalcy. The biggest hurdles will be regulatory and/or safety-driven. Although the timelines and requirements for the easing of restrictions vary greatly, there are two common threads: limiting occupancy levels and contact tracing individuals who have tested positive for the virus.

whitePaper | July 15, 2022

Today, the use cases for AI (artificial intelligence) and machine learning are developing at a remarkable pace. We are beginning to see cases where AI is contributing to society through its implementation in systems and services that are in production and consumer-facing. These include the automation of nuanced decisions that until now could only be made by humans, thereby increasing the profitability of corporations, and increasing customer satisfaction through the personalization of services making them tailored for each user. In addition, important discussions have begun on the adverse effects such AI systems have on humans and the resulting ethical issues they can create.

whitePaper | June 2, 2022

Licensing programs are channels where you can buy Power Apps, Power Automate and Power Virtual Agents. You can license Power Apps, Power Automate and Microsoft Power Virtual Agents through Microsoft Volume Licensing (VL), Cloud Solution Provider program (CSP), and/or Web Direct (MOSP) programs. In Volume Licensing, Power Apps and Power Automate are available through:

whitePaper | June 28, 2022

Artificial intelligence (AI) has been accelerating across sectors. It has great potential to benefit society but the technology’s full potential can only be realized if it includes the diversity of the populations it represents throughout every step of its development. With growing concerns about bias, data privacy and lack of representation, it is critical to re-evaluate the way in which AI is both designed and deployed to ensure that all affected stakeholders and communities reap the benefits of the technology, rather than any harm.

whitePaper | September 23, 2022

It’s been several years since organizations began adopting artificial intelligence (AI) to improve their business; few have come close to mastering its existing capabilities. A small number of organizations in our research aim to become AI-driven—a status we define as AI and machine learning underpinning almost everything the enterprise does—by 2025. However, this elite group—who we term “AI leaders”1—as well as the many others looking simply to embed AI more firmly in the enterprise foundations face formidable challenges to achieving their objectives.

whitePaper | December 15, 2019

Artificial Intelligence (AI), and specifically Machine Learning (ML), are being tested in an increasing number of fields, including data-centric environments. Image or text analysis, speech recognition, chatbot interactions, custom machine learning models… all these are elements that could enable the AI journey of a public safety and security organisation. This document dives into different aspects of integrating AI & ML in Public Safety activities, at different levels and in different domains of activity. It presents ethical and regulatory considerations, real examples from Public Safety Answering Points (PSAPs) and Emergency Response Organisations (EROs), and also initiatives that can benefit the public sector greatly, with a series of recommendations at the end.