How MongoDB Provides Strategic Advantage in Financial Services

whitePaper | August 17, 2020

For years, employees drove to an office, opened their computer, logged onto a corporate network with their username and password and got on with their workday. But working standard hours in a fixed office location is becoming more and more rare. In fact, a report by Gallup found that 43 percent of American employees work remotely.1 This growing mobile workforce requires the same, secure access to resources as their onsite counterparts — without connecting to the corporate network. And both onsite and remote employees need secure ways to access the expanding number of applications and resources that are hosted in the cloud. To accommodate, enterprise technology and IT practices must adapt.

whitePaper | January 28, 2022

Since more and more decisions that used to be made by humans are nowadays made either with the help of Artificial Intelligence (AI) or by AI alone, it is essential that the AI algorithms are “fair.” In this whitepaper, we discuss issues surrounding the fairness of AI applications, with a special focus on how it can be assessed independently and subsequently certified. We explain why an AI application cannot be classified – and subsequently certified – as “fair” or “unfair” in a general sense and propose an approach that makes it possible to classify it as “fair” or “unfair” under the (application)-specific definition of fairness.

whitePaper | May 25, 2022

Modernization of data and applications on the mainframe is a necessary priority for modern organizations. Building a MongoDB Operational Data Layer (ODL) is a pattern widely used to make critical mainframe data available for modern mobile and web applications.

whitePaper | December 6, 2022

The impact of system downtimes is rapidly rising due to businesses’ increased dependency on data and technology. It can cause loss of opportunities, productivity loss, confidence erosion, SLA penalties, supply chain ripple effects, and most importantly, a damaged reputation.

whitePaper | December 26, 2022

IBM embraces five foundational pillars of trustworthy AI: Explainability, Fairness, Robustness, Transparency, and Privacy. These pillars underpin the development, deployment and use of AI systems. This document and IBM’s trustworthy AI pillars are meant to help you align on both process and outcomes.

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.