Artificial Intelligence & Machine Learning
31 white papers and resources
Artificial Intelligence & Machine Learning
AI and Observational Learning: Resetting the Rules of Data Reconciliation
This whitepaper looks at how AI-driven observational learning techniques can improve accuracy and efficiency in your data reconciliations. No longer will AI need to be programmed to manage specific tasks on large, complex datasets – this ground-breaking technology observes, learns and improves on…
Managed Services in 2021: Poised for Lift-Off
This research report sheds greater light on current and future outsourcing trends that are likely to shape the capital markets including why cost reduction and efficiencies aren’t the only reasons for outsourcing and how cloud will become integral to managed services business model
The Total Economic Impact™ Of IBM OpenPages With Watson
IBM recently commissioned Forrester Consulting to conduct the Total Economic Impact (TEI) study that evaluated the financial impact of IBM OpenPages with Watson on organizations. Learn how IBM OpenPages with Watson, an AI-driven integrated GRC platform, can cut license and implementation costs and…
Machine Learning Model Governance
Machine learning (ML) models need governance just like other models, only more so. This is particularly true of ML models designed to improve automatically through experience. Their ability to “learn” not only enables greater accuracy and predictability, but can also greatly increase model risk and…
The Pulse of the Industry
This research report is based on the results of a survey on the future of data and technology across capital markets.
EDM client case study: Managing SRI-ESG data
This case study reveals how Mirabaud Asset Management is using IHS Markit’s Enterprise Data Management (EDM) platform to establish a strong foundation for the its long-term SRI-ESG (socially-responsible / environmental, social and governance investing) strategy. This includes empowering Mirabaud’s…
Data Management Trends That Can Mean The Difference Between Success and Failure
This paper explores some of the most important changes in AI and data management. Discover what these trends mean to your organization and how you can leverage them to your benefit.
AI & Risk Management: enabling factors, use cases and future challenges
This white paper examines the roots of the combination between AI and Risk Management, the main application fields nowadays and the future challenges.
Digital & data for the new normal
In this session, Paul Lewis, Global Chief Technology Officer at Hitachi discussed the top concerns and shifted priorities for CIOs and Technology leaders: how can they lead the IT transformation under the new normal? How to elevate data to be a value creator, which still be able to accommodate…
Building Artificial Intelligence in Credit Risk: A Commercial Lending Perspective
This whitepaper, drawing on recent academic evidence and business insights, provides a contemporary look at what AI and ML adoption could mean for commercial lending and credit risk assessments while also proposing different approaches to AI and ML adoption tailored to each step of the commercial…