Discussion into possible use cases for deep learning within financial services, particularly in risk and investment management, as well as the challenges that arise from an infrastructure and data storage perspective.
Many middle-office systems at banks and brokers still rely on a mishmash of spreadsheets and legacy systems, some of which have been in need of modernisation for years. How can firms embrace technology to improve efficiency and reduce costs in this area?
This article investigates the increasingly popular development method of DevOps, focusing specifically on what kinds of organisational and cultural changes are involved in a successful transition that will deliver real benefits.
In this article we look at the future of middle-office systems for banks and trading firms. Many of these companies are now relying on hodgepodge solutions, systems that essentially rest upon legacy technology and have been in need of modernisation for years. Meanwhile, as regulatory requirements have increased, demands on middle office systems have risen. […]
In this paper, Dan Barnes and Mike O’Hara of The Realization Group investigate the real-world applications of AI within financial business today, taking use cases from experts in the field and exploring the choices firms need to face in order to overcome hurdles in implementation. Speaking with Rael Cline of MediaGamma, Jonty Field at Quantitative […]