Agile technologies key to future-proofing the back office
Global capital markets are advancing at a staggering pace. While increasing regulation has been the major driving force of change in the past decade, rapid technological advances have also contributed to the rewiring of the marketplace. As capital market firms pour time and money into upgrading their capabilities in front office revenue-generating activities, post-trade operations that constitute the backbone of the financial system have often been overlooked.
Post-trade systems continue to be defined by legacy technology and siloed operations that require significant manual intervention, making them a critical source of inefficiency and operational risk. But as revenue streams are challenged by uncertain economics and growing competition, there’s great pressure on post-trade operations to reduce costs, boost margins, and improve return on equity.
Re-architecting post-trade operations is a big task, and not only because of the significant resources required. With ground-breaking innovations being introduced on a nearly daily basis, today’s new technology might be legacy by tomorrow. This further complicates the buying decisions of CTOs at large financial institutions as they need to consider the future evolution in the business, regulatory, and technology environment.
Global research, advisory, and consulting firm Celent has observed a dramatic shift in attitude and approach to operational transformation among capital markets firms in the last 18–24 months. According to Celent, firms are moving away from “big bang” transformation projects—that were a common model until just a few years ago—to a component-based and modular approach, with smart investments to reduce costs and avoid disruption. Seeing a complete overhaul of legacy as too complex and risky, firms are instead replacing smaller pieces that are approaching the end of their lifecycle and integrating these older pieces with new and future-proof technology.
As a result, sell-side firms are increasingly turning to managed services providers who can ensure a rapid deployment of proven products and allow firms to focus their efforts and resources on value-add activities.
Furthermore, the evolution of technology solutions such as cloud, big data, robotic process automation (RPA), artificial intelligence (AI), and machine learning (ML) are proving useful in terms of enhancing, or even replacing, some manual processes. In addition to eliminating the need for manual intervention, these solutions can help improve data management and workflows, as well as managing communication and electronic messaging aspects in post-trade.
However, adopting these new technologies will still require a fundamental re-organisation of workflows across asset classes and the trade lifecycle. Despite efforts to upgrade some of the most inefficient processes, automation in the back-office space remains extremely low across the industry. As highlighted by Celent, many back-office processes in asset classes such as FX, fixed income, and others are still handled manually. Even in core equities, automation levels need to be improved—and error and exception handling processes to be made more efficient—due to disparate times zones and post-trade practices, and reduction in settlement cycles across the globe.
Many banks are still at an early stage of the automation journey in post-trade. They frequently struggle with immediate challenges in data and workflow management, and seamless communication with other systems and counterparties, which limit levels of automation and straight through processing (STP). The key focus for these banks is to modernise their archaic back-office systems with future-proof technology based on the latest standards and frameworks, and increasingly cloud- and AI/ML-based solutions. They also need to simplify the complex patchwork of systems accrued over the years. Additionally, outsourcing technology and operations to expert third-party providers can further help untangle the back-office maze, making post-trade processing even more efficient.