Having worked in fixed income markets for over 20 years, I often found that answering what should have been fairly simple business questions around clients, flows and market conditions were far more problematic than it needed to be. When technology was fundamentally changing many other facets of my life, why could I still not immediately answer basic questions such as ‘who is more likely to buy this security’, ‘what flows have I seen from a particular client or jurisdiction’ or ‘is my hit ratio with this account getting better or worse?’ Eventually I realised that there were a multitude of reasons for this including general pressure on business margins and revenues, sustained pressure on IT resources, institutional resistance to change as well as a general lack of awareness of the advances in data analytics in other fields.
At CurveCue we have a range of skill sets from across industries, from a deep knowledge of fixed income markets and structures, a thorough understanding of bank IT infrastructure through to expertise on the latest in DevOps and automated deployment technologies from the technology sector. We also have access to established practitioners familiar with the latest in AI, machine learning and semantic search. Put these skills together and our clients have the ability to produce highly effective solutions, customised to their unique data sets and business needs.
Until fairly recently, advanced technology on the trading floor meant exotic trading models and more advanced trading platforms. Going forward, technology will fundamentally reshape internal business processes by transforming decision making and analysis. Machine learning and data analytics will vastly improve market practitioners’ ability to serve their clients more effectively. A joint Pwc/AFME research piece noted that 95% of survey respondents rated the potential for new technologies to reduce costs and inefficiency as the primary business driver for their adoption and 84% of respondents expected banks to have significantly advanced data and analytics capabilities embedded in 5 years time.[1]
Banks are currently at different levels of maturity in terms of their data capabilities. It is difficult for them to realise the significant benefits that a comprehensive data analytics strategy would bring due to the historical constraints of legacy systems, IT cost and other resource issues.
Many financial institutions will realise that partnering with a firm such as ours will have the key benefits of being able to define and deploy their strategy in-house while outsourcing virtually all of the costs and complexity to a focussed data analytics partner.
In another study, it was noted that although the use of machine learning and advanced analytics may be in its relative infancy in fixed income markets, one Head of Sales noted that those banks without it ‘will automatically be at a disadvantage’[2].
A well planned and executed data strategy will allow more employee time to be spent on higher-level thinking, creativity and decision-making by leveraging technology that will process, analyse and evaluate increasingly complex datasets that are currently unable to be fully utilised.
References
¹ Technology and Innovation in Europe’s Capital Markets – Current trends in technology and innovation and their impact on the ‘Investment Bank of the Future’: September 2018
² Future of Sales – How Investment Banks must adapt to a shifting sales landscape 2019