Data can be a double-edged sword. It’s immensely valuable and growing exponentially in volume week by week. But in this deluge of information, there’s the risk of missing hidden gems.
Firms are relying more than ever on analytics to interrogate the large volumes of data in the hunt for signals and trends, according to a report by Iress and Waters Technology, 5 Key Drivers Shaping the Future of Trading, based on insights from 38 Australian-based capital markets firms.
More than 80 per cent of firms say their strategies are becoming increasingly data-driven, the report reveals.
Automated and algorithmic trading platforms are now vital to manage high-frequency, low-value transactions, according to more than half of the firms surveyed.
The evidence of a quickening pace towards transformation is underlined by the rapid uptake of real-time data, enabling actions and decisions that were previously inefficient or impossible.
Real-time data is enhancing trading strategies by identifying trends and anomalies as they unfold, bolstering algorithmic trading, providing more robust risk management and boosting data analytics.
Forbes Technology Council member Don Murray says the benefits are obvious but cautions that making real-time data an effective part of a data strategy takes time and effort. He recommends a clear plan to begin with, getting the right technology in place and starting small, perhaps with a pilot project.
Most importantly, Murray recommends prioritising data quality and security to ensure the accuracy, reliability and protection of real-time data sources.
AI’s role in enhancing data analytics
Using real-time data in artificial intelligence (AI) models unlocks new levels of potential.
A global survey of IT leaders across a range of sectors found the use of AI continues to accelerate, quickly spreading its tentacles throughout organisations, according to Info-Tech's Tech Trends 2025 report.
For the second year running, AI or machine learning was the technology attracting the fastest growing investment. Although it remains behind other more entrenched technologies: cybersecurity solutions, cloud computing, and data management solutions, the report says.
More than two-thirds of the Australian trading firms who contributed to the 5 Key Drivers Shaping the Future of Trading report expect AI to transform trading within five years and almost half are currently using AI for predictive analytics.
AI is already a valued and dynamic tool for trading firms. Its ability to process complex datasets, provide market volatility analysis and deliver predictive modelling has been a gamechanger.
Mixing in real-time data allows AI algorithms to analyse current conditions, identify trends and find anomalies to capitalise on opportunities and mitigate risks.
AI may also offer the chance to enhance environmental, social and governance (ESG) data analysis.
Capital Group’s annual Global ESG Study, a survey of more than 1100 institutional investors, found that while only 10 per cent are using AI to analyse ESG data, more than half plan to do so in the future.
Among the barriers to ESG adoption, difficulties with the consistency and reliability of ESG data are most widely cited, according to the Capital Group report.
Data consistency was also the top reported challenge in a 2024 report by the Morgan Stanley Institute for Sustainable Investing, which polled 900 institutional investors across North America, Europe and Asia Pacific.
More than three-quarters of asset managers and owners expect sustainable assets under management and asset allocations to rise in the next two years, driven by new mandates and a more established track record for sustainable investing.
Future-proofing through data-driven innovation
Better data science approaches combined with AI tools may also provide hope for new ways of addressing changing and often complex regulatory and compliance requirements. For example, automated compliance monitoring tools, able to flag suspicious transactions or compliance concerns are a leap forward in efficiency. Enhanced reporting using AI tools to generate detailed compliance reports is also a bonus.
Iress is keeping on the front foot by embracing best-of-breed systems as part of its rebuild.
The power of interoperability is driving our new SaaS (software as a service) cloud-hosted model and will help unlock the full power of analytics. Meanwhile, our upcoming data insights product leverages advanced big data processing technologies to enhance compliance and risk workflow efficiency, empowering data-driven decision-making across the organisation.
This article was originally published in SIAA Monthly February 2025.
