- Real–time data feeds are increasingly being adopted in the front office.
- Cloud technology remains a catalyst for improving data management and governance.
- Generative AI has the potential to enhance investment strategies and improve workflow efficiency.
Bloomberg Professional Services
As 2025 approaches, we reflect on data trends that shaped 2024. These include: industry participants such as portfolio managers, traders, and risk managers increasingly relying on real-time data to make decisions across asset classes; the ongoing use of cloud technology to process larger and more complex datasets; and the potential for generative AI tools to refine investment strategies and optimize workflow.
Immediacy becoming the baseline
With 2025 around the corner, attendees of Bloomberg Enterprise Tech & Data Summit, held in October 2024 in New York, identified key trends of the year. A significant trend noted was the growing reliance of portfolio managers, traders, and risk managers on real-time data to make faster and more informed decisions across various asset classes.
“We are now able to process data at speeds not possible years back. Even the transmission of data hope has leapfrogged from where it used to be,” said Pallavi Tripathi, Senior Vice President and CIO, Capital Markets Technology at CIBC. “Technology has enabled us to be able to keep up and react quickly.”
“Instead of just trading off of a price, before you hit that trade, you could look out at what’s the issue or sentiment,” said Cory Albert, Global Head of Real-Time Data & Technology at Bloomberg. According to Albert, seeing new coverage or bringing in data on solvency and creditworthiness still allows market players to trade on a price, but it gives the front office much more information.
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Cloud powering financial precision
Another trend highlighted by the experts during the Bloomberg Enterprise Tech & Data Summit is the continued role of cloud technology as a force multiplier. It enhances the management of new sources of data and alleviates pressures on collection, integration, and delivery of said data, thereby allowing experts to focus more on governance and analysis.
“If there’s an easier way for us to consume (data) in the cloud, where processing time is cut short, those are the things that we go for first, before going after solutions that we build to ingest the data… We focus more on delivering the data to the business a lot faster and getting it [into analysts’] hands because that’s where the value is driven from,” said Albert Obeng, Head of Technology, Private Alternatives at Alliance Bernstein.
Cloud systems are also changing where data is delivered and who consumes it. Applications in the front office are expanding, which creates a rising need for cloud platforms to be broadly accessible while companies maintain security and accuracy. This means data normalization becomes more important every single day.
Companies and their customers are demanding “high-quality content that’s comprehensive, immediately usable for downstream systems and applications, and can be integrated into existing and new tools and services so everyone in a firm can access consistent data across their workflows,” said Maureen Gallagher, Global Head of Reference Data at Bloomberg.
Significant potential for generative AI
Experts looking at 2024 trends in data, pointed also to the potential of Generative AI. “If we never saw another advance in intelligence beyond GPT-4, we’d still be extracting value from it for the next 20 years,” said Jonathan Frankle, Chief AI Scientist at Databricks.
“We have been seeing the trend of fundamental analysts and portfolio managers utilizing more quant overlays to target precise outcomes and manage risk better. Additionally, given the sheer volume of data out there that could drive alpha and the rise of GenAI, can fundamental investors retain their edge without incorporating more quant & AI/ML techniques?” asked Angana Jacob, Global Head of Research Data at Bloomberg.
Among use cases related to investment strategies, experts pointed to using AI for deriving insights from large datasets. “Within investment life cycles, there is a lot of unstructured data. Being able to capture that and then use AI on top of that to be able to query it, we can extract answers [from data],” said Alliance Bernstein’s Obeng.
Notably, according to the poll focusing on which investment approaches will drive alpha over the coming years, 45% of respondents selected human driven approach with AI assistance and more data sources, while 40% favor quant style with AI-driven strategies and human-oversight. By comparison, traditional quant style with access to new sources of data and improved quant technologies was selected by 14% respondent and approach based only on human intuition and experience was selected by 1%.
Additionally, AI is applied at financial services firms to streamline workflows to enable fast and efficient work. “It has been an efficiency play on so many levels: where can we use it for code reviews, where can we use it to perform operational tasks that make sense,” explained Kim Prado, CIO, US Capital Markets, Head Investment & Corporate Banking and Office of the COO at BMO during a panel at the Enterprise Data & Tech Summit on how financial leaders adopt technologies such as Gen-AI to drive business results.
Steps to refine decision-making process
The trends shaping the 2024 investment landscape emphasize the importance of high-quality, readily available enterprise data in refining decision-making processes. As real-time data feeds and cloud technologies transform operations, market participants’ embrace of generative AI underscores the ongoing challenge of balancing accuracy with time-to-market.
Interested in using enterprise data to power your firm’s decision-making? See Bloomberg Enterprise Data solutions here.
Quotes in this article are from the Bloomberg Enterprise Data & Tech Summit held in NYC in October 2024. Watch the full event here.