“Agility, quality and interoperability will likely be core components of the data-buying decision framework in 2024.”
Leila Sadiq is Bloomberg Global Head of Enterprise Data Content.
What were the key themes for your business in 2023?
2023 was both exciting and challenging for the industry, marked by leaps forward in technology and unprecedented uncertainty within the market and geopolitical space. Amidst those shifts, data strategy is, more than ever, an important part of C-suite conversations and factors heavily into a firm’s strategy to compete in a challenging market. Another trend we’re seeing is vendor consolidation by capital markets participants, as they look to simplify extremely complex data operations.
In 2023, as a business, we continued to expand our data product offering with interoperable solutions that help our customers solve complex issues and unlock more opportunities and insights.
Key highlights in 2023 include the launch of our Enterprise Funds Data solution and the expansion of our regulatory data products, which give customers unparalleled agility to respond to global sanctions, entities screening and FRTB data challenges. We also brought new cutting-edge solutions to the market, like Bloomberg’s Research data solutions for quantitative and quantamental analysis, and continued to invest in our award-winning Liquidity Assessment tool, LQA, one of the first in the industry to create trust with our clients for how it uses Machine Learning.
AI has been a leading topic this year, how has this impacted your business?
2023 has indeed been a standout year for the global adoption of artificial intelligence with Gen-AI and Large Language Models. Where this intersects with my business is that these types of models require discernibly high-quality data to foster reliable and understandable outputs.
Having a solid and best-in-class data foundation is key to the future success of our customers, especially when it comes to projects using AI, whether buy-side or sell-side financial institutions or non-financial corporations and government agencies.
For example, the use of AI in financial models requires robust data inputs like foundational reference data inclusive of corporate actions and funds data, market data and any other proprietary data, delivered faster and more efficiently.
This is an area we are paying close attention to as it plays to our known strength of providing high quality, comprehensive data that can be easily integrated with other datasets.
What are your expectations for 2024?
I expect we will see a heightened focus on data management challenges in 2024.
With growing uncertainties in the geopolitical landscape, a challenging market environment, supply chain risk, weather pattern shifts, and the ongoing transition to a low-carbon economy, customers increasingly face new interconnected challenges and need interoperable data sets across their business operations.
To be resilient, customers also require a holistic and granular view into areas like corporate structure, country of risk, supply chain exposures, default risk and physical risk that may impact their operations and/or investments.
Having interconnected datasets complemented by modern cloud-ready data management services, like Bloomberg’s Data License Plus solution, allow market participants to make these connections at scale and derive more value from their data. Agility, quality and interoperability will likely be core components of the data-buying decision framework in 2024.
