The Depository Trust & Clearing Corporation (DTCC) has detailed four hypotheses that will drive how data is used in financial markets in the future – data will be more accessible and secure, interconnected data ecosystems will emerge, there will be more capacity to focus on data insights, and open source data standards will become ubiquitous.
The company sets out the hypotheses in a white paper it researched and wrote, Data Strategy & Management in Financial Markets, with a view to identifying data management challenges and themes driving evolution in financial market data exchange and data management over the next decade.
“For years, companies have collected massive stores of data, but the siloed nature of data and the need for better data quality has limited ability to extract strategic insights for more effective decision-making,” says Kapil Bansal, managing director, head of business architecture, data strategy and analytics at DTCC. “We’re at a moment where we can make this a reality, but long-term success hinges on market participants ensuring their data strategy meets the demands of a digitalised and interconnected marketplace.”
Expanding on the four hypotheses, DTCC notes that in terms of data being accessible and secure, data users will have increased flexibility in determining how and what data is received at desired times. To enable this, data governance, privacy and security will need to be prioritised.
Interconnected data ecosystems as a new infrastructure layer will allow industry participants to move their data from legacy systems and pool it in data ecosystems and connect these ecosystems to others. This will reduce duplication of data across the industry and allow for co-development of innovative data insights.
On increased capacity to focus on data insights, DTCC says more efficient data management, cloud enabled capabilities, and further automation of routine data management tasks will free up capacity and accelerate time to market for new product development.
Finally, the paper refers to ubiquity of open source data standards, anticipating that the industry will continue to adopt more standards around data models, with the most viable use cases being reference and transaction reporting data. This will result in increased operational efficiency and better data quality.
To enable these changes, institutions that produce and consume significant amounts of data need to embed key principles into their data operating models, including: robust foundational data management capabilities; strong data governance; and of where there is mutual benefit from collaborative data environments. Applying these principals, the paper concludes, will help market participants gain access to data that is trapped or underutilised today, and allow for new and faster insights.
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