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Addressing Data Management Challenges with Emerging Technologies and Industry Collaboration

By Kapil Bansal, DTCC Managing Director, Head of Business Architecture, Data Strategy & Analytics| 3 minute read | October 18, 2023

Along with AI, cloud and other advances, it will take a cultural shift to overcome the obstacles of overlapping standards, legacy-system complexities and firms not optimizing their own data’s power.

We operate in an increasingly data-driven environment. Data is being leveraged to address many of today’s challenges, providing new insights to assist with areas such as risk management, operational performance measurement and client experience.

In recent years, with the increased focus and growth in access to data, and as the financial markets have grown more digital, the data capabilities have expanded alongside the development of a broader set of methods and formats for data exchange. Yet, this increased focus on data has not resulted in improved methods for managing, using and exchanging data efficiently across the industry.

Related: Powering Innovation with Cloud and Data Analytics

To date, while the industry has focused on standardization of data exchange across organizations, little attention has been placed on developing standards for how data is managed within firms. At the same time, several aspects of firms’ trade lifecycles remain manual, such as post-trade processes, meaning that some data never gets analyzed or even stored in modern technology platforms.

There are several reasons why data management and exchange are inefficient today, including:

  1. Data exchange is often dictated by overlapping standards and formats that require a high degree of maintenance.
  2. The way data is stored in most organizations, typically in silos, prevents its users from exploiting it fully.
  3. Many data sets that financial institutions rely on today do not have the data quality standards necessary for decision support and automated decision-making.
  4. Operational complexities remain, including manual processes in the post-trade lifecycle.

Embracing Innovation and New Technologies

To effectively address these challenges and capitalize on the power of data, firms should consider two key priorities: accelerating innovation, including the adoption of new technologies; and embracing greater levels of industry collaboration.

Technology is constantly evolving and being adopted in ways that both enable and necessitate change and drive innovation in data management and exchange. This is true for new technologies like artificial intelligence and distributed ledger technology, but also is clearly demonstrated when looking at the most rapidly adopted technology that can support improved data management – cloud computing.

DTCC research finds that most firms expect to have applications that are fully cloud native, or to have fully adopted cloud, by 2024, meaning the industry is currently balancing the need to re-architect the way it handles and manages data as well as the risk management concerns that can arise when introducing third-party technologies into an organization.

But in the face of these adoption challenges, the industry is also benefiting from cloud’s ability to deliver solutions to current data management inefficiencies. Specifically, firms can exploit the power of data leveraging cloud’s scale and automation capabilities, which can mean quicker insights, quicker business processes, and ultimately a more efficient financial services industry.

Other emerging technologies, like AI and machine learning, can also be impactful in data management through their ability to improve data processes, but many firms are still very early in their use.

For example, in many early experiments with AI, financial institutions lacked the large-scale clean data sets needed to take full advantage of AI. Identifying solutions to today’s data management challenges can support firms’ innovation and modernization journey not only by providing access to clean data sets, but also in enabling new technologies that can be leveraged for processing and analysis.

Yet, this increased focus on data has not resulted in improved methods for managing, using and exchanging data efficiently across the industry.

A Culture of Collaboration

While technology can be an incentive and an essential tool to improve data management, any true industry shift demands collaboration. At DTCC, we have already seen industry experts collaborating in this area and expect to see increased levels of data sharing between partners and counterparties in the near future.

The culture surrounding the next generation of data exchange and sharing will be more collaborative than ever before, enabled by new technology and driven by business necessity. Organizations across the industry will need to embrace openness and greater flexibility. Collaboration efforts will need to be supported by strong governance around data, as well as high standards around privacy and security.

New paradigms will enable participants to transfer data to places in the trading and data ecosystem where it can be amplified. There will be greater data sharing, especially of standardized reference information between partners and counterparties, leading to the emergence and growth of data utilities that serve new and existing clients.

As we look to the future, data must be accessible, secure, interconnected through ecosystems and deliver powerful insights. Today, the future advancement of data management is blocked by overlapping data standards, legacy technology complexities, and firms not fully exploiting their own data’s power. These challenges can be addressed through a cultural shift in the industry’s thinking around data exchange while embracing new technologies and a culture of collaboration and sharing.

By embracing innovation, leveraging technology and ensuring ongoing industry dialogue, the power of data can reach its full potential. The future advancement of the industry will be enabled by data.

This article first appeared on the GARP web site on October 13, 2023.

Kapil Bansal - Managing Director, Head of Business Architecture, Data Strategy & Analytics at DTCC
Kapil Bansal Managing Director, Head of Business Architecture, Data Strategy & Analytics

 

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