Automating Operations on Mission-critical Data


Why Establishing Best Practices for a Data-centric Operating Model in the Middle- & Back-office Matters More Than Ever

This report, presented in partnership with Duco, examines the ways in which the operating models of different types of capital markets financial services companies are evolving to become data-centric by focusing on upstream data quality as a means of minimising the need to deal with downstream exceptions.

Read More

The capital markets industry’s data operations capabilities are, in 2023, arguably on the cusp of coming of age, thanks to developments in technology and best practices that have made it possible to think about data differently. A recent GreySpark survey of financial services firms found that it is often the case that the software necessary to manage a firm’s data in a truly automated fashion has not yet been deployed uniformly across all its operational areas. Large parts of the middle- and back-office arenas typically are losing out on the benefits of data automation through the persistent use of legacy technology.

This report explores the scale of that problem, arguing that data automation in the middle- and back-office should not be a luxury only available to a select few and it should not be deployed on a team-by-team basis. Instead, institutions should seek to create an enterprise-wide data-centric operating model that is enabled by a data automation system that seamlessly integrates with other upstream and downstream siloes to digitally transform – front-to-back – the entirety of a firm’s post-trade landscape.

This system should be capable of addressing the core issues of reconciliation and operational controls along the trade lifecycle, for example, thus creating opportunities for firms to solidify the foundation on which their data operations rest and – in doing so – saving time and money by ensuring that the data entering any workflow is clean, reliable and auditable.

Published on: 3 Sep, 2023

Please login or register to download this report for free


  • 1.0 From Data Opacity to Data-centricity
  • 2.0 Many Routes to Better Data
  • 3.0 Standardising Custom Data Operations
  • 4.0 Consolidating High-volume Data Operations
  • 5.0 Data-centricity: Thinking About the Data that Drives the Process
  • 6.0 Data Automation: A Roadmap to Data Centricity
  • 7.0 True Data-centricity

You may also like…

  • Digital Transformation: Artificial Intelligence Applications & Use Cases in Investment Banking 2022

  • Digital Transformation of Investment Banking

  • Digital Transformation: Assessing Sellside Digital Maturity

  • Digital Transformation: Assessing Sellside Digital Maturity 2021