Reviewing Data Management Practices
An asset management firm requested our assistance to analyse the existing processes around the creation and maintenance of security data and provide recommendations for improvement through benchmarking to industry best practice.
The firm has a reasonably traditional investment strategy mainly investing in straightforward products and a small number of OTC derivatives where all accounting and reporting is performed in-house.
Based on a high-level overview of the existing processes, we scheduled a series of interviews with key users and departments. This meant holding discussions with representatives from all relevant functions which included Portfolio Management, Compliance, Accounting, Corporate Actions, Settlements, Legal, Risk and IT.
All interviewees were asked to describe on an individual basis what their involvement was in the creation, maintenance or use of security data. They were encouraged to raise issues and frustrations and to put forward suggestions for improvement.
The analysis was captured on a detailed set of process-flow charts which described the whole process and highlighted the impacts and interdependencies on multiple functions. These were reviewed and refined in supplementary cross-functional discussions.
It was immediately apparent that there was an excessive amount of manual data input and validation as well as a surplus number of teams required to create a simple security. More critically, there was a lack of data ownership and an IT framework in need of review against current best practice.
The End Result
Within six weeks, we presented the client with functional and technical improvements that would reduce risk, bring them into line with current industry best practice and have potential for cost savings and many of these have been implemented since our report.
The functional recommendations affected every part of the process and included:
- Establishment of a data governance hierarchy
- Nomination of a dedicated Data Manager
- Centralisation of security creation and maintenance within a dedicated team
- Automation of data processes to replace manual inputs
- Proactive identification and resolution of issues to improve data quality
The technical recommendations were with a focus to minimise operational risk and included:
- Introduction of a dedicated data management system, either via in-house development or by purchasing a system such as Curium or Markit EDM
- Review of the existing data processes to streamline these back to core functions
- Removal of redundant applications from the process