Capco partnered with a tier one Global Bank to establish and grow data capabilities within a Chief Data Office to address regulatory requirements, market competition and new business demands.
During this complex and multi-year programme we helped the bank to:
The importance of a bank’s data rose to prominence in the wake of the financial crisis as regulators sought to substantiate capital planning with regulations focused on the reliability of data aggregation and reporting. Banks are now transitioning from a defensive position focused on data integrity to a commercial strategy driven by profitability. In particular, the Bank wanted to use the data as an asset to obtain commercial advantage through analytics and insight, and improve operational efficiency through strategic data management and automation e.g. artificial intelligence and machine learning.
1. BUILD AN APPROPRIATE AND EFFECTIVE CHIEF DATA OFFICE (CDO)
A clearly defined and understood governance structure formalised in policy is essential when establishing and embedding governance bodies and roles across the bank. These foster trust within both business and technology and require clear strategic oversight and direction, divisional and cross-divisional data management combined with operational execution. We designed and implemented a robust data management framework formalised in policy and underpinned by guidelines to enforce minimum standards and mitigate data quality risk.
2. ESTABLISH A COMMON DATA LANGUAGE
Establishing a common language using easily understood business terms is vital in building awareness and engagement of the importance of good data management across the bank. Defining the semantic relationship of data enabled conceptual modelling which showed the hierarchy of data relationships and validated the provenance of “trusted” sources. This allowed service users to quickly understand what they needed and where and when to obtain it, avoiding unnecessary fact finding.
3. ACHIEVE AND SUSTAIN GOOD DATA QUALITY
Various quality dimensions such as completeness, conformity, consistency, validity, accuracy, and timeliness of data are measured and published/reported on a periodic basis to help drive trust in the data output. We used data profiling to proactively interrogate data sets to better understand data quality issues. We standardised the approach to onboarding data controls and created a monitoring dashboard which provided a clear view to stakeholders of data quality – building further trust and therefor further strengthening the data culture.
4. SUPPORTED BY SUITABLE TECHNOLOGY
We upgraded the existing technology, enabling it to encompass the new methodology, semantic relationships and data provenance minimising new spend. At the same time, we worked on on-boarding new technology enhancements to automate maintenance processes, ensuring these align with the bank’s long-term strategic architecture.
Continue to build on the trust already established by the CDO within the organisation, strengthening the data culture with a clear code of ethics and tailored training according to different lines of defence. The further use of analytics and reporting will provide a clearer view of the level of data quality across the organisation and drive focus areas for remediation and the development of commercial portfolios.