INTRODUCTION

Capco partnered with a tier one global bank to establish and grow their data capabilities within a new chief data office function to address regulatory requirements, market competition, and new business and technology demands. 

During this complex multi-year programme, we partnered with the bank to:

• Meet global regulatory requirements and commitments
• Establish an effective governance structure for their chief data office (CDO) 
• Define a principle-based policy to enforce minimum standards of data management and ensure a robust control framework 
• Create a new data quality framework with monitoring, profiling, and enhanced issue management capabilities to provide transparency of the quality of data across the bank and drive continuous improvement  
• Upgrade existing technology and onboard new technology to automate and integrate processes, ensuring these aligned to the bank’s long-term strategic architecture 
• Developed and are now implementing a bank-wide IT data strategy which is focused on breaking down monolithic data platforms into a new, cloud-based, distributed data product ecosystem. This is based on data mesh and microservices architecture, which has enhanced data control, data quality and data management frameworks built into its core.  

WHY NOW?

The importance of banks’ data rose to prominence in the wake of the financial crisis leading regulators to require banks to substantiate capital planning by increasing the focus on the reliability of data aggregation and reporting. Across the industry, banks are now in the process of transitioning from a defensive position focused on data integrity to meet regulatory requirements, to a commercial strategy driven by profitability. 

In particular, the bank wanted to lay the foundations for the usage of data as a corporate asset to obtain commercial advantage. The bank pursued improvements to design effectiveness and operational efficiency through strategic data management and governance, data analytics, insights and automation, e.g., through artificial intelligence and machine learning.  

THE CHALLENGES  

• Maintaining significant volumes of metadata related to critical data which the bank had captured to meet regulatory commitments and ensuring this metadata remained up to date, fit-for-purpose and usable was a persistent challenge at the heart of the bank’s strategic change initiatives 
• Inconsistent representations of data and data quality across the bank were key barriers for uncovering, understanding and remediating data quality issues required to maximise opportunities for competitive advantage. 

OUR APPROACH

1. BUILD AN APPROPRIATE AND EFFECTIVE CHIEF DATA OFFICE (CDO)

The bank’s data management framework was significantly enhanced, governed by policy and syndicated at board level to strengthen the bank’s data culture.  Group-wide centers of excellence were established to enable the effective roll-out of capabilities to support the bank in the continuous improvement of its data quality through monitoring compliance against minimum standards. Top-down data metrics were introduced to measure the performance and ongoing maturity of the CDO function.

A clearly defined and understood governance structure formalised in policy and guidelines was essential to establish and embed governance bodies and roles across the bank. In particular, a clear distinction was made between the roles of technology and business in their management of data with data ownership residing with the business. 

2. ESTABLISH A COMMON DATA LANGUAGE

Establishing a common language using easily understood business terms was vital in building awareness of the importance of good data management across the bank. The introduction of glossary standards provided consistent definition of critical data which enabled a shared understanding across business areas within the bank.

3. ACHIEVE AND SUSTAIN GOOD DATA QUALITY

Data controls’ best practices and minimum requirements including standardised measures were established for correctness, completeness and timeliness dimensions to enable a common understanding and transparency of data quality across the bank and to help drive trust in the data output. Data profiling and advanced analytics were used to proactively interrogate data sets to better understand data quality issues. A streamlined data quality issue management and governance process supported by a single bank-wide tool and repository were instrumental to drive the focused remediation and improvement of data quality.

4. SUPPORTED BY SUITABLE TECHNOLOGY

The bank’s existing technology stack is being upgraded to encompass the enhanced data management framework which enables the appropriate usage of governed data and promotes informed investment decisions. Capco is partnering with the bank to implement new technology patterns with a shift towards modern, cloud-based data mesh and microservice architecture which control and govern data and make related automated processes readily available to consumers when they need it. Additional benefits for the bank include automated lineage, common taxonomies and real-time data quality controls. Implementation requires aligning to the bank’s strategic architecture roadmap with good data management standards built into the core of its infrastructure to maximise commercial value. 

WHAT NEXT?

Continue to build on the trust already established by the CDO, business and technology partners within the organization, strengthening the data culture with a clear code of ethics and training tailored to the lines of defence. The further use of analytics and insights will provide a clearer view of the level of data quality across the organization and drive focus areas for remediation and the development of commercial portfolios. Continue to mature the bank’s data architecture.