Research on data governance and data granularity

DTS implemented for CGAP, part of the World Bank, a series of pioneering research projects designed to strengthen how financial authorities govern, manage, and use data for inclusive and resilient financial systems. These projects generated actionable insights and practical frameworks to support supervisory agencies worldwide in building responsible, high-quality, and equity-focused data ecosystems.

The Challenge

Supervisory authorities face growing demands for better, faster, and more granular data to effectively monitor market conduct, inclusion, and risks. Yet, fragmented data governance, inconsistent taxonomies, and lack of shared data standards limit the ability of regulators to capture the full diversity of financial consumers, especially women, rural populations, and other underserved groups.

CGAP engaged DTS to map global practices, identify gaps, and propose solutions that would help financial authorities:
• Establish robust data governance frameworks to ensure data quality, integrity, security, and responsible use.
• Enhance data granularity to go beyond topline indicators and capture differences in access, usage, and outcomes across population segments.
• Build a stronger evidence base for inclusive policymaking, aligned with responsible data principles.

Our Work

Over a multi-month engagement, DTS conducted extensive research, interviews, and analysis with supervisory authorities globally, combining academic rigor with practical, field-tested insights. The project was delivered in two main workstreams:

1. Data Governance for Financial Authorities

We developed a research brief outlining:
• Best practices and standards in regulatory data governance, covering data collection, validation, storage, access, and sharing.
• Institutional governance models to clarify data stewardship roles and responsibilities within supervisory agencies.
• Ethical and responsible data use frameworks, including privacy safeguards, data rights of consumers, and accountability mechanisms for supervisory data handling.
• Recommendations for capacity building and infrastructure investments, enabling supervisors to build resilient and trustworthy data ecosystems.

2. Data Granularity for Diversity and Inclusion

This second research brief explored:
• The importance of granular data to uncover barriers faced by specific population groups, including gender-based disparities, rural-urban divides, and usage gaps.
• Global benchmarks and case studies where granular data has improved policy outcomes (e.g., women’s access to credit, quality of agent networks).
• Taxonomies and reporting templates that enable supervised entities to provide disaggregated and standardised data without excessive reporting burdens.
• Roadmaps for financial authorities to improve granularity in both regulatory and voluntary data flows, supporting inclusive market development.

Outputs

The project delivered:
• Two Research Briefs, designed for practical use by financial authorities, summarising findings, tools, and actionable recommendations for:
1. Data governance frameworks
2. Data granularity for diversity and inclusiveness
• Global landscape mapping of supervisory data practices across multiple jurisdictions.
• Policy guidance notes highlighting quick wins and longer-term investments for inclusive data strategies.
• Insights that are now informing CGAP’s global dialogue with regulators, standard-setters, and development partners on building data ecosystems for financial inclusion.

Impact

These research projects are shaping:
• Better data practices within supervisory authorities globally, leading to more reliable, consistent, and comparable market data.
• Improved inclusion policies, as regulators gain visibility into who is served, who is left out, and why, enabling targeted interventions.
• Greater collaboration between supervisors, financial service providers, and development partners on open data, shared taxonomies, and ethical standards.