Abstract

The Reserve Bank of India is an integral part of the official statistical system in the country. It compiles and disseminates macro-financial statistics in areas related to banking and financial systems, currency, payments system, monetary policy surveys, foreign exchange management, external accounts, private corporate sector, and public finance including public debt management. The Reserve Bank’s system of data and information management has evolved over the years guided by its statutory role, promotor of robust financial architecture, policy and monitoring needs, and emerging requirements of the growing economy and financial system. It disseminates considerable information as a ‘public good’ and also constantly strives for refinement in relevance, quality and timeliness of data to support data-driven policies and monitoring.
Currently, activities like building an information management system based on data warehousing approach for data receipt, processing, production, storage, retrieval and dissemination; standardisation of reporting of financial data; developing a statistical system for maintaining data quality are largely centralised. This paper reviews the existing information management structure in the Reserve Bank with respect to the three critical elements of data governance, viz., people, processes and technology. It also discusses the information governance through an inter-departmental return governance group, which aims to rationalise the process of rationalisation regarding data elements, periodicity, new prescription/s and system/s in a concerted manner. The Reserve Bank has deployed tools and technology for managing each stage of the data lifecycle, namely data collection, compilation, dissemination and access. Given the diversity of reporting entities with different levels of technology, use of multiple channels for data collection and their handholding is necessary. The investment in technology for information management and handholding of reporting entities, when necessary, has ensured continuous flow of information to the public even during the period of lockdown induced by the COVID-19 pandemic.
The present structure has consolidated the learnings from the past in terms of standardisation of data collection methods; rationalisation of returns/statements; and reduction in the time required to deploy a system for new data/modification of existing data due to the centralisation of overall information management. The scope for implementation of global best practices has ensured increased standardisation across the organisation. The envisaged changes for implementing a data governance framework at the organisation level include: (a) implementing an enterprise-level data model, (b) standardisation of return introduction/modification, (c) maintenance of metadata and definitions, (d) implementing element-based reporting, (e) provision of standardised supplementary information, (f) conduct of periodic reviews, and (g) creation of principles and policies related to data lifecycle. Finally, the paper discusses the guidelines provided for implementing data governance at the regulated entities and recommends increased engagement of the regulated entities and other financial regulators; development of a data quality framework with appropriate metrics to evaluate the quality of data; and implementation of data privacy decisions and protection for efficient data governance.

* The paper is co-authored by Archana Dilip and Debasis Nandi. The views expressed in this paper are those of the authors and are not necessarily shared by the Reserve Bank of India.