5 min
During late 2010, India’s premier Central Regulatory Institution - the Reserve Bank of India (RBI) informed banks via an ‘Approach Paper’ that they require submitting over 200 reports spanning key areas such as Treasury, Reconciliation, Advances, Deposits, Frauds and Foreign Exchange. While banks were already sharing most of this information with the RBI, the highlight of this particular communication was that the data henceforth had to be submitted directly from the banks’ source systems with ‘no manual adjustments’ (to ensure data quality, accuracy, integrity and auditability). RBI essentially sought a ‘straight-through processing’ of data directly from the banks’ source systems by first storing the data in the banks’ Common Data Repository (CDR) and then performing an automated upload of reports at pre-defined frequencies into the RBI’s CDR. This new process was termed ‘ADF’ or Automated Data Flow.
The RBI viewed ADF as the bedrock for accurate, real-time insights on the state of the Indian Financial Services sector. This was also part of the RBI’s strategy to evolve to a technology-driven data collection approach, which would also enable better downstream BI and Analytics that could be developed on the same data.
The Approach Paper also mentions certain ‘layers’ or components that were fundamental to achieving the larger ADF objective (see image below) -
- The Data Acquisition Layer would need to have the intelligence to interact with and extract data from a wide range of banking source systems (core banking systems, product processes, etc.) and perform data quality checks as required.
- The Integration & Storage Layer needed to have a comprehensive data model that would facilitate capture and storage of all relevant data elements.
- The Data Conversion Layer would need to facilitate necessary data conversions and unification to enable final report creation and submission.
- The Data Submission Layer was envisaged to have features to enable scheduling of report submission, review by relevant stakeholders and conversion to XBRL.
- ‘Nobody Wants a Proprietary Platform,’ Says Coforge’s Anup Nair
- Why Buying Specialist Engineering Firms Won't Fix Indian IT’s Growth Problem
- The Anthropic-Indian IT Partnership Is a Two-Way Bet
- Coforge Is Outgrowing Its Larger Rivals. Is AI the Reason?
- Are Boutique AI Firms India’s Next Big Thing?
- Indian IT’s New Workforces Come with a Margin Challenge

