Home Banking From a good start to a great finish: Automating data flow in banks

From a good start to a great finish: Automating data flow in banks

by internationalbanker

Shivani PhotographBy Shivani Venkatesh, a Lead Consultant at iCreate who comes with rich experience in Consumer Banking (Channel Management, Proposition Development, Customer Portfolio Management and Segment Strategy). Shivani is currently working with iCreate’s solutions team in building nextgen banking decision enablement products and solutions.

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.

Banks were given 6 to 24 months depending on their readiness and maturity levels to achieve the desired end-state. But, given the diversity of the subject areas (across 200+ reports), the required involvement of multiple teams (IT, Business, Risk & Compliance) and an aggressive deadline by when RBI required banks to be ‘ADF-ready’, this was an initiative that demanded  attention and focus from the bank’s senior management. Several solution choices were available at the time; while some purchased ‘off-the-shelf’ products, other banks opted for in-house development and a few engaged services vendors.

It is exactly 3 years since and the solution implementations are now approaching closure. While there have been several success stories, not all banks have been able to achieve the desired end-state, due to a variety of factors. In certain cases a CDR was not created. In some other scenarios, straight-through processing of data couldn’t be achieved due to the complexity of interacting with diverse source systems. There are also cases where a substantial amount of manual intervention was required (to track timelines, review the reports and finally submit them). Quite a few prominent banks had to invest considerable unplanned amount of effort in these operational tasks.

One could infer that while the efforts were genuine and consumed significant resources in terms of time and money, 100% data flow automation (as envisaged by the RBI, within the timelines) is yet to be achieved by the Indian banking sector.

On the other hand, certain banks that invested in developing a solution exactly as per RBI’s recommendations, reaped benefits (hands-free report submission, for instance) resulting in significant savings in terms of man hours which was earlier devoted to extracting data from multiple source systems, business owners, calculating / validating values, tracking deadlines, etc. Also, creation of a CDR proved to be a boon, because it could be scaled for business reporting as well as all other non-regulatory reporting. The CDR eventually became a robust regulatory and business report data mart for banks. Another positive outcome was, banks began investing serious efforts to enhance data quality through process and technology initiatives.

While a modest number of banks have truly achieved ADF-readiness and reaped additional benefits from the investments made, the majority continues to trail behind, despite having made significant investments. With feedback from the RBI trickling in, banks are now reviewing their ADF solutions to understand if it actually meets the intended objective of the guidelines.

With considerable monies already invested in ADF, banks are now looking at solution providers who can add value in terms of accelerating efficiencies. They are also looking at niche ADF specialists who can bring their experiential implementation expertise to the table. With a renewed focus on ADF by the RBI and with senior executives re-igniting the ADF compliance thread, the Indian banking sector appears to have a new momentum to get ADF-ready.


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