Over the past few years, the Reserve Bank of India (RBI) has undertaken a series of strategic regulatory changes aimed at revolutionising the financial landscape of the nation. These initiatives are designed to enhance the robustness, transparency, and efficiency of financial institutions, paving the way for a more resilient and inclusive financial ecosystem.

In a recent roundtable session led by Nasdaq and attended by C-level executives from prominent banks in India, the discussion centred on navigating the evolving landscape of Indian regulations and future-proofing the banking regulatory ecosystem. Moderated by Regulation Asia, the discussion delved deep into several pertinent topics, shedding light on both challenges and opportunities for financial institutions.

CIMS Reporting: Challenges and Advantages

Comprehensive Information Management System (CIMS) reporting remains a cornerstone of regulatory compliance for banks. The panel highlighted the dual nature of CIMS reporting. On one hand, it poses significant challenges due to its complexity and the vast amount of data required. Banks often struggle with data accuracy, integration across various systems, and timely submission. On the other hand, CIMS reporting provides substantial advantages by offering a structured framework for data management, enhancing transparency, and paving the way for the future Element Based Reporting regime.

When CIMS was introduced in 2023, the aim was to modernise and automate the entire data reporting lifecycle and reduce the compliance burden for banks. The RBI’s long-term vision was to transition all reporting to CIMS, eliminating the need for multiple submission platforms and reducing data redundancy.

According to the roundtable participants, the transition to CIMS has been slow due to technical complexities and integration challenges, but it has been progressing gradually. Currently, around 70-80 reports are being submitted to CIMS, out of a total of around 250 returns required by the RBI.

The participants at the roundtable also highlighted that there is still “ad hoc information” being requested by the regulator, though they acknowledged that this will become less common as the reporting ecosystem becomes more advanced.

From the RBI’s perspective, there is a recognition that not all reporting entities have the same level of sophistication, which means the process of transitioning can be slower for firms that face resource or other constraints. The regulator is aiming to “create a balance” that allows all reporting entities to transition together. This ensures no segment is left behind, but also slows down the full adoption of CIMS.

One participant highlighted that the RBI does not provide a UAT platform that allows banks to test their CIMS submissions before they go live. He said this not only impacts data quality, but presents operational risks for banks and introduces the potential for reporting errors.

“When trying to work across different departments within the bank to implement transformation projects and get those data that we need, we encounter a lot of practical issues,” said another participant. “It all happens through email and Excel sheets and creates a lot of chaos.”

CIMS is designed to create more streamlined and seamless reporting processes, while ensuring high quality data in submissions. When launching CIMS in 2023, then-governor Shaktikanta Das highlighted the importance of complete, correct and consistent data for the central bank’s statistical analysis and policy formulation.

Currently, the RBI is understood to be working on a framework for grading data quality levels at banks based on their submissions. It is hoped that this peer benchmarking process will help to drive improvements in this area.

Foreign Banks in India

The participants from foreign banks highlighted a set of unique challenges they face in complying with regulatory change in India, mostly arising from the need to secure budgets and resources from overseas headquarters for implementation.

“From a foreign bank perspective, we usually use global systems with servers located outside India, so making any changes or tweaks to our systems is not in our hands,” said one participant. “This becomes a challenge particularly when tight deadlines are set, because there is always already a priority list of system changes lined up for implementation.”

Another participant highlighted the need to ensure a proper understanding of the importance and criticality of a change that is being implemented to be able to communicate this to the group level. He noted that clearer communication of implementation deadlines is sometimes needed from the RBI to provide enough time for foreign banks to secure budgets and approvals at the group level.

“Often the implementation deadlines don’t factor in enough time to deploy changes, particularly if there is a change in the data elements being requested, which require further mapping and disaggregation of data in some cases,” said another participant.

“Every bank stores data at a different level of aggregation,” he said. “Whenever the RBI demands certain data, some banks may be ready with that level of aggregation of that level of element. But others may already have another aggregated level of data stored on top, meaning they have to detach those data to submit what the RBI has asked. This is what often takes a lot of effort and causes a lot of last-minute rushing.”

Some participants also noted that their local units are often unable to leverage common infrastructure, accounting platforms or automations built at the group level because India does not align with international standards such as IFRS.

Source of Truth Model: Journey to Success

Subbaiyan Vaithinathan, Head of Regulatory Technology Products and Financial Technology for APAC at Nasdaq, said some large banks in India have overhauled their data infrastructure to accommodate current and future changes to reporting requirements, adopting a “source of truth” model.

This involves consolidating the data in a centralised repository within a bank to make access to high quality and complete data easier for reporting. Vaithinathan said this model has resulted in fewer challenges uploading reports, fewer errors, and faster transformation to accommodate CIMS.

“People used to implement band-aid solutions, patch things and still keep their departments and organisations siloed,” he said. “Using this ‘source of truth’ model instead brings a lot more innovative solutions into the market and pushes the industry to move faster.”

While on paper this looks like a simple solution, getting this implemented across a bank with the legacy operational and data issues is much more challenging.

Vaithinathan also added that, in his experience, financial institutions that embark on strategic data and reporting programmes have gradually solved all their major pain points over time, and in the long run they “experienced fewer struggles in implementing regulatory changes”.

Some other banks applying tactical or “short-cut” solutions to meet their reporting requirements seem to have more issues complying with regulatory changes in a timely manner, he added.

The Role of AI in Regulatory Compliance

Artificial intelligence (AI) is poised to play a transformative role in the regulatory compliance landscape. The participants explored how AI can assist banks in automating compliance processes, enhancing accuracy, and reducing the burden of manual reporting.

Elevating Data Quality

One of the pivotal roles that AI will play is in enhancing data quality. Accurate data is the cornerstone of regulatory reporting, and AI offers tools to ensure its precision. By detecting anomalies upfront, AI systems can flag inconsistencies before they become larger issues. This proactive approach not only saves time but also mitigates the risk of submitting erroneous data.

Moreover, AI’s capability to analyse trends and variances can be instrumental in understanding the data landscape. Before submission to regulators, AI can scrutinise the data, providing insights into patterns that might otherwise go unnoticed. This level of analysis ensures that the information is not only accurate but also comprehensive, reflecting the true state of affairs.

One of the most critical aspects of data quality is reconciling data across multiple departments. Traditionally, this has been a labour-intensive process, rife with the potential for human error. AI, however, can streamline this reconciliation process, ensuring consistency and accuracy across various data sources. This harmonisation of data is vital for maintaining the integrity of regulatory submissions.

Streamlining Operational Processes

The second major impact of AI in regulatory reporting lies in operational efficiency. The regulatory landscape is characterised by stringent submission timelines, and any delays can have significant repercussions. By streamlining operational processes across different departments, banks and financial institutions can leverage AI to automate numerous manual tasks.

Automation through AI not only accelerates the reporting process but also reduces the potential for human error. Tasks that once required significant manual intervention can now be handled seamlessly by AI systems. This shift allows staff to focus on more strategic activities, thereby enhancing overall productivity.

Furthermore, the ability to maintain short submission timelines is crucial in the fast-paced financial sector. AI’s ability to process and analyse data rapidly ensures that institutions can meet regulatory deadlines without compromising on data quality. This agility in operations is a competitive advantage, enabling organisations to stay ahead in a highly regulated environment.

Element Based Reporting: What is Expected

Regulators in the EU, Australia, Hong Kong, and Singapore have been moving towards more granular data reporting requirements to strengthen the effectiveness of supervision, regulatory oversight, risk monitoring, and financial stability analysis.

Bangko Sentral ng Pilipinas (BSP) is meanwhile consolidating all reporting into an XML-based structure, moving away from Excel-based reporting. One participant called out this initiative as having the potential to enhance the quality of data supervisors receive while at the same time enabling efficiencies for banks.

The shift towards element-based reporting is another critical development in India’s regulatory landscape. This approach demands data elements rather than form-based reporting, thus requiring banks to maintain meticulous records and ensure data integrity.

The expectation is that more granular data reporting will lead to more precise regulatory oversight and better risk management. For banks, adopting element-based reporting necessitates significant investments in technology and training, but the long-term benefits in terms of compliance and operational efficiency are considerable.

The Way Forward

The RBI’s ultimate aim is to make regulatory reporting “completely seamless”. In the long run, it is seeking to move from return-based reporting to “element-based reporting”, which involves automated reporting of individual data elements at the granular level.

An element-based reporting pilot is already underway with some banks in India – the idea being to move to a world where data can be pulled by the RBI in an automated fashion rather than asking banks to submit individual returns.

Vaithinathan said as long as the data is consolidated properly, cleaned up properly, and available in the system, element-based reporting “should not be an issue” to implement. In this regard, he said banks need to avoid taking short-cuts or “using band-aid solutions” to obtain the required data for reporting if they wish to future proof against the new element-based reporting regime.

The roundtable participants agreed that technology has become a key for regulatory reporting. “Now we can’t do without technology – that is very clear,” said one participant. “The introduction of the CIMS platform means every bank now has to depend on technology.”

It was acknowledged that the RBI is addressing the cost of compliance to an extent, with plans to make it easier for financial firms in India to use cloud services, which could significantly enhance the efficiency and scalability of regulatory reporting at Indian banks.

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This article was developed in a collaboration between Regulation Asia and Nasdaq.

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