Co-operative banks under RBI reporting pressure
Co-operative banks are under increasing pressure to deliver accurate Reserve Bank of India (RBI) reporting on tighter timelines, even while data remains distributed across core banking, treasury, and digital channels, according to Vivek Hegde, Founder Director and CEO, Ahana.
“With the Data Model, designed by Ahana, we are helping banks reduce manual effort, improve audit readiness through traceable lineage and historical records, and move toward faster, more consistent regulatory reporting cycles,” Hedge said on 15 April.
Taking note of such requirements, Ahana has announced a solution-led initiative for co-operative banks, built on Ahana’s Data Management Solution platform and delivered through the Data Model designed by Ahana. It is a business solution purpose-built for co-operative banks to simplify RBI reporting in environments where data resides across core banking, treasury, and digital channels. Reporting cycles still rely heavily on extraction, validation, reconciliation, and spreadsheet-driven workflows.
Adapting to the Evolving RBI Reporting Landscape for Co-operative Banks
Co-operative banks often manage reporting data across multiple systems and departments, leading to reconciliation overhead and inconsistent reporting outcomes. Common conditions include disconnected core banking, treasury, and digital systems; RBI reporting that takes days per cycle; higher error rates due to manual consolidation; and difficulty producing a unified customer view.
Audit readiness adds complexity. In many environments, audit data is distributed across departmental systems without a historical data retention strategy, and reports are manually created from on-premises backups, increasing turnaround time and contributing to repeated audit delays.
The same operating conditions will require substantial manual effort, with approximately 30 to 40 personnel across functions such as Credit Monitoring, Accounts, Treasury, and Forex involved in data extraction, validation, and consolidation for MIS and reporting.
A governed RBI reporting solution for co-operative banks and audits
Data Model designed by Ahana is being used to deliver a regulated reporting framework for co-operative banks, focused on simplifying RBI reporting where reporting cycles depend on manual consolidation. The solution establishes a governed reporting foundation that consolidates data, standardizes processing, and supports RBI and MIS reporting workflows through structured pipelines and analytics-driven consumption.
From an implementation standpoint, the approach focuses on standardizing ingestion, orchestration, and report-ready data structures to reduce manual consolidation.
Srinath C V, Head – Automation and AI Initiatives, Ahana, elaborated, “For regulated reporting, automation needs controlled pipelines and consistent definitions across cycles. By standardizing ingestion, orchestration, and the STG, CDR, and MART structure, banks can reduce dependency on spreadsheet-driven workflows and make reporting more repeatable.”
Outcomes that co-operative banks can expect
The solution is positioned to support measurable outcomes, including faster RBI reporting cycles moving toward reports generated in hours instead of days, reduced manual effort and error exposure through standardized processing and reduced dependency on spreadsheet-based workflows, and improved audit readiness supported by traceable data lineage and historical records for regulatory review.
Ahana noted that delivery emphasis is on operational controls that support consistent reporting cycles and audit readiness.
Chidananda Murthy, Head-Presales, Ahana, continued, “The priority is to make reporting dependable in day-to-day operations. That means there should be clear controls around data quality and audit evidence, historical records supported by traceable lineage. This reduces redevelopment and massaging of reports. This will greatly reduce the pressure on MIS team to commit the timelines for report submission.”
It also supports a scalable KPI operating model, including measures such as on-time submission rate, data quality score, report preparation time, and manual adjustments per report, tracked on a defined cadence. The approach is intended to support a single source of truth for reporting and audit needs and minimize discrepancies across systems. Fiinews.com
