Compliance and operational reporting are becoming more demanding as regulators, auditors and boards expect timely, consistent and explainable numbers, supported by strong risk data aggregation and governance. Organisations must show not only what they report, but also how figures are derived, aggregated and controlled across systems – reflecting principles found in BCBS 239 and broader RDARR guidelines.
At the same time, many reporting landscapes are still built on a mix of legacy platforms, local extracts and spreadsheets, making it difficult to guarantee data quality, lineage and governance end to end when supervisors or internal audit start asking detailed questions.
The data challenge
Behind every compliance report sits a data problem:
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Critical metrics (financial, risk, ESG, operational KPIs, customer or product metrics) are sourced from different systems, with overlapping or conflicting definitions, leading to inconsistencies between regulatory, risk and management reports.
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Data moves through multiple steps – ingestion, transformation, aggregation – without consistent documentation or automated controls, so it is hard to trace how a figure in a report links back to the original transaction, which BCBS 239‑style principles explicitly expect.
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Reporting teams depend on manual reconciliations and ad hoc SQL or Excel logic that only a handful of people fully understand, increasing key person risk and making it harder to evidence robust risk data aggregation.
As reporting requirements grow in volume and granularity under RDARR‑inspired expectations, these data issues become more visible. Organisations need reporting that is faster and more flexible, but also demonstrably governed: complete, accurate, consistent and explainable to internal and external stakeholders.
The solution: a governed data and reporting layer
LACO helps organisations redesign their operational and compliance reporting around a governed data foundation, using modern cloud technologies such as Microsoft Azure, Microsoft Fabric, Power BI and Azure Databricks.
The goal is to create a single, reliable layer where critical data is integrated, modelled and controlled, and from which both day‑to‑day operational reports and BCBS 239 / RDARR‑aligned compliance reports can be served.
Concretely, this means:
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Data integration: ingesting source data from core systems into a central, secure data platform (for example using Azure Data Lake, Azure Data Factory or Synapse pipelines), with clear ownership and access controls that support regulatory expectations on data governance.
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Semantic and modelling layer: building governed data models that standardise key definitions – such as exposures, limits, revenue, cost, ESG indicators or operational risk metrics – so the same trusted data feeds BCBS 239 reports, RDARR‑driven risk dashboards and management reporting.
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Reporting and visualisation with Power BI: exposing governed datasets to business and compliance users via Power BI, with role‑based access, row‑level security and reusable report templates for recurring regulatory and internal reporting cycles.
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Built‑in data quality, reconciliation and lineage: embedding checks, reconciliations and metadata so teams can trace any reported figure back to its sources and transformation logic, and can demonstrate that data is complete, accurate and consistent – core BCBS 239‑style requirements.
By placing this governed layer at the centre, work shifts from rebuilding logic in each reporting tool to modelling and governing data once and reusing it many times – for regulatory risk reporting, RDARR‑aligned aggregation, internal risk dashboards and operational steering.
Result: explainable, BCBS 239 / RDARR‑ready reporting
Compliance and operational reporting become more repeatable, explainable and resilient, and better aligned with BCBS 239‑ and RDARR‑style expectations.
Reporting teams work with a single set of validated data and definitions, reducing inconsistencies between reports and limiting discussions about which number is the “right” one, both internally and with supervisors.
Business, risk and compliance users gain access to controlled data through modern tools, without bypassing the underlying governance, quality checks or lineage.
Organisations can adapt more easily to new reporting requirements or additional disclosures, because the underlying data architecture and technology stack are already designed for scalability, governance and reuse – creating a reporting landscape that not only supports today’s BCBS 239 / RDARR‑inspired demands, but is also ready for further digitalisation, stricter data rules and new forms of analytics and AI.
The reporting transformation becomes an engine for agility and trust, ready to support future regulatory change.
