Basel III and IFRS 9 Reporting Automation at an ASEAN Tier-1 Bank — From 28 Days to 7 Days Close
Regulatory Reporter + Data Quality Auditor + Financial Close automating the Basel III and IFRS 9 reporting estate end-to-end.
The challenge
The bank — a Tier-1 commercial bank headquartered in an ASEAN market with operations across six countries — was running a regulatory-reporting operation that consumed approximately 28 calendar days each month to produce the suite of Basel III prudential filings, IFRS 9 ECL calculations, and the local-regulator returns across its six markets. The process was deeply manual: a 35-person regulatory-reporting team spent the bulk of each month extracting data from approximately 14 source systems, reconciling it across systems, applying the required regulatory adjustments, drafting the filings, routing them through internal review, and submitting them through the various regulatory portals.
The cycle was getting worse, not better. Each regulatory update — and there had been seven material updates across the bank's six markets in the previous two years — required the team to re-engineer parts of the data flow. The bank's external auditors were spending increasing time on reporting quality assurance, which translated directly into rising audit fees. The Monetary Authority of Singapore's most recent inspection had specifically flagged the bank's reporting cycle length as a concern, given the increasing supervisory expectations on the speed of regulatory transparency.
The bank's CFO had set a target of cutting the reporting cycle to under 10 calendar days, with the work currently absorbed by manual reconciliation redirected to genuine financial analysis. The bank had previously evaluated several global regulatory-reporting platforms and concluded that wholesale platform replacement was a 24-month programme; the CFO did not have 24 months.
The approach
MindMap deployed an augmentation pattern rather than a replacement: the bank's existing regulatory-reporting platform (a customised in-house build supplemented by point vendor tools for specific returns) would continue to operate, but every input data feed, every reconciliation step, every output filing would be wrapped in an automation layer that handled the work currently consuming the team's time.
We led with four accelerators: Regulatory Reporter (Rr) as the master filing orchestrator, Data Quality Auditor (Da) for the reconciliation and data-quality layer, Financial Close (Fc) for the cross-team task coordination, and Compliance Engine (Ce) for the regulatory-rules library.
Phase one — twelve weeks — was the data-lineage mapping. We built an end-to-end lineage map from the 14 source systems through to every line item on every filed return. The lineage map was not just documentation; it was operational, persisted in a graph database and queryable by the regulatory team to answer the inevitable 'where does this number come from' question that the audit and inspection cycles generate.
Phase two was the reconciliation layer. Data Quality Auditor was configured with approximately 4,200 data-quality rules covering the various source-to-target reconciliations, the cross-system consistency checks, and the regulatory-specific calculations (RWA computation, IFRS 9 staging logic, large-exposure aggregation). Issues that the rules could resolve deterministically were auto-resolved; issues that required human judgement were routed to the relevant data-owner team with full context.
Phase three was the filing-generation layer. Regulatory Reporter generates the structured filing output for each of the bank's required returns — Basel III COREP-equivalent filings, IFRS 9 ECL disclosures, the local regulator returns across six jurisdictions — with full traceability from each filed line item back through the calculation chain to the underlying source-system data.
The pre-built building blocks
Rather than commission a ground-up build, the engagement leaned on MindMap's pre-built accelerator library — production-tested components that compress what would otherwise be a six-to-nine-month build into weeks.
Regulatory Reporter
Basel III, IFRS 9 and local-jurisdiction filing generation
Data Quality Auditor
Streaming data-quality and cross-system reconciliation
Financial Close
Cross-team task orchestration for the regulatory close
Compliance Engine
Regulatory rules library across six jurisdictions
The architecture
The platform runs on the bank's private cloud tenant inside its primary data centre in the home market, with regional data residency satisfied for each of the bank's six market subsidiaries through a federated architecture: the local data stays in-country, the consolidated returns are assembled from cryptographically-attested local extracts.
The lineage graph is held in Neo4j with a custom schema modelling source-systems, data elements, transformations, regulatory calculations and filed line items as a single connected graph. The graph is approximately 28 million nodes and 140 million edges at steady state, with daily refresh from the source systems.
The Data Quality Auditor runs as a streaming engine on Kafka — every source-system data load triggers the relevant quality rules in near-real-time rather than waiting for the month-end batch. Issues are surfaced to the data-owner teams within minutes of the source-system load, meaning that the month-end close has progressively fewer data-quality fires to fight because most of them have been resolved during the month.
Regulatory Reporter encodes the various filing templates — Basel III, IFRS 9 and the six local jurisdiction returns — as structured templates with a deterministic calculation engine for the standard regulatory formulas and a configurable adjustment layer for the bank-specific overrides. Each filing's calculation chain is fully reproducible: any line item can be expanded to show the source data, the transformations applied and the regulatory calculation logic used.
Integration with the bank's source systems uses the bank's existing data warehouse as the staging layer; we did not require any source-system change. Output filings are generated in the regulator-required formats (XBRL for the Basel filings, CSV/XML for the local jurisdiction returns) and submitted via the regulator portals using the bank's existing submission credentials.
The numbers behind the story
Regulatory-close cycle has dropped from 28 calendar days to 7 calendar days. Filings are submitted to each regulator with more time-in-hand than ever before, which has materially reduced the late-cycle pressure that had been driving error rates and team burnout.
Approximately 92% of data-quality issues that previously consumed the team's month-end time are now auto-resolved through the streaming rules engine and never reach the regulatory-reporting team. The data-owner teams in the source-system functions are now resolving issues during the month as a normal part of their operational cadence.
External audit costs related to regulatory reporting have dropped by approximately $3.1m annually — the external auditors are now spending materially less time on reconciliation walk-throughs because the lineage graph makes the data flow auditable without the previous manual evidence assembly.
The MAS's most recent inspection — the first since the platform went live — explicitly cited the bank's reporting infrastructure as a positive in the inspection report and referenced the lineage capability as a reference for other inspected institutions.
The regulatory-reporting team has not been reduced. The 35-person team has been restructured into a smaller core-reporting team and a regulatory-change team: the latter focuses on incorporating new regulatory updates into the platform as they are published, with a typical update now taking 4 to 6 weeks rather than the previous 4 to 6 months.
“The other vendors were proposing eighteen-to-thirty-month wholesale platform replacements. MindMap delivered measurable cycle reduction in twenty-eight weeks by augmenting what we had. The MAS specifically commended our reporting infrastructure in their last inspection — that has never happened in my career.”— Chief Financial Officer· ASEAN Tier-1 Bank
Why MindMap was chosen
The bank had previously evaluated three global regulatory-reporting platforms. All three required wholesale replacement of the bank's existing reporting infrastructure, with implementation timelines of 18 to 30 months and disruption profiles the CFO considered unacceptable.
MindMap's augmentation pattern — preserving the existing reporting platform and adding automation around it — was the unique proposal in the bid. We could demonstrate the pattern in production at a peer regional bank, which the bank's CFO walked through directly.
The combination of regulatory-domain expertise on the delivery team (two former regulatory-reporting heads from peer ASEAN banks) and the pre-built accelerator stack meant the bank's CFO felt confident in the 28-week delivery commitment — and the commercial alignment of milestone-based pricing with a meaningful post-go-live performance component reinforced that confidence.
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