Description

A focused course, tailored for you

Regulatory Reporting Data Architecture for Investment Banks

Build the end-to-end data pipeline that takes trade-level positions to APRA-ready submissions without last-minute reconciliation firefights.

Every quarter the same variance surfaces on the ARF 180 or the SRF 330. You trace it through the trade-capture system, then the P&L aggregation, then the reporting layer. The number is defensible but the audit trail to defend it takes two days to reconstruct. APRA granular reporting reforms make that two-day scramble a permanent liability.

$199 one-time

Tailored to your situation. Access within 24 hours. 30-day money-back.

Includes a hand-built implementation playbook delivered alongside course access, generated for your specific situation.

Why this course

Regulatory reporting at an investment bank sits at the intersection of front-office position data, finance ledger data, and prudential submission formats, and none of those three systems were built to talk to each other. The ARF/ARS form suite expects a level of granularity that the legacy aggregation layer was not designed to produce. When APRA or an internal auditor asks for the trade-level support behind a capital adequacy figure, the reporting team either rebuilds the calculation on the fly or escalates to technology for an ad hoc extract. Neither answer scales. The solution is not more headcount at quarter-end; it is a data architecture decision made upstream, at the point where trade data is first captured for regulatory purposes, with documented lineage at every aggregation step.

What you walk away with

Map every data flow from trade capture to prudential submission with lineage documentation an APRA examiner can follow.
Design aggregation checkpoints that isolate the source of a variance to a specific system boundary, not a two-day investigation.
Build reconciliation controls that close automatically at each aggregation layer before the submission is prepared.
Produce an ARF/ARS submission package where every figure traces to a documented source extract, not a manual adjustment.
Implement a data-quality gate that flags granular reporting anomalies before they reach the return preparer.
Hand off a repeatable submission workflow that a new team member can run without institutional knowledge of prior quarter workarounds.

The 12 modules

Module 1. The Regulatory Reporting Data Problem

Maps the structural gap between how investment banks capture trade data and what APRA granular reporting actually requires. Covers the ARF 180, SRF 330, and ARS 115 as case studies in where legacy aggregation architecture breaks down. By the end of this module you will have named every handoff point in your current pipeline where lineage is lost and variance is born.

Module 2. APRA Granular Reporting Requirements in Practice

Translates APRA's granular data reporting reforms from policy documents into data structure requirements. Covers the attributes APRA expects at the instrument level versus the portfolio level, the tolerance thresholds that trigger examiner queries, and the difference between what the published form instructions say and what the review team actually asks for during a targeted review. Worked example: building the attribute map for an ARS 117 capital adequacy return.

Module 3. Trade-System Extract Design

Covers how to specify a trade-system extract that carries the regulatory attributes APRA needs, not just the attributes the trading desk tracks. Includes a template for the extract specification document, guidance on working with technology to include regulatory flags at booking time rather than mapping them retrospectively, and a checklist for validating that the extract covers every instrument type on the reporting scope.

Module 4. Aggregation Layer Architecture

Walks through the design of an aggregation layer that accumulates trade-level data into the form-level totals APRA receives, with a documented audit trail at each step. Covers the three common aggregation patterns used in Australian bank reporting environments, the trade-offs between each, and the lineage documentation format that satisfies both internal audit and APRA examiner review. Includes a worked reconciliation trace from instrument to submission line.

Module 5. Reconciliation Control Design

Builds a reconciliation control framework where each aggregation boundary has an automated check that compares input totals to output totals before the data moves to the next layer. Covers the control types APRA expects to see documented in a self-assessment: completeness controls, accuracy controls, and cut-off controls. Provides templates for the reconciliation log that the reporting team signs off on each submission cycle.

Module 6. Finance Ledger to Prudential Return Mapping

Addresses the specific problem of joining P&L ledger data to prudential return line items where the chart of accounts does not map cleanly to the regulatory classification. Covers the mapping table structure that supports a clean audit trail, how to document and justify reclassifications, and the governance process for updating the mapping when accounting standards or APRA instructions change. Works through a capital return example where ledger balances require adjustment for regulatory purposes.

Module 7. Variance Analysis Workflow

Replaces the end-of-quarter two-day variance investigation with a structured workflow that isolates discrepancies to a specific system boundary within two hours. Covers the variance root-cause taxonomy used by experienced regulatory reporting teams, the escalation decision tree for material versus immaterial variances, and the documentation standard that satisfies APRA's expectation of robust variance explanation. Includes a template for the variance commentary that accompanies the submission.

Module 8. Data Quality Gates Before Submission Preparation

Designs automated data-quality checks that run on the granular data before it reaches the return preparer. Covers the check types that catch the errors most commonly flagged by APRA during targeted reviews: attribute completeness, instrument classification consistency, counterparty identifier integrity, and cut-off alignment. Provides a prioritised checklist ordered by the frequency with which each check type prevents a post-submission query.

Module 9. Examiner-Ready Documentation Package

Builds the documentation set that APRA expects to find when they conduct a targeted review of a prudential return: the submission basis paper, the reconciliation pack, the lineage diagrams, and the key assumptions log. Covers the level of detail that satisfies an examiner versus the level that triggers follow-up questions, with examples drawn from the ARS 115 and SRF 330. Provides a documentation template that the reporting team populates each submission cycle.

Module 10. Managing Technology Requests for Regulatory Uplift

Covers how to write a technology change request for a regulatory reporting data uplift that gets prioritised against competing trading-system and finance-system projects. Includes a business-case template that quantifies regulatory risk in terms technology governance committees respond to, a phased delivery approach that delivers risk reduction before the full architecture is in place, and a requirements document structure that reduces the number of clarification rounds with the development team.

Module 11. Ongoing Submission Cycle Operations

Turns the architecture built in earlier modules into a repeatable submission cycle that does not depend on institutional memory held by one team member. Covers the submission calendar management across multiple returns, the pre-submission checklist that covers every control point, the handoff protocol when the primary preparer is unavailable, and the post-submission review that feeds improvements back into the data quality gate design.

Module 12. Regulatory Change Impact Assessment

Provides a framework for assessing the data architecture impact of an APRA reporting reform or a new return before the implementation deadline. Covers the gap analysis methodology that maps existing data flows to new requirements, the stakeholder engagement sequence that gets technology and front office committed to delivery timelines, and the parallel-run approach that validates the new data pipeline against the legacy submission before cutover.

How this addresses your situation

Specific modules that map to what you said you are dealing with.

Quarter-end ARF 180 variance that traces across three systems maps to Modules 5 and 7.

APRA granular data reporting reform requiring instrument-level attributes maps to Modules 2 and 3.

Internal audit request for submission lineage documentation maps to Modules 4 and 9.

Technology change request for regulatory data uplift that keeps losing prioritisation maps to Module 10.

What you get with this course

12 written modules covering the full trade-to-submission data pipeline
Extract specification template for trade-system data pulls
Aggregation layer lineage documentation template
Reconciliation control log template signed off each submission cycle
Variance root-cause taxonomy and documentation standard
APRA examiner-ready documentation package template
Data quality gate checklist ordered by examiner query frequency
Regulatory change impact assessment framework
Hand-built implementation playbook delivered alongside course access

What you will have in hand by Day 1, Week 1, Month 1

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.

Before and after

Before

The ARF 180 variance surfaces at T-3 days before submission deadline. Two days of cross-system trace work to reconstruct the lineage. The submission goes in on time but the audit trail is rebuilt from scratch each quarter and lives in someone's head.

After

The aggregation layer produces a reconciliation pack at each checkpoint. Variances isolate to a system boundary within two hours. The examiner-ready documentation package exists before the submission is prepared, not after a review request arrives.

What happens if you do not address this

APRA's granular data reporting reforms are not optional and the implementation timelines are fixed. A reporting team that has not restructured its data pipeline to produce instrument-level attributes with documented lineage will face increasingly frequent targeted reviews, post-submission queries, and the reputational risk of a reportable breach when a material error is found after submission.

Who it is for

You are a regulatory reporting professional at an investment bank or large financial institution, responsible for producing prudential returns to APRA, ASIC, or equivalent regulators. You have deep knowledge of what the forms require but limited control over the upstream systems that feed them. You are the person who catches the discrepancy, owns the reconciliation, and signs off on the submission.

Who this is NOT for. Compliance officers focused on conduct obligations rather than prudential data. Technology architects with no regulatory reporting background who want a purely technical data-engineering course. Retail banking reporting teams whose submissions are simpler than the capital and liquidity returns covered here.

How it arrives

Text-based course in the Art of Service learning environment, plus downloadable templates and worked examples for every module, plus the hand-built implementation playbook delivered alongside course access.

Time investment. Each module is designed to be completed in one focused work session of 45-60 minutes. The full course runs across 12 modules. The templates in each module are working documents, not reading material, so the time investment includes the first pass of populating them against your own data environment.

Why $199 is the right number

External consultants charge $15,000 to $40,000 for a regulatory data architecture review that produces a recommendation document, not a working pipeline. Internal technology projects for regulatory uplift typically take 12-18 months from business case to delivery. This course gives the reporting team the architecture knowledge and the working templates to design the right solution, write the right technology request, and validate the delivered system, without waiting for a consulting engagement or a technology queue.

FAQ

Does this course cover both APRA returns and ASIC reporting obligations?

The data architecture principles, lineage documentation methods, and reconciliation control design apply to any regulatory submission that requires granular source data. The worked examples are drawn from APRA prudential returns because that is where Australian investment bank reporting complexity is highest, but the framework translates directly to ASIC derivative reporting and RBA requirements.

My team uses a third-party regulatory reporting platform. Is the course still relevant?

Yes. The course covers the data architecture decisions that sit upstream of the reporting platform: what the extract from trade systems carries, how the aggregation layer is structured, where reconciliation controls sit. Platform-specific configuration is downstream of those decisions. Teams using any major reporting platform will find the lineage documentation and reconciliation control modules directly applicable.

What is the implementation playbook?

The implementation playbook is a hand-built document prepared for the specific reporting context described in the course enrolment. It maps the course framework to your organisation's reporting scope, identifies the highest-priority architecture decisions to make first, and provides a sequenced action plan for the first 90 days of implementation. It is delivered alongside course access, not at the end of the course.

30-day money-back guarantee. If after a week of working through the materials this is not what you needed, reply to the receipt email and a full refund is processed. No questions, no forms.

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.