Transitioning to a dataset-based APRA reporting process in ADI's

The Australian Prudential Reporting Authority (APRA) is increasing the granularity, quality and velocity of data collections in the ADI industry. APRA is expecting entities to have in place the framework, policies and procedures, and systems and controls that ensure consistent high-quality data is reported to the regulator. Organisation need to ensure that they have in place a fit for purpose governance model to address APRA’s expectations around accountability, transparency, and improved operational agility in the entities it regulates. Below are some observations that highlight the direction APRA is taking in relation to ADI industry data and associated data governance policies.



In addition, as part of APRA’s data strategy, in recent months there has been a significant increase in granular data collection requests from APRA. Most recent examples such as ARS 220 Data Quality, ARF923.5 Residential Mortgage Lending activity, the COVID19 Reporting Cube data set submission highlight that the shift in APRA’s data collection approach i.e. going from "Return-based" data collection to "Dataset-based" collection is gaining pace.


Dataset-based collections requested by APRA to-date have typically involved collation of data points from different departments such as Finance, Risk and Treasury. Some of these data points are already being submitted to APRA in various existing returns at an aggregate level. Most organisations today have their regulatory reporting controls and governance layers on the aggregated returns and reports, managed by the regulatory reporting teams. However, with the introduction of granular dataset based collections, the Regulatory reporting team will find it increasingly challenging to solely own the review and ultimately sign off and submission of datasets to APRA. Collaboration across the different teams that own the data and understand it intimately will become increasingly crucial to ensure accurate and complete submission to APRA. The diagram below provides a high-level overview of the various regulatory requirements of financial institutions and the inter-relationships with different departments such as Finance, Risk and Treasury.



In recent years, APRA has increased its focus on ensuring regulated entities have appropriate data governance in place and accountabilities are clearly defined within the organisation for data management. Effective governance, risks and controls in place for maintaining Data quality and Data risk management is an area that is increasingly being scrutinised by APRA. A data risk management standard (CPS-235) has been flagged by the regulator for some time now, and many entities are working through the establishment of Data Governance on their Critical Data Elements.


Financial institutions require transformational change as the current legacy technology platforms, tools, and data capabilities are inadequate and will not scale to meet the various customer, business, and regulatory demands. One of the biggest challenges faced by organisations is the need to take a more holistic approach to deliver across multiple initiatives that are currently in flight. Embedding a fit-for-purpose Governance framework is critical to meet your regulatory reporting obligations.


Challenges for Regulated Entities

Specific regulatory requirements such as ARS 220 (Credit Quality) and ARS 923.5 have revealed the need to report granular data that integrates Credit Risk (eg. RWA in compliance to APS 112 & 113), AASB 9 provisions, and EFS categorisation in one granular dataset submission. The recent finalisation of the reporting Taxonomies for Superannuation Data Transformation (SDT) provide a glimpse of how APRA will start collecting tabular data sets in APRA Connect, APRA’s new data collection platform that went live in September 2021, across the wider industry.


These requirements pose a real challenge to ADIs, because the current return preparation and governance processes are largely designed around independent return preparation silos. Most organisations have not established common data quality processes across the disciplines of Risk, Finance and reporting.



How we can help

Entities should strive for an integrated approach to managing common data elements across the various reporting obligations to ensure data reconciliation and quality at the most granular level, with an emphasis on establishing or expanding the role of dedicated data owners.



Governance framework for Regulatory reporting will require detailed review and redesign to ensure the accountabilities are better distributed across functions that own the data, the processes re-engineered to ensure the right people equipped with the best knowledge execute the relevant step in the process. Given APRA is already collecting granular data set from organisations as noted previously, this shift in governance approach is an immediate and critical need for organisations to ensure compliance.


RegCentric can help your organisation in this transition to a more data-focused reporting process and governance framework. Leveraging on RegCentric’s subject matter expertise in Risk, Regulation and Data, we will be able to help establish and analyse your current state, recommend pragmatic and achievable goals for the future state, and execute against these goals.



Contact us us today to organise an obligation-free discussion with our experts.

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