ASIC Data Strategy 2021-26
This data strategy outlines our vision to fully harness our data assets and analytics capabilities, empowering our people to put data into action and enabling data-informed regulatory decisions.
It sets out our plans to:
- collect more and better data to systematically enhance our regulatory work
- use data to prioritise our regulatory activities
- use data to automate internal processes
- maintain high standards for privacy, information security and data governance in how we store, manage and protect data.
Introduction
We are on a path to fully harness the benefits of new and sophisticated technologies to drive more efficient, informed, and targeted regulation.
We continue to invest in technology to become a leading digitally enabled and data-informed regulator. We are especially interested in improving the way in which we collect, use and share information, and how we can use digital technologies to drive more efficient, proportionate and targeted regulation.
Good data governance is a key challenge and responsibility for us, and we are focused on ensuring we have both the staff capability and the technological safeguards to enable and support effective data governance standards.
Implementing the ASIC Data Strategy 2021–26 will continue to transform the way we work and help us realise our vision for a fair, strong and efficient financial system for all Australians.
Purpose
ASIC’s data strategy:
- states our vision to harness data and analytics at ASIC
- outlines our target state for data and analytics at ASIC
- defines our five data success factors for achieving our target state
- explains the programs of work we will undertake to achieve our target state
- describes how we will measure progress towards our target state.
By successfully executing the strategy, we will:
- renew and deepen our commitment to uplifting our data capabilities
- be able to perform our regulatory duties more efficiently and effectively
- foster a data-informed culture and continue to build the frameworks and capabilities to support future data and analytics use cases.
Our vision
Fully harness our data assets and analytics capabilities and empower our people to put data into action and make good regulatory decisions
Our success factors
- Data driven culture
- Efficient and effective data governance
- Robust data and analytics capability
- Trusted, secure and valued data sets
- Fit for purpose data and analytics tools.
Value proposition
- Providing ASIC with a low-friction data experience that delivers:
- Visibility of available data sets
- Safe access to trusted data assets
- Outcome-driven data and analytics services
Target state
What does good look like for ASIC?
Operationalisation and ongoing experimentation with new datasets, technologies and analytic techniques to enhance ASIC's supervisory and regulatory activities.
Collect newer, better data
- Real-time monitoring
- Integration with regulated entities’ systems
- Machine readable regulation
- Data sharing between government agencies
- Natural language processing (NLP) for documents, audio, video and image data
Store, manage and protect data
- Centralised, cloud-based big data storage and processing
- Machine learning to detect faulty or incomplete data
- Integration of related data
- Robust information security
- Mature data governance, privacy and ethics practices
Use data to enhance priority activities
- Machine learning for risk scoring and categorisation
- Early detection of fraud and emerging threats and harms
- Enhanced auditing of market conduct
- NLP to audit promotional material and prospectuses
- Policy simulations
Use data to automate internal processes
- Automated data processing (integrated datasets, workflows and dashboards)
- Automated reporting (internal and external)
- Automated licensing and registration processes
Data success factors
To achieve our target state, our data strategy outlines five success factors that will drive a strong data culture while uplifting our data quality, capability and platforms.
|
Data success factors |
Definition |
Long-term objectives |
|---|---|---|
|
Data-informed culture |
A culture that recognises the value of data and analytics, where staff are curious about how they can realise the full value of data to improve outcomes for ASIC and our stakeholders. |
Foster positive cultural change. Co-define ‘What’s in it for me’ use cases to demonstrate the value of data assets and capabilities in everyday work. Increase awareness of data holdings and service offerings. |
|
Efficient and effective data governance |
End-to-end lifecycle management of data as a strategic asset, including data governance and management practices to create secure data sets that are readily discoverable and consumable by authorised users. |
Revise the Data and Information Governance Framework. Review effectiveness of data decision-making fora and data controls. |
|
Robust data and analytics capability |
Equipping and empowering people with the data skills and capabilities to realise the full value of data, including a comprehensive set of skilled staff and supportive organisational functions. |
Assess current data and analytics capability maturity. Identify uplift priorities for capabilities and skills. Develop learning opportunities to continue growth of data literacy. |
|
Trusted, secure and valued data assets |
Providing staff with the right data, in the right format, in the right place and at the right time to enable them to make more effective decisions. We will broaden access to data while protecting privacy and security. |
Maintain an Enterprise Data Model and data catalogue. Define and measure the value of core data sets. Explore ways to make more trusted data sets accessible from internal and external sources through ASIC’s enterprise data infrastructure. |
|
Fit-for-purpose data infrastructure and analytics tools |
Empowering ASIC staff and data specialists to turn data sets into actionable insights through the right ecosystem of technologies and tools including sourcing, storage, aggregation, analysis and visualisation. |
Continue leveraging ASIC’s enterprise data infrastructure. Implement high-priority use cases that deliver long-term value and/or ‘no regret’ outcomes. |
Programs of work
We will achieve our success factors through five programs of work:
- Break down silos and barriers
- Enrich our data profiles of regulated entities and their industry environment
- Build confidence and trust in our data
- Create a faster path to decisions and actions
- Standardise our data environment
1. Break down silos and barriers
Unlock data and organisational knowledge siloed within teams and systems to fully leverage data assets.
Key projects:
- Projects to uplift ASIC’s data operating model – including developing a data service catalogue, service level agreements and self-service tools – and develop data literacy through training plans and change management.
- ASIC Data Dictionary, detailing an enterprise data and metadata model to govern the way ASIC teams read, use, interpret and communicate data.
- ASIC Knowledge Finder, providing a central enterprise information portal for ASIC team members.
- Connected Workforce, aimed at connecting ASIC teams through shared knowledge, automation, smart alerts and workflow management.
Key objectives
- Make data discoverable and consumable across teams through an ASIC data dictionary and knowledge sharing.
- Integrate systems to give ASIC staff a comprehensive view of external and internal work to drive efficiencies and enable operational reporting.
- Uplift ASIC’s data operating model and data literacy to empower staff to make data-informed decisions.
2. Enrich our data profiles of regulated entities and their industry environment
Collect and surface up-to-date insights on the entities and markets we regulate, arming our regulatory teams with information that is easy to use, understand and verify.
Key projects
- Recurrent Data Collection, collaborating with industry to phase in more frequent and more granular reporting of financial services data. Includes capability for external data sharing.
- Entity and Adviser 360, collating all information collected by ASIC about each regulated entity including relevant interactions, insights and relationships.
- Market and Industry Insights, developing a centralised solution for extracting real-time market and industry data from relevant external sources and structuring for internal consumption, reporting and analysis.
Key objectives
- Provide a comprehensive, user-friendly view of all the information ASIC collects on entities and the industries and markets in which they operate.
- Correlate market and entity data to strengthen our understanding of the regulated population.
- Harness recurrent and timely data collection for internal and external users, improving speed-to-insight and timely detection of threats and harms.
3. Build confidence and trust in our data
Roll out data quality and access solutions for internal and external users.
Key projects
- Data Quality Improvement, collecting and profiling ASIC reference data to improve consistency across the organisation.
- ASIC Service Portal, a one-stop-shop to publish relevant and reliable information for the public and enable enquiries.
Key objectives
- Embed data standards to ensure quality, completeness, accuracy, availability and timeliness of data to drive data-led decision making.
- Promote confident and informed participation in the financial system by facilitating requests and delivering valuable insights to the regulated population and consumers.
4. Create a faster path to decisions and actions
Leverage analytics, insights and automation to increase organisational responsiveness.
Key projects
- ASIC Business Insights, implementing standardised, user-friendly data visualisation interfaces.
- Digital Agents, enabling artificial intelligence (AI) and cognitive automation capabilities to reduce human intervention during data capture and analysis.
- Smart Monitoring, implementing automated detection and reporting to intervene in potentially harmful behaviours.
- Rapid Value Factory, an ongoing program of work to deliver ‘quick win’ data solutions to facilitate efficiency gains.
- Agency Knowledge Exchange, providing an efficient and secure platform for data exchange and inter-agency collaboration.
Key objectives
- Expose cross-organisation data assets to support seamless data exploration and reporting.
- Leverage our investments in regulatory technology (regtech) and supervisory technology (suptech) with smart monitoring and risk-scoring tools.
- Increase automation of data capture and analysis.
- Enhance data sharing between local and international regulators.
5. Standardise our data environment
Establish a strong data foundation, architecture and operating model to guide, direct and govern the delivery and outcomes from our data portfolio
Key projects
- Advanced Analytics Foundation, implementing AI and machine learning (ML) capabilities to support risk scoring, triage and analysis of regulated entities’ transactions and relationships.
- Data Consumption Foundation, deploying a standard suite of business intelligence and analytics tools and training to support self-service reporting and visualisation.
- Data Integration Foundation, implementing AI and ML to facilitate the use of data and insights in ASIC business applications workflows and processes, as well as efficient and secure data exchange capabilities with other entities, agencies and the public.
- Data management, movement and security foundations, introducing standards for data quality and access.
Key objectives
- Establish the architecture for storing, managing, exploring, and moving data.
- Introduce advanced analytics to optimise document analysis, indexing and triage, and integrate data analytics into standard ASIC business processes.
- Implement a centralised data security and policy management solution.
Measure of success
We will continuously measure our progress against five data success factors.
|
Data success factors |
Proof points |
Potential measures |
|---|---|---|
|
Data-informed culture |
Increased awareness and adoption of data assets and services Growth in ‘What’s in it for me’ use cases Successful delivery of data and analytics projects Proactive data champions network |
Growth in the number of use cases identified, funded and implemented Data accessibility and usage Percentage of ASIC staff using data and analytics tools and methods Realisation of data and analytics use cases, and project benefits |
|
Efficient and effective data governance |
Aligned business and data performance measures Data decision rights and responsibilities clearly defined Clearly documented data controls, rules and governance Compliance with data governance frameworks Participation in data decision-making forums |
Number of data policy or governance-related exceptions, variations or non-conformances Data service catalogue and service levels defined Percentage of data policies documented and actively enforced Alignment of data and business performance measures Effectiveness of data decision-making forums Chief Data and Analytics Office service level performance |
|
Robust data and analytics capability |
Acquisition and retention of new data capabilities and skills Fit-for-purpose skills and capabilities as required to meet business needs Active engagement of staff in data training and development programs |
Uplift in high-priority data capability maturity levels Reduction in vacancy duration and employee turnover for key data positions Data and analytics training offerings and participation Percentage of team members with talent development plans |
|
Trusted, secure and valued data sets |
Increased quality of data sources, including detailed metadata and documentation Growth in availability and usage of existing and new data sources Reduced manual effort absorbed in data preparation activities Compliance with ASIC security and regulatory obligations |
Business colleague satisfaction rating (episodic and transactional) Percentage of data sets proactively registered, classified, audited and quality-managed Uptake and utilisation of Chief Data and Analytics Office services Increased volume and reuse of common data sets Reduction in effort spent on data sourcing and preparation |
|
Fit-for-purpose data and analytics tools |
Increased availability and utilisation of data and analytics tools Sturdy and flexible technology foundations to support new data use cases Efficient and effective utilisation of budget allocations |
Data and analytics projects delivered to scope, on time and at budget Performance tracking against data and analytics strategy and roadmap Increased reuse of common data assets and tools Total data and analytics funding against industry benchmarks |
More information
For more information about our data work, digital future and organisational priorities, refer to the ASIC Corporate Plan.
Feedback
If you have feedback or if you wish to reproduce any material from this document, send a request by email to feedback@asic.gov.au.
