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.