We extract ABN profiles, Annual Information Statements (AIS), responsible persons, and enforcement actions from the ACNC. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Charity Profiles objects from acnc.gov.au. All fields typed and schema-versioned.
"abn": "11005357522", "charity_name": "Australian Red Cross Society", "charity_size": "Large", "registration_date": "2012-12-03", "dgr_status": true, "operating_status": "Registered", "website": "www.redcross.org.au"
| # | abn | charity_name | other_names | charity_size | registration_date | dgr_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Financial Data (AIS) objects from acnc.gov.au. All fields typed and schema-versioned.
"abn": "11005357522", "reporting_year": 2023, "total_revenue": 845000000.0, "total_expenses": 842000000.0, "net_surplus": 3000000.0, "government_grants": 412000000.0, "employee_expenses": 380000000.0
| # | abn | reporting_year | total_revenue | total_expenses | net_surplus | total_assets |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Responsible Persons objects from acnc.gov.au. All fields typed and schema-versioned.
"abn": "11005357522", "person_name": "John Smith", "position": "Board Member", "appointment_date": "2019-11-15", "is_active": true, "board_role": "Director", "related_entities": 2
| # | abn | person_name | position | appointment_date | cessation_date | related_entities |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Operations & Beneficiaries objects from acnc.gov.au. All fields typed and schema-versioned.
"abn": "11005357522", "main_activity": "Emergency Relief", "operating_states": "['NSW', 'VIC', 'QLD', 'WA', 'SA', 'TAS', 'ACT', 'NT']", "employee_count": 2450, "volunteer_count": 15000, "beneficiary_types": "['General community in Australia', 'Victims of disaster']"
| # | abn | operating_countries | operating_states | main_activity | beneficiary_types | volunteer_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Compliance & History objects from acnc.gov.au. All fields typed and schema-versioned.
"abn": "11005357522", "compliance_status": "Up to date", "reporting_overdue": false, "enforcement_action": "None", "action_date": "None", "revocation_date": "None", "revocation_reason": "None"
| # | abn | enforcement_action | action_date | action_summary | revocation_date | revocation_reason |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our ACNC scraper handles WAF rate limits, complex search session states, and unstructured PDF financial reports. We convert regulatory filings into queryable databases.
Extract ABN, legal name, aliases, registration date, and charity size across the entire 60,000+ entity catalogue.
Parse structured financial data from the Annual Information Statement, including revenue, expenses, assets, and liabilities.
Track Deductible Gift Recipient (DGR) endorsements and tax concessions linked to each registered entity.
Extract board members, trustees, and directors. Map individuals across multiple charity boards to identify network clusters.
Download attached financial reports and apply OCR to extract key metrics from unstructured audited statements.
Monitor changes in compliance status, overdue reporting flags, and formal enforcement actions issued by the ACNC.
Categorise charities by target demographics, main activities, and operating locations down to the state or territory level.
Capture historical AIS filings to build longitudinal financial models of non-profit sector growth.
Run pipelines monthly to capture new registrations, board changes, and fresh financial filings without re-processing the entire register.
Brief in. Clean data out.
Specify target segments by charity size, state, DGR status, or provide a list of ABNs. We map the extraction schema.
We configure Scrapy crawlers, handle ACNC session cookies, implement rate limiting, and build PDF parsing logic.
Schema validation, cross-checking financial totals, and null-rate monitoring before production deployment.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on your required cadence.
Government portals prioritise stability over accessibility. Here is how we extract ACNC data reliably without triggering WAF blocks.
Government firewalls block aggressive crawling. We enforce strict per-IP concurrency limits and randomised delays, distributing requests across Australian IP pools to maintain access without degrading site performance.
The ACNC advanced search relies on complex viewstates and session cookies. Our crawlers maintain persistent sessions and handle form hydration to paginate deep into search results without losing context.
Many charities submit financial data as scanned PDFs rather than structured web forms. We download attachments, apply Tesseract OCR, and use heuristic parsing to extract revenue and expense lines from unstructured tables.
Reporting requirements change over time. We map historical AIS fields to a unified modern schema, allowing you to query 2014 financial data alongside 2023 filings without writing custom transformations.
Names are entered inconsistently. We extract responsible persons and apply normalisation rules to help you track individuals across multiple non-profit boards accurately.
Software vendors and service providers target non-profits based on revenue size, employee count, and technology budgets.
Philanthropic foundations verify compliance status, DGR endorsement, and financial health before approving grant funding.
Universities analyse sector-wide financial trends, volunteer participation rates, and the economic impact of charities.
Financial institutions ingest ACNC data for KYB (Know Your Business) processes and to monitor enforcement actions.
Private banks identify high-net-worth individuals and influential directors serving on major charity boards.
State and federal agencies track service delivery gaps by mapping charity operating locations and beneficiary types.
"The ACNC register holds the financial reality of Australia's non-profit sector, but accessing it systematically requires navigating strict WAFs and unstructured filings."
Extracting charity data at scale involves more than simple HTTP requests. You must handle complex pagination, parse legacy PDF financial reports, and map responsible persons across multiple entities. DataFlirt manages the extraction, normalisation, and delivery, so your analysts can focus on due diligence rather than writing custom parsers.
Everything supported by our acnc.gov.au scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright manages complex ASP.NET session states and viewstate hydration required for deep search pagination.
Pipelines integrate Tesseract OCR and PyPDF2 to download, parse, and extract structured tables from scanned annual reports attached to charity profiles.
Pipelines run on AWS ECS. Airflow handles monthly scheduling for AIS updates. All state and historical diffs are stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About acnc.gov.au scraping, legality, and pipeline operations.
Ask us directly →Yes. The ACNC Charity Register is a public database designed for transparency. DataFlirt extracts only publicly available information. We adhere strictly to rate limits to ensure we do not disrupt government infrastructure.
Charities submit their Annual Information Statements at different times depending on their financial year. We typically run ACNC pipelines on a monthly cadence to capture new registrations, board changes, and recent AIS filings.
Yes. While basic financial metrics are available in the web-based AIS, detailed audits are often uploaded as PDFs. We download these attachments and use OCR to extract specific line items, though accuracy depends on the quality of the scanned document.
We capture the 'appointment date' and 'cessation date' for responsible persons as listed on the registry. By running periodic pipelines, we build a timeline of board composition changes.
We extract the ABN directly from the ACNC profile. If required, we can cross-reference this with the Australian Business Register (ABR) to append additional corporate structure data.
We support full-register extractions (approx 60,000 entities) or targeted subsets based on specific criteria (e.g., all charities in Victoria with revenue over $1M). Contact us with your parameters for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off database of all registered charities or a monthly feed of financial filings, we build and operate the pipeline. Tell us what you need.
