# ASIC AFSL Growth & Adviser Movement Signals (`starshaped_bullsnake/asic-afsl-growth-adviser-movement-signals`) Actor

Produce recent AFSL-level adviser movement and new-licensee signals from official ASIC open-register data.

- **URL**: https://apify.com/starshaped\_bullsnake/asic-afsl-growth-adviser-movement-signals.md
- **Developed by:** [Starshape Tools](https://apify.com/starshaped_bullsnake) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $20.00 / 1,000 afsl movement signals

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## ASIC AFSL Growth & Adviser Movement Signals

Produces deterministic, licence-level commercial signals from the Australian Securities and Investments Commission (ASIC) open registers published on [data.gov.au](https://data.gov.au/). One Dataset item represents one Australian Financial Services Licence (AFSL) with at least one enabled signal.

### Signals

- `ADVISERS_GAINED`: an ASIC Financial Adviser appointment start date occurred in the inclusive signal window.
- `ADVISERS_LOST`: an appointment end date occurred in the inclusive signal window.
- `NEW_LICENSEE_COMMENCED`: the AFS licence start date occurred in the inclusive signal window.

These are register appointment movements, not verified employee headcount. An adviser may both join and leave during the same window. The Actor exposes no adviser names or adviser numbers; only AFSL-level aggregate counts are returned.

### Data and timing

The Actor uses only the current **ASIC Financial Advisers Dataset** and **ASIC Australian Financial Services Licensee Dataset** packages published on data.gov.au. Their point-in-time snapshots are normally updated weekly. It resolves the current downloadable resources from data.gov.au package metadata at runtime and does not scrape individual ASIC webpages.

Although the resources are described as CSV, ASIC documents TAB-delimited content. The Actor detects TAB from each header and accepts comma-separated content only as a compatibility fallback. Required headers are validated before processing.

By default, the window covers the most recent 30 calendar days relative to the earlier official source snapshot date. Both endpoints are inclusive. If the two snapshots differ by more than seven days, the run fails with `SOURCE_SNAPSHOT_SKEW` rather than combining mismatched versions.

### Input

```json
{
  "lookbackDays": 30,
  "maxItems": 100,
  "includeAdvisersGained": true,
  "includeAdvisersLost": true,
  "includeNewLicensees": true,
  "states": []
}
```

`states` filters the AFS licensee principal-business state; an empty array includes all states and territories. No login, API key, proxy, credentials, comparison baseline, or historical snapshot crawl is required.

### Output

Results are ranked deterministically, prioritizing newly commenced and growing licensees. `SUMMARY` in the default Key-Value Store records source dates, row and event counts, filters, exclusions, limits, resource details, delimiter detection, and duration. Summary rows are never mixed into the default Dataset.

The Financial Adviser source is rejected with `ADVISER_DATA_SANITY_FAILED` if a nonempty download does not contain usable role statuses, current appointments, start dates, and licence numbers. `SUMMARY` exposes aggregate-only parsing diagnostics; it never includes adviser-level values.

Repeated runs against the same source snapshots and input produce identical Dataset content, including stable SHA-256 `signalId` values. The output `scrapedAt` is anchored to the reference snapshot date to preserve that reproducibility.

### Attribution and licence

Source data is attributed to the Australian Securities and Investments Commission (ASIC) and data.gov.au. Reuse is subject to the licence stated on the relevant data.gov.au dataset pages (commonly Creative Commons Attribution 4.0); users should review the current package metadata and attribution requirements.

# Actor input Schema

## `lookbackDays` (type: `integer`):

Calendar days before the official source snapshot date, inclusive of both window endpoints.

## `maxItems` (type: `integer`):

Maximum ranked AFSL signals written to the default Dataset.

## `includeAdvisersGained` (type: `boolean`):

Include appointment-start signals in eligibility, counts, and change types.

## `includeAdvisersLost` (type: `boolean`):

Include appointment-end signals in eligibility, counts, and change types.

## `includeNewLicensees` (type: `boolean`):

Include licence-commencement signals in eligibility and change types.

## `states` (type: `array`):

Empty selects all. Filters on the licensee principal-business state.

## Actor input object example

```json
{
  "lookbackDays": 30,
  "maxItems": 100,
  "includeAdvisersGained": true,
  "includeAdvisersLost": true,
  "includeNewLicensees": true,
  "states": []
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("starshaped_bullsnake/asic-afsl-growth-adviser-movement-signals").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("starshaped_bullsnake/asic-afsl-growth-adviser-movement-signals").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call starshaped_bullsnake/asic-afsl-growth-adviser-movement-signals --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,starshaped_bullsnake/asic-afsl-growth-adviser-movement-signals"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/vEySDtUueJar8x3dk/builds/J9ZPiUcsxso47CaCe/openapi.json