📁 Download 💿 189 , 💿 190 and 💿 491 s56 to grants data. There...

We have added WEEKDAY name field to the exported files.

Check out this grant estimate of my profile from gemini https://g.co/gemini/share/2d4deab581e2

From claude https://claude.ai/public/artifacts/6c1013a4-abd4-4587-a3e5-22ac67c46fc7

Great. Can you provide same kind of data for the Visa grants for 190 pattern with GPT prompt? (not after s56)

Would be great to have also data for s56 awaiting grant that way you could see where you are.

Prompt

You are a data analyst studying trends in Department of Home Affairs (DHA) decision-making for visa applications. You are given two datasets in the attached file separated by headers. One dataset shows when applicants received their visa grants after receiving an S56 request. The other dataset has details of applicants that are waiting for the grants after receiving the S56. An S56 request (or an RFI (Request for Further Information) request) is a request raised by DHA for more documents, police checks, medicals, etc.

Your primary objective is to help me understand the strategy and pattern DHA is currently following such as which types of applicants are being processed faster, what kinds of S56 requests are more common and how long DHA usually takes to finalize the cases after receiving the requested documents, by analysing the relevant datasets provided and generating insights.

Your secondary objective is to utilise the generated insights to identify how many applications with attributes similar to mine are waiting to receive their grants and estimate an approximate grant window for my application.

The details of my application are provided in the next section.

My Profile

PASTE YOUR PROFILE TEXT HERE

Task

Execute the following steps in order:

1. Identify DHA's current processing pattern From the dataset (where applicants received their grants), look for visible trends in how DHA is finalising grants:

   • Which occupations or industries are being cleared first (ICT, Engineering, Healthcare, etc.)?
   • Are onshore cases being granted faster than offshore?
   • Are certain countries (India, Pakistan, others) moving faster?
   • Which types of s56 (medical, PCC, form 80) lead to quicker outcomes?
   • Has there been a shift in speed over recent months (e.g., faster grants in Oct 2025 vs Sept 2025)?

   Summarise these insights clearly using visuals (bar charts, line charts, etc.)

2. Find similar applicant clusters based on my profile
   Next, find applicants in both datasets who are most similar to my profile:

   • Same visa subclass.
   • Same onshore/offshore status.
   • Same or nearby country.
   • Similar occupation family.
   • Same type of S56 (medical, PCC, mixed or other).

   If there aren't enough exact matches, expand to the nearest cluster (e.g., all offshore ICT roles).

3. Summarise observed timelines
   For the cluster identified in step 2,

   • Identify how many days DHA typically takes between s56 and grant (where applicants received their grants).
   • Report the most common, still normal, and less common but possible timelines.
   • Report the number of applications pending grant after receiving the S56 request. Include relevant insights like the commonly requested S56 type, the age of the application after receiving the most recent S56 request.
   • Avoid technical terms like "percentiles" - just express these as human-readable time ranges.

   Summarise these insights clearly using visuals (bar charts, line charts, etc.)

4. Give an estimated grant window
   Using my profile's data, translate those time ranges into real calendar dates, with three levels:

   • Most Likely - Where DHA finalised most similar cases. An example wording would be "Most applicants like you were granted within 1-2 weeks after s56."
   • Still Normal - Where slower cases were finalised. An example wording would be "Some took 2-3 weeks - still within the normal range."
   • Less Common but Possible - Rare but observed cases. An example wording would be "A few took up to a month - uncommon but possible."

   Visualise the estimated grant time window for me.

5. Wrap up with a paragraph that summarizes DHA's current processing strategy.
   End with a short insight on DHA's apparent processing behaviour, e.g.: 'DHA seems to be clearing recent ICT and engineering occupations in quick batches, often within 1-2 weeks of remedical clearance. Cases that combine medical and PCC requests tend to take longer. Offshore timelines are now aligning closely with onshore ones, suggesting end-of-year batch finalisations."

6. Include a disclaimer "These insights are based on real community timelines from SmartVisaGuide. They reflect observed DHA behaviour = not official predictions. Actual grant timing can vary based on case officer workload and security checks."

@all