Nicheloom

Market intelligence for builders — see what's gaining traction before it's crowded.

I got fired so I built a bank statement converter

Details

External ID
45812277
Source
HN
Company
—
Product
I got fired so I built a bank statement converter
Website domain
aussiebankstatements.com
Launched
Nov. 4, 2025
Cohort
—
Upvotes
16
Upvotes percentile
0.6299126637554585
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

I recently got fired and decided to channel my energy into something productive. Over two weeks, I spent 16-hour days building a tool that converts Australian bank PDFs into clean, reliable CSVs, tailored specifically for Aussie banks.Most Aussie banks only provide statements as a PDF, and generic converters often fail: columns drift, multi-line descriptions break parsing, headers shift. Existing tools don’t handle it well and I wanted a tool that just works.To get started, I used my own bank statements to build the initial parsers. There was a "duh" moment when I realised how hard it is to get more realistic test data. People don't just hand over their financial ledgers. This solidified my core principle: trust and privacy had to be the absolute top priority.I initially tried building everything client-side in JavaScript for maximum privacy, but performance and reliability were poor, and exposing the parsers on the front-end would have made them easy to copy.I settled on a middle ground: a Python and FastAPI backend on Google Cloud Run. This lets me balance reliability with a strict privacy architecture. Files are processed in real-time and the temp file is deleted immediately after the request is complete. There is no persistent storage and no logging of request bodies.My technical approach is straightforward and focused on reliability:- I use pdfplumber to extract text, avoiding complex and error-prone OCR.- I apply a set of bank-specific regex patterns to pinpoint dates, amounts, and descriptions.- A lookahead heuristic correctly merges multi-line transactions. Each parser is customised to its bank's unique PDF layout quirks.The project is deliberately focused. Instead of supporting hundreds of banks with mediocre results, I'm concentrating on a small set to get them right. It currently supports CommBank, Westpac, UBank, and ING, with ANZ and NAB next. The whole thing is deployed on Cloudflare Pages and outputs clean CSVs ready for Excel, Google Sheets, Xero, or MYOB.It was a fun challenge in reverse-engineering messy, real-world data.Try it out here: https://aussiebankstatements.comI'd love to hear feedback. If it breaks on your statement, a redacted sample would be a huge help for improving the parser.I'm also curious to hear how others here have tackled similar messy data extraction challenges.

Enrichment

Theme
spreadsheet and tabular data tools
Vertical
Fintech
Function
Vertical SaaS
Audience
B2C
AI stance
Not AI
Project type
Commercial product
Normalized one-liner
bank statement converter
Manually corrected
False

Could you build this?

Yes This is a targeted PDF parser that processes bank statement text/tables into CSV format, which can be readily built using standard PDF extraction libraries or LLM parsing pipelines.

Discussion

4 comments analyzed.

Concerns raised: How data purging and isolation actually works technically

Competitors

Other products that read as similar to this one — 94 launches clear the similarity bar, closest 8 shown.

Attention rank: #35 of 95 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Looks like the first mover among its competitors.

Other launches for this product

Same idea, different domain

Nobody's really built a vertical saas tool for Insurance yet.