Turn a 300-Page HK Annual Report into Structured Financials
What this scenario solves
Digging numbers out of an annual report by hand takes two hours per company and still produces transcription errors.
Tool stack
Not the only solution, but a stack we have verified end to end. Each tool links to its full review, including who it is not for.
What you end up with
Structured JSON for revenue, gross margin, cash flow, and segment data — each field carrying its source page number.
Full steps
- 01環境搭建:macOS 上的 Transformers 引擎
- 02PP-OCRv5 首戰:00928 帝王國際投資 FY2025 P&L 頁
- 03PP-StructureV3 的 KMeans Bug:技術根因分析
- 04自建 Table Parser:DBSCAN 行列分群
- 05AK-OCR Pipeline:端到端自動化
Articles carrying the full content
- PaddleOCR in Practice: Extracting Hong Kong Stock Annual Report Financial Data in 83 Seconds
A hands-on test of Baidu PaddleOCR, the open source document AI engine with 81K Stars. PP-OCRv5 with 96.5% accuracy extracted 102 text regions from a Hong Kong stock annual report P&L page, discovered a KMeans clustering bug (n_clusters=0) in the PP-StructureV3 Transformers engine, built a custom DBSCAN row and column clustering parser, and completed automatic structuring of three financial statements end to end in 83 seconds.
2026-06-0817 minRead - 300-Page Annual Report to Structured JSON: The Three Statements and Segment Data
Building on the PaddleOCR field practice, this pushes 'reading out the text' to 'usable data': locating the financial-statement pages, handling cross-page tables, field mapping and unit normalization for the three statements and segment information, JSON schema design, and a complete pipeline and checklist for automated proofreading via reconciliation relationships.
2026-09-3022 minRead - How Machines Read Financials: From PDF to Structured Data
The first bottleneck of automating financial-statement analysis is that machines cannot read the PDF. This article breaks down the three paths — text-layer extraction, OCR, and layout analysis — explains why financial tables are especially hard to read and why human proofreading is mandatory after OCR, and gives the design concepts of structured output (JSON schema).
2026-09-3010 minRead - Three-Statement Articulation and Cash-Flow Quality Checks: Spotting the Book-Profit Trap
Profit is an opinion; cash is a fact. This article takes apart the reconciliation relations of the income statement, balance sheet, and cash-flow statement, gives check dimensions such as the cash conversion ratio, working capital, and capitalized spending, adds a 'red-flag signal → account to check → verification method' cheat sheet, and demonstrates writing these checks as an automatically executable, traceable rule engine.
2026-09-3015 minRead - Automating Comparable Company Analysis: Run an Entire Sector in One Pass
The difficulty in comparable company analysis is not the arithmetic of multiples but the basis: fiscal year, currency, one-off items, and EV composition can all let two companies' numbers contaminate each other. This article breaks down the criteria for selecting peers, six categories of basis-unification rules, and the traps in choosing multiples, and gives a five-stage automation pipeline design with executable code, from data extraction to outlier handling.
2026-09-3019 minRead
Adjacent scenarios
Other scenarios using
- PaddleOCR in other scenarios
- DeepSeek in other scenarios
- Claude Code in other scenarios
Level: Beginner · Tracks: Finance Track · Business Track · Last verified: 2026-09-29