IDX_Financial_Statements: The Multimodal Indonesian Financial Dataset

IDX_Financial_Statements is a centralized repository providing the most complete set of financial disclosures for public companies listed on the Indonesia Stock Exchange (IDX). This dataset is designed for advanced financial research, spanning from raw document archival to structured data extraction.

Dataset Overview

This is a multimodal dataset that captures the full lifecycle of financial reporting. It includes:

1. PDF Reports: Original Annual Reports (Laporan Tahunan) and Financial Statements as submitted by issuers. Ideal for Document AI, layout analysis, and OCR tasks.
2. Excel Sheets: Semi-structured spreadsheets containing balance sheets, income statements, and cash flow details.
3. XBRL Instances: High-precision, machine-readable XML-based data using the IDX Taxonomy. This is the gold standard for quantitative data integrity.
4. Metadata: Associated tickers, industry sectors, reporting periods (Q1, Q2, Q3, FY), and submission timestamps.

Key Features

• Format Diversity: Supports a wide range of technical workflows, from computer vision (PDF parsing) to direct database ingestion (XBRL).
• Historical Depth: Comprehensive coverage of the Indonesian capital market over multiple fiscal years.
• Bilingual Context: Documents often contain side-by-side Indonesian and English text, making this a valuable resource for financial-domain NMT (Neural Machine Translation).
• Audit-Ready: Includes original source documents, allowing for the verification of extracted data against official corporate filings.

Use Cases

• Multimodal RAG: Build AI agents that can "read" a 200-page PDF annual report and cross-reference it with numerical Excel data.
• XBRL Analysis: Utilize the standardized taxonomy for high-speed fundamental screening without the need for traditional scraping.
• Document AI Training: Fine-tune models for table detection, key-value pair extraction, and financial entity recognition.
• Market Intelligence: Analyze corporate governance statements and management discussion & analysis (MD&A) sections for sentiment and strategic shifts.

Data Structure

The repository is organized by Ticker and Period. A typical directory structure looks like:

• [TICKER]/[YEAR]/[PERIOD]/
  • FinancialStatement-202X-I-Ticker.pdf
  • FinancialStatement-202X-I-Ticker.xlsx
  • FinancialStatement-202X-I-Ticker.zip (XBRL)

License

This dataset is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0). You are free to share and adapt the material for any purpose, including commercial use, provided you give appropriate credit.

Disclaimer

This dataset aggregates publicly available information for research and analytical purposes. Users are encouraged to cross-reference data with the IDX official disclosures for formal investment or legal decisions.

---