finO$ blog
Guides on turning bank statement PDFs into usable data: Excel, CSV, and structured output for Latin American banks.
These pieces cover the practical side of getting financial data out of documents: how OCR differs from screen scraping, what a CSV needs to look like before accounting software will accept it, and where each approach to bank data actually breaks down.
The focus is Latin America, where account aggregation coverage is uneven and the PDF is often the only source that exists for a given bank or a given month. If you are evaluating options for a product, the comparison pages go deeper on trade-offs; if you are integrating, start with the API reference.
Bank statement OCR vs screen scraping: which to use
How bank statement OCR and screen scraping differ in accuracy, coverage, maintenance and failure modes, and how to pick the right one.
Read articleBank statement to CSV: a practical guide for imports
How to convert a bank statement to CSV that imports cleanly: the column layout accounting software expects, encoding pitfalls, and how to validate it.
Read articleConvert bank statement to Excel: 3 ways compared
Three ways to convert a bank statement to Excel (manual entry, generic PDF converters and purpose-built extraction) with the trade-offs of each.
Read articlePlaid alternatives for Latin America: an honest comparison
Plaid, Belvo and PDF-first extraction compared for LATAM financial data: how each works, where each wins, and the trade-offs nobody publishes.
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