Table structure issues with OCR on financial statements

I’m working on a project where I run OCR on scanned financial statements and then extract only specific predefined fields from the tables. I’ve tested several tools, including PaddleOCR-VL 1.5, DeepSeek, Qwen, and Docling. Text recognition is generally fine. The real challenge is table reconstruction.

The statements are highly unstructured. Some columns have no headers, some rows span multiple columns, and layouts change across pages. When a column has values but no label, most tools try to force a fixed grid. This often results in merged cells, removed columns, or values shifting into the wrong columns. That breaks numeric alignment between years and makes downstream filtering unreliable.

I tested a couple of commercial tools and the structural output was much more consistent, but those options are paid. I’m trying to find an open source alternative with stronger table structure handling.
Any suggestions would be appreciated.