I had problems with the mentioned KNIME only approaches so I tried something with KNIME and R. It has these steps: * run and configure R's "tabulizer" * it seems the settings 'stream' and GUESS are working best in your case * it would extract one table from each page and try to find headers and bring them to a table * not all information would be in the same columns (we come to that later) * the tables are saved as single CSVs (with their varying structure) * then they would be imported into KNIME forcing the columns to be all strings and be brought into a single table * the text fields which contain information in three columns would be integrated * the summary lines with the Credit balance would be separated * a single ID for each transaction block is created and distributed * the "our reference" field is extracted separately and be stored in a separate column (you might do that to other information as well) * the remaining "communication" is brought into one cell * all the information is being put together and could be stored Of course, you might do further manipulations like converting the sums into numbers. Introducing checks with the separate balances and so on. If you have columns that would change very much you might have to alter the workflows and change the definitions in R.
This is a companion discussion topic for the original entry at https://kni.me/w/3YMQ5EiC7ojFR7AZ