Now that we have scanned quite a few more bank statements, it is timely to summarise our experience with processing them by optical character recognition.
Generally bank statements are scannable. We rarely need to resort to typing them in by the column. Often there is some issue with the bank statements. They may be too faint, or they may have handwriting on them. A session on the computer-assisted blink comparator always provides a remedy, and is always much better than typing it in. We are glad we have this system.
Narratives are entered with the assistance of Narrative Prediction. This always speeds things up, but often it is less than wonderful. Maybe this is where we need to have some new ideas. One thing we do is to customise the F1 … F10 keys for each particular client, and this is a help. In February when there was not much to do, we had a session of tweaking the customisation for each client, and this should be a help as well.
Once the bank statements are captured in our software, processing is usually straightforward. Our mapping table has a direct link to the Internet so we can look up payments with strange narratives and no invoices on file.
Generally we are happy with the way things are going. We think our choice of a hybrid OCR/Narrative Prediction system is right, because most bank statements will be just not good enough for a pure OCR system. We do often need to deal with handwritten records which resemble handwritten bank statements, so we could do with Narrative Prediction and reprogramming the F1 … F10 keys anyway.