I'm trying to analyse a dataset to detect fraudulent insurance claims. Unfortunately, other than basic demographics the rest of the claim is a free format OCR scanned text file made from documents submitted by the patient. These documents include lab tests, hospital bills etc., patient summaries.
Right now, manual coding is one option but expensive.
Is there any chance that applying textual analysis / text-mining might yield some predictive strength? It need not be perfect but even if it can reliably identify high fraud potential claims, that's a plus.
Any ideas how I could model this?