A heavier bodily-injury claim. You juggle the accident report, the loss adjuster's findings, medical certificates and a thick stack of letters from the policyholder. Asking an AI to rebuild the timeline or flag an inconsistency would save you half a day, and the temptation is real. But here is the catch: a claim file is anything but trivial, because it blends the policyholder identity, the identities of various third parties and, sometimes, genuine health data. Paste it as-is into a consumer tool? You expose all of them at once. The point is not to give up AI. It is to hand it a file where nobody is identifiable by name anymore.
Identity is masked, the amount stays visible: the AI analyzes the file without knowing whose it is.
A claim is never just one person
Take a car accident. You have the policyholder, the other driver, their passengers, and sometimes that witness who left a number at the bottom of the report. Each one carries a name, an address, a phone. The vehicle license plates are identifying data in their own right too. Pseudonymizing the file therefore means masking every single one of those parties and not just your policyholder, because otherwise a third party stays perfectly recognizable in the text sent to the AI.
Medical assessment, the most sensitive part
The moment a bodily-injury file lands, everything changes. The expert report and the certificates carry health data: disability rating, diagnosis, medical history. Sensitive. Under the GDPR this counts as special-category data, and a single copy-paste is enough to leak it. So you mask the injured person's name and the details that point to them, while leaving the AI the identity-free clinical material it genuinely needs to check whether a settlement is consistent.
What must stay readable
The policy number and the claim number become stable pseudonyms. Enough to follow the thread. Never enough to point to the policyholder. The settlement amounts, the relative dates and the nature of the claim, on the other hand, stay in clear, because that is exactly the material the AI has to analyze to be of any use to you.
The method in practice
The method comes in three steps. You pseudonymize the file and its attachments, the AI works on the masked version (summary, qualification, inconsistency detection), then you re-identify locally for final processing. At no point is the policyholder, a third party or a witness exposed to an external service. Not once.
Safe-Doc does exactly that. It masks files and their attachments before the AI, keeps the original layout, processes inside the European Union then purges the data. To go further, see the ChatGPT and GDPR at work guide.
Protect the policyholder. Pseudonymize the file before you send it to the AI.