Frodau Research
AI has changed the economics of document fraud. Receipts, invoices, medical documents, financial statements and other supporting evidence can now be generated or manipulated in seconds. Documents that look legitimate to a human reviewer may never have existed in the real world.
Frodau Research examines how synthetic and manipulated documents are created, how they can be detected, and how organizations can identify suspicious evidence before money moves.
Traditional document fraud often leaves visible traces: altered values, inconsistent fonts, copied signatures or obvious image manipulation.
Generative AI changes that model.
Fraudsters can increasingly create complete documents rather than edit existing ones. The result may be visually coherent, internally consistent and difficult to identify through manual review alone.
Has this document been edited?
The question is increasingly also:
Is there evidence that this document, transaction or claim ever existed?
Frodau Research focuses on document fraud detection across insurance document fraud, receipts, invoices, medical documentation, and other evidence submitted before payment.
We are building a controlled benchmark designed to evaluate document-fraud detection across genuine, manipulated and AI-generated documents.
The objective is not to create a marketing accuracy number. It is to understand where different detection methods work, where they fail, and how reliably organizations can distinguish suspicious documents from legitimate evidence.
Planned document categories
Documents will be evaluated across different fraud and manipulation techniques.
How frequently are synthetic or manipulated documents correctly identified as suspicious?
How frequently are genuine documents incorrectly flagged? False positives matter because fraud detection that creates excessive manual review can simply move the operational problem elsewhere.
Detection performance may vary significantly between receipts, invoices, medical documentation and other formats. We intend to report these differences rather than collapse them into a single headline metric.
Where possible, results will be segmented by the type of manipulation or generation technique used.
We are interested in understanding which fraud signals humans identify effectively, which automated systems identify effectively, and where combining the two produces better decision support.
Where possible, research should describe the dataset, methodology and evaluation criteria clearly enough for others to understand how conclusions were reached.
We will distinguish observed results from hypotheses and clearly state important limitations.
Results should include difficult cases and failures—not only examples where detection worked.
A system that identifies fraud but incorrectly challenges large numbers of legitimate customers is not solving the complete problem.
Document analysis produces evidence and risk signals. Frodau does not treat an automated verdict as proof of fraud. Results are designed to support investigation and decision-making.
Frodau research is informed by publicly available work from fraud-prevention organizations, insurers, financial institutions, regulators, academic researchers and technology providers. Where external statistics or findings are referenced, we link to the original source whenever possible.
This distinction is important. We do not present third-party findings as proprietary Frodau research.
Document fraud is evolving alongside generative AI. Frodau will publish new findings, benchmarks and practical analysis as our research develops.
Make document fraud harder to hide.
Help organizations make better decisions before money moves.
Frodau is an AI-powered document fraud detection platform designed to help insurers and other organizations identify potentially fabricated, manipulated, duplicated or inconsistent documents before payment.
Frodau combines multiple layers of document analysis to surface evidence and risk signals for human and automated decision workflows.
Document fraud detection should provide evidence—not just a score.
About Frodau AI