Bynn automates the work of collecting claim documents across languages, then examines the evidence for signs of fabrication or manipulation before a decision is made.
Where this stands: Claims evidence collection and forensic examination are available to insurers today.
Sample claimMotor claim, rear collision
- Invoice: amount field editedIndicator of manipulation
- Photos: no generation signs
- Police report: consistent
Most of a claim's time is spent waiting for evidence.
A claim can generate repeated requests and long email exchanges before anyone can assess it. Repair invoices, medical bills, police reports and photos of damage arrive in different formats and languages, often incomplete.
Some of that evidence may not be what it seems: an invoice with a changed amount, a reused template, a damage photo that was generated or edited. Staged or exaggerated, fraud drives up costs for honest policyholders.
What claims teams answer to
Fair, prompt handling
Policyholders and regulators expect valid claims to be settled quickly and fairly. Slow evidence gathering works against both.
Investigations that hold up
When special investigation units review a suspicious claim, they need specific findings they can explain, not an unexplained score.
Generated evidence
Image generators and editing tools make convincing damage photos and documents easy to produce, and hard to spot by eye.
Where AI does the work
Uses available products
Automated document collection
Agents request the documents a claim needs, follow up on what is missing and handle the correspondence across languages, so the evidence reaches the claims process without manual chasing.
Uses available products
Document fraud detection
Invoices, bills and reports are examined for tampering, reused templates and hidden edits, using the file's structure as well as its appearance.
Uses available products
Image authenticity
Photos of damage are checked for signs of AI generation and localized editing, as separate signals.
Uses available products
Agentic fraud reasoning
AI reasoning brings the findings together within the wider evidence review, so a suspicious claim reaches an investigator with the reasons attached.
One claim, from first notice to decision
Run agentic workflows autonomously, with optional human review when an agent is unsure how to proceed. Configure the workflow around the way your organization handles claims.
A claim is opened. The workflow works out which documents are needed and asks the claimant for them, in the claimant's language.
Missing or unreadable documents trigger a follow-up instead of an email thread. Each document is identified as it arrives.
Document forensics and image-authenticity models examine the evidence for indicators of fabrication or manipulation.
Agentic fraud reasoning weighs the findings in context. Clear claims move on; uncertain ones are routed to a person with the evidence and the reasons.
The claims handler or investigator makes the decision with complete, examined evidence in front of them.
In
- Repair invoice
- Photos of the damage
- Police report
Out
- Invoice: amount field editedIndicator of manipulation
- Photos: no generation signs
- Police report: consistent
Two benefits, measured separately
Administrative time saved
Automating collection removes the repeated requests and correspondence needed to obtain the right documents. This is a saving in handling time.
Fraud losses avoided
Detecting suspicious evidence addresses a different cost: losses from invalid, incorrect or fraudulent claims. This is a saving in what is paid out.
What is involved
AI document collection
Requests, follow-up and intake across languages.Learn moreDocument fraud detection
Forensic examination of submitted documents.Learn moreAgentic fraud reasoning
Reasoning across findings within the review.Learn moreDetector24
Specialist models for AI-generated and edited images.View productZOREAL Verify
Forensic analysis of PDFs and document images.View product
Questions from claims teams
Does this replace claims handlers?
No. It removes the coordination work around a claim and examines the evidence. Decisions on uncertain or suspicious claims go to your people, with the findings attached.
Can the workflow run without human review?
Yes, if you configure it that way. Workflows run autonomously by default, and you choose where a person reviews, including whenever an agent is unsure how to proceed.
Which documents can be examined?
The documents claims depend on, such as invoices, bills, reports and statements as PDFs or images, along with photos submitted as evidence.
How much will we save?
It depends on your claim volumes, lines of business and current process. We measure administrative time and fraud losses separately with you rather than quote a generic figure.
Other industries
All industries
Discuss your claims workflow.
Show us where claims wait today. We will map the collection and examination steps that can run on their own.