Document Trust

On this page youโ€™ll find detailed information about our Document Trust service.

What is Document Trust ?

Youtrust enables customers to analyze all types of documents for signs of fraudulent tampering. To match various industries expectations on Document Fraud Detection, we offer two distinct levels on Document Trust :

  • Document Trust - Standard
  • Document Trust - Advanced

To detect fraudulent tampering we leverage fraud detectors that span across three major detection categories :

  • Metadata analysis (modification history, suspicious producers, date consistency etc โ€ฆ)
  • Structural and visual analysis (fonts analysis, incremental updates etc ..)
  • Trust marker analysis (signature, specimen detectors etc ..)
  • Advanced AI detection analysis.

To help companies and compliance teams act on this analysis we provide a : Risk Label based on a scoring engine.

When using Document Trust, the risk labels are :

Risk labelAction required
High RiskReject the document
Medium RiskManually review the document to assess fraudulent intent.
Low RiskManually review or accept the document
Trusted.Accept the document

Each call to Document Trust is also accompanied by a list of indicators that are here to explain and detail the risk label.

These indicators can be used to help your compliance team understand the verdict and take the appropriate decision.

Standard and Advanced level fraud analysis


The main differences between the Advanced and Standard level are the following :

Main featuresStandardAdvanced
Detectors>30>600
Accepted document formats.pdf (only)pdfs : .pdf
images : .jpeg, .png, .jpg
Template based analysisโŒโœ…
Trusted : risk labelโŒโœ…

What is template based analysis ?

In addition to the above detectors, Document Trust offers an additional control layer by matching documents to their known structural and visual templates in order to improve the accuracy of fraud detection.

This control layer enables us to return the Trusted risk label on a multitude of common documents.

As we are continuously seeking to improve our document template coverage, please contact our sales team to learn more about the process.

Data extraction on Document Trust

In addition to providing a fraud risk label, Document Trust can provide :

  • Extraction
  • Document type matching
  • Data consistency checks

Youtrust uses OCR (Optical Character Recognition) and LLMs (Large Language Models) to turn static documents into structured data and help you automate internal processes in addition to verifying document authenticity.

Data consistency checks enable you to verify that information such as : first_name, last_name or other data points are actually present in the document.

Currently these capabilities are available on the following document type list. If you donโ€™t see your document in the list, please contact our sales team or you dedicated TSM to add a new document type.

List of Supported Document Types for Extraction and Classification.

Document typeCountry of origin
social_security (Card or Certificate)๐Ÿ‡ซ๐Ÿ‡ท France
company_certificate (KBIS)๐Ÿ‡ซ๐Ÿ‡ท France
business_registration_certificate (Avis de situation)๐Ÿ‡ซ๐Ÿ‡ท France
driver_licence (Driver's license)๐Ÿ‡ซ๐Ÿ‡ท France
rne_certificate (Attestation RNE)๐Ÿ‡ซ๐Ÿ‡ท France
vehicle_registration_certificate (Carte Grise, Libretto Auto)๐Ÿ‡ซ๐Ÿ‡ท France, ๐Ÿ‡ฎ๐Ÿ‡น Italy
auto_insurance_claims_history (Relevรฉ d'informations)๐Ÿ‡ซ๐Ÿ‡ท France
temporary_vehicle_registration_certificate (Permesso di circolazione)๐Ÿ‡ฎ๐Ÿ‡น Italy
tax_notice (Avis d'imposition, Certificazione Unica, Steuerbescheid)๐Ÿ‡ซ๐Ÿ‡ท France, ๐Ÿ‡ฎ๐Ÿ‡น Italy, ๐Ÿ‡ฉ๐Ÿ‡ช Germany
payslip๐Ÿ‡ซ๐Ÿ‡ท France, ๐Ÿ‡ฎ๐Ÿ‡น Italy
invoice๐Ÿ‡ซ๐Ÿ‡ท France, ๐Ÿ‡ฎ๐Ÿ‡น Italy, ๐Ÿ‡ฉ๐Ÿ‡ช Germany
proof_of_address (Certificato Di Residenza)๐Ÿ‡ฎ๐Ÿ‡น Italy
proof_of_address (Meldebescheinigung)๐Ÿ‡ฉ๐Ÿ‡ช Germany
id_document
โ„น๏ธ only extraction is available for this document, no fraud level
๐Ÿ‡ฉ๐Ÿ‡ช Germany

Document Classification on Document Trust

Classification categorizes the type of document that was uploaded, so you can process it automatically. Currently the list of supported documents for classification can be found above but keep in mind that new document_type values are added over time.

Treat a value you do not know as unrecognised rather than rejecting the payload.

All Documents submitted to Document Trust Analysis get a document_type label and when available a country_code inside the document_classification object.

Additionally; you can reject documents that don't match your expected document type by adding the type field when requesting a Document Trust Analysis. When a type field is added, we compare it's value to the classified label, and will return a dedicated status_code (more details here) in case there is a mismatch.

๐Ÿ“˜

Implementation Tip

When your uploaded document doesn't match the expected type but the document_classification.document_type returns a value that you are ok to process, retry your request by using the classified label as an expected type.

What document formats do we currently accept ?

โš ๏ธ

Disclaimer

While we currently support both native pdfs and images (png,jpeg) on the Advanced level we strongly advise you to choose native pdfs whenever possible as they keep a stronger digital fingerprint and make it easier to detect tampering attempts.

When pdf alternatives are not available, we still accept the document and perform our fraud detection layer based on image based detectors, but some tampering traces can be permanently lost during the format conversion.

File limitations and guidelines

Limit typeLimit valueApplicability
Max file size25 MBAll documents
Maximum number of pages10 pages (check billing unit section for billing informaiton)All document

Do not upscale or enhance

Never upscale a low-resolution image, adding extra pixels only adds to processing time without an increase in accuracy.

It is best to avoid very low-resolution images, if possible.

Keep the aspect ratio

Never change the original aspect ratio. Doing so will create distortions and degrade the performance of the OCR.