AI document fraud detection
Koncile combines forensic AI-powered consistency analysis, image analysis, metadata intelligence to detect document fraud others miss.
Most forged detection tools look only at pixels.
We analyze logic and context. We uncover inconstencies.
How our fraud detection works
Contextual Consistency Check
- OCR extraction
- Business-rule intelligence
- Regulatory awareness
- Cross-field validation
Forensic Detection Layer
- Layer analysis
- Compression artefacts
- Pixel anomalies
- Font inconsistencies
Metadata Analysis
- Creation software mismatch
- Edited timestamps
- Embedded object inconsistencies
- PDF producer anomalies
Fraud detection models, tailored to every document
Every document has its own fraud patterns. We build specialized models to detect them.
Invoice fraud
Paystub
Bank statement forgery
W-2 fraud
1099 fraud
Utility bill fraud
For risk, compliance and operations teams
One platform to extract, control, and secure every document in your pipeline.
KYC
Procurement
Lending
Insurance
Fintech & payment
Marketplaces
An AI OCR tool built for regulated environments
Founded by a former lawyer, Koncile was designed with compliance and data protection at its core. We are independently audited under SOC 2 and compliant with GDPR and HIPAA requirements.
Talk to an expert who knows your industry.
- Get an external expert opinion on your specific use case
- Benchmarks and results from hundreds of clients in your industry
- Help activating the right Koncile features for your workflow
Real life insights on document automation
Developers launch MacDoc, an illegal fake passport generator
In February 2026, US authorities shut down OnlyFake, a widely used fake document generator. Weeks later, an identical service reopened under the name MacDoc. Its forgeries are getting past the KYC checks of major institutions including PayPal, Airbnb and Coinbase.
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Document deepfakes: catch the fakes slipping past your checks (2026)
In 2026, document fraud has a new face: the document deepfake, a fake generated entirely by AI. According to Shufti's Identity Fraud Index 2026, it's the fastest-growing fraud category, with an annualized increase estimated at nearly 3,900%. What sets these fakes apart: they're clean on the surface. Here's how to detect the ones still slipping past your checks.
Top 10 Best Document Fraud Detection Software in 2026
Document fraud has outgrown Photoshop. In 2026, the fastest-growing threat is the AI-generated fake: invoices, bank statements and payslips produced from scratch, pixel-perfect, with clean and consistent metadata. Here is our comparison of the 10 best document fraud detection software platforms every finance and risk team should know, and how to choose the right one.
OpenCV in Python: Detecting Document Fraud Through Image Analysis
OpenCV is one of the most widely used computer vision libraries in Python. But can it really detect document fraud? In this article, we test OpenCV on several real-world falsification scenarios: amount modification, signature copy-paste, inpainting removal, and compression analysis (ELA). The objective is simple: understand what visual detection can actually identify and where its limits are.
Invoice fraud : how to detect fake invoices and suspicious suppliers
Invoice fraud is often perceived as a marginal or exceptional risk. In reality, it is one of the most common sources of financial loss for organizations of all sizes. Fake invoices, supplier impersonation, payment diversion, and subtle manipulation of approval processes continue to bypass traditional controls. While some cases are caused by simple billing errors, invoice fraud is intentional by nature. It relies on small inconsistencies, operational pressure, and trust in documents that appear legitimate. Understanding how invoice fraud works is the first step toward detecting it before payment.
Your questions about fraud detection
Document fraud detection refers to the automated identification of falsified, altered, or forged documents, invoices, payslips, bank statements, contracts, or ID documents, submitted to an organisation. As document volumes grow, manual review becomes impractical, making automated fraud detection an essential layer of financial and operational control.
A document fraud detection tool analyses incoming documents to flag signs of tampering or inconsistency. Unlike manual checks, it processes high volumes in real time, combining business rules, reference data, and analytical models to surface suspicious documents before they generate financial exposure.
Most fraud detection tools rely on pattern matching alone. Koncile takes a contextual approach: for each document type, the platform develops specific models alongside domain experts (accountants, legal specialists, operations teams), who encode the rules and logic relevant to each context, enabling coherence checks the way a human expert would. Rather than simply flagging PDF alterations or abnormal patterns, it evaluates whether a document's data is reliable as a whole, cross-referencing figures against each other and against sector-specific rules.
The most targeted documents are supplier invoices, payslips, bank statements, contracts, and administrative certificates. Document fraud affects every sector, but is particularly prevalent in finance, HR, and procurement, anywhere high-value decisions rely on document-based evidence.
La fausse fiche de paie est l'un des documents les plus falsifiés, notamment dans les dossiers de crédit ou de location. Koncile s'appuie sur deux niveaux de contrôle : d'abord l'analyse des métadonnées du fichier, où les modifications laissent souvent des traces très visibles ; ensuite la vérification de cohérence des montants, cotisations, brut, net, qui nécessite une connaissance fine des règles de paie françaises. C'est pourquoi Koncile a été conçu avec des experts métiers : pour que ces contrôles réglementaires soient fiables et directement opérationnels.
Two integration modes are available. Via the platform, documents are uploaded directly and Koncile returns a reliability score for each one, with automatic alerts triggered on high-risk files. Via API, documents are sent to Koncile's endpoint and the score and alerts are returned in real time, for seamless integration into your existing workflows.
Effective detection relies on two complementary levels: file metadata analysis, which reveals traces of modification, and semantic verification of the document's content, which catches internal inconsistencies even when the document appears intact on the surface. It is also essential to define rules specific to each document type. On a payslip, for instance, the relationships between gross pay, net pay, and contributions follow precise rules that the tool must understand. That is why Koncile builds its models with domain experts, ensuring controls that are reliable and operational from day one. Finally, detection must cover the entire incoming document flow, not just the documents that appear suspicious at first glance.
Implementation starts with choosing the integration mode: direct access via the platform, or an API connection to plug Koncile into the organization's existing systems (ERP, HRIS, credit portal…). This integration is compatible with automation tools such as Zapier, n8n, or Power Automate. The next step is configuring the control rules specific to each document type, which is done in plain language, with no custom development required. At Koncile, this configuration is carried out with the relevant domain experts : finance, HR, and compliance. To ensure the models are reliable and fully operational from the very first day.