Account registration and onboarding
Prevent fraudulent access to bank services by identifying identity theft, invalid identity documents, and altered proof of address or utility bills.
Document Fraud Detection
Protect your organization from document fraud
Mitigate risks, improve compliance, and avoid financial losses with AI-powered document fraud detection.
The financial impact of document fraud
Digitizing your business operations brings numerous improvements, including increased efficiency and improved data management. But it also comes with significant risks: the low barrier to document forgery and fraudulent transactions. These transactions cost organizations across the world an estimated 5% of their annual revenues, amounting to $5 trillion.
The banking and financial services sectors are the most attractive industries to criminals and fraudsters, closely followed by insurance, healthcare, and government organizations. To protect their profits, reputation, and customers, organizations are tasked with increasing their investments in preventative resources to meticulously review and check incoming documents.
Organizations face significant challenges with fraud detection
Inefficient and expensive manual verification
Manually reviewing incoming documents is a slow and error-prone process. It requires significant employee resources, but delivers relatively low detection rates due to the sophisticated tampering methods criminals use.
AI-based solutions provide instant results with higher accuracy and lower cost.
Mix of document types, formats, and quality
Business documents often come in a range of file formats, document types, and levels of quality (including PDFs, scans and photos). Sorting through unclassified documents often proves challenging for fraud detection solutions.
Organizing and normalizing incoming documents and data prior to feeding them into a specialized fraud detection solution increases success rates.
Incomplete fraud detection solutions
Implementing simplistic fraud detection solutions that focus only on detecting image manipulation misses the enormous opportunity that the data contained in the document provides.
Combining checks for image manipulation with rule-based data cross-checks is a more powerful and accurate way to detect fraudulent documents.
