Automated file tampering detection and mathematical checks empower you to onboard customers with confidence.
Ocrolus automatically checks the documents your customers provide for tampering and inconsistencies that pose a risk to your business. Our solution recognizes suspicious documents by identifying incomplete data, missing pages, invalid information, and abnormal edit history. Our algorithms have been trained on more than 100 million pages of documents derived from thousands of financial institutions.
Step one: Tampering detection
Ocrolus evaluates each submitted document for signs of tampering and inconsistency, flagging edits that were made subsequent to the document’s creation and highlighting areas where changes have occurred.
Step two: Algorithmic checks and validation
Our accurate data capture provides Ocrolus with the foundational ability to conduct numerous algorithmic data validations. For example, we automatically highlight outlier values, reconcile totals against line items, identify missing pages, flag invalid dates, and cross-validate data fields for the same borrower across multiple sources.
Step three: Data enrichment
We work with hundreds of the most innovative financial services companies and constantly ask our customers for feedback on best-in-class technologies. Ocrolus has partnered with SentiLink (synthetic fraud detection) and Middesk (Know Your Business automation) to provide lenders with a curated and complete stack of leading fraud solutions available through a single platform.
Step four: Comprehensive suspicious activity signals
Ocrolus returns a detailed set of suspicious activity signals in a structured format, providing risk systems and fraud analysts with the information they need to handle questionable cases and ultimately make confident lending decisions.
We're enhancing the Blend platform with Ocrolus' automated, accurate document classification and data extraction capabilities. Our partnership with Ocrolus enables us to swiftly deliver time-saving innovations to our customers.”