Our unparalleled expertise in industry verticals creates network effects to significantly improve fraud detection and credit evaluation capabilities.
While individual lenders know their own customers, they may lack the data to evaluate applicants in the context of their peers and the broader market. Ocrolus uses a unique privacy-preserving entity-resolution framework to understand each customer relative to millions of others in our dataset. This enables lenders to use benchmark data such as a borrower’s cash flow against a cohort of comparable companies and also to identify instances of loan stacking and detect document tampering.
Step one: Perform entity resolution
Securely match new applicants with existing records in the Ocrolus data network. Our entity resolution software can identify signals that are key to understanding the viability of an applicant, including the number and frequency of previous loan applications, as well as past instances of file tampering.
Step two: Run cash flow benchmarks
Gain insights from our network of more than 100 contributing lenders, enabling you to use benchmark data such as small business cash flow based on geography and industry. Retrieve percentile metrics with a borrower’s peer group for revenue, expenses, debt capacity, cash balance, and other analytics.
Step three: Incorporate benchmark data into an underwriting process
Incorporate benchmark data into predictive models to evaluate risk with greater precision. Use loan stacking and previous file tampering data to build business rules in your underwriting flow, escalating to analyst review when necessary.
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Schedule a demo to see how we deliver on entity resolution and precise risk evaluation.
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.”