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 benchmark a borrower’s cash flow against a cohort of comparable companies and also to identify instances of loan stacking and previous file tampering.
Step one: Perform entity resolution
Securely match new applicants with existing records in the Ocrolus data network. We 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 benchmark small business cash flow data 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 results 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.
Ocrolus has been so easy to work with; we’ve been able to scale Operations by implementing Ocrolus.”