TL;DR: Ocrolus has integrated with Freddie Mac’s AIM Check API, enabling mortgage lenders to receive an early income assessment from Loan Product Advisor® (LPA®) asset and income modeler (AIM) directly inside Ocrolus Analyze. The integration uses W-2s and pay stubs already uploaded to Ocrolus, with no prior LPA submission required and no duplicate data entry. Income values, AIM eligibility per income type, the AIM Check API certificate and its expiration date are returned in Analyze and stored on the loan, and results can be imported to Encompass® by ICE Mortgage Technology®,
Today, Ocrolus announced its integration with Freddie Mac’s AIM Check API, enabling mortgage lenders to receive an early income assessment from Loan Product Advisor® (LPA®) asset and income modeler (AIM) directly inside Ocrolus Analyze. Lenders can access this capability using the W-2s and pay stubs already in their loan file, with no prior LPA submission required and no duplicate data entry.
“Mortgage lenders already use Ocrolus throughout the origination process to transform bank statements, pay stubs and tax forms into decision-ready data,” said Nadia Aziz, GM of Mortgage at Ocrolus. “With this integration, that same data can now power an early income assessment from AIM inside lenders’ existing workflows. It’s a significant step in reducing manual touchpoints and further accelerating lenders’ path to clear-to-close.”
As an AIM Check API integrator, Ocrolus submits extracted W-2 and pay stub data to AIM Check API, enabling lenders to receive an early income assessment directly in Ocrolus Analyze. Through this integration, lenders benefit from:
By leveraging documents already in the loan file, lenders can accelerate income assessment without a prior LPA submission and without duplicate data entry. Income data collection and assessment remain among the most manual and time-intensive steps in mortgage origination. Through this integration, lenders can streamline income calculation, reduce manual effort and improve efficiency while increasing confidence in income calculations.
This is Ocrolus’s second government-sponsored enterprise (GSE) integration. Ocrolus’s existing Fannie Mae integration covers self-employed and rental income. Freddie Mac’s AIM Check API integration covers wage-earner income (W-2s and pay stubs) and is designed to complement it for lenders managing borrowers with different income profiles in the same pipeline.
Both integrations are built on the same principle: income results should flow from the documents lenders already collect, not from a separate submission process. Loans originated using AIM are half as likely to produce defects and become delinquent (source: Digital Innovation Drives Loan Quality)
Lenders who originate Freddie Mac-eligible conventional loans and currently use Ocrolus can speak with their account manager to learn more and get started.
AIM Check API enables access to LPA and asset and income modeler (AIM) independent of a complete LPA submission. It gives mortgage lenders an early view of the income assessment, as far upstream as lender pre-approval, without first submitting a complete loan application into LPA.
No. Ocrolus submits extracted W-2 and pay stub data to AIM Check API and displays the results returned by AIM. The income assessment is generated by AIM.
The integration uses W-2s and pay stubs already uploaded to Ocrolus. It covers wage-earner income. Self-employed borrowers and tax-return income calculation capabilities will be added with Freddie Mac at a future date.
Income values, the Report ID for the LPA submission, and the AIM Check API certificate are stored on the loan in Ocrolus and can be imported into Encompass® by ICE Mortgage Technology®.
The Fannie Mae integration covers self-employed and rental income calculated from tax returns and related documents. The integration of Freddie Mac’s AIM Check API uses Ocrolus-extracted W-2s and pay stubs and covers wage-earner income. Ocrolus is working with Freddie Mac to add support for Self Employment and Rental income calculations at a future date.