Events

In this session, we’ll walk through how leading lenders are rethinking loan setup as the first control point for cost, quality, and speed.

You’ll see how TRUE:
-Ingests documents directly from Encompass
-Classifies and validates data at intake
-Identifies inconsistencies before they create downstream conditions
-Establishes a clean, trusted file from the start

In this session, we’ll show how lenders are transforming post-close from a bottleneck into a control layer for quality, compliance, and capital efficiency.

You’ll see how TRUE:
-Processes full loan packages at scale
-Validates documents and data against investor and QC requirements
-Automates checklist completion and exception identification
-Creates an audit-ready file without redundant review

In this session, we’ll walk through a full lifecycle demo, from loan setup through post-close, tailored specifically to retail Encompass-based lenders.

We’ll show why Manual Review Rate (MRR) has become one of the most important metrics for retail lenders, and how reducing it unlocks faster, more scalable QM mortgage processing without adding headcount.

You’ll see how TRUE:

-Normalizes borrower-submitted documents
-Eliminates repeated validation across teams
-Reduces conditions and rework
-Enables exception-based workflows across the lifecycle

In this session, we’ll focus on how TRUE helps wholesale lenders handle inconsistent, broker-originated loan packages without increasing manual review.

You’ll see how TRUE:

-Ingests and organizes large, unstructured loan packages
-Validates data and documents early in the review process
-Identifies missing or inconsistent information
-Reduces friction between broker submission and funding
-Automatically splits, classifies, and assembles documents into a complete, review-ready loan file

In this session, we’ll walk through how TRUE supports post-close and package-level validation workflows, while also addressing where automation is more challenging today. While these loan types may never be fully automated, lenders can significantly reduce manual effort by automating the repeatable tasks and surfacing only the exceptions that require expert review.

We’ll also demonstrate how TRUE handles complex income scenarios, including bank statement loans and DSCR loans, using deterministic rules and AI to extract, validate, and organize data for faster, more consistent decision-making.

You’ll see:

-How TRUE processes full loan packages in correspondent workflows
-Where standard automation performs well
-Where non-standard documents (e.g., bank statement and DSCR income) introduce complexity
-How lenders can think about applying automation in these environments
-How TRUE extracts and analyzes bank statement data using AI and deterministic rules to generate structured income reports for Non-QM underwriting