MORTGAGE + CREDIT EVIDENCE

Preserve the evidence behind AI-influenced mortgage and credit workflows.

Mortgage and credit AI increasingly spans lenders, technology vendors and multiple systems. LoopGrid is exploring a focused Design Partner wedge: portable evidence that records which AI system acted, under what policy and authority, what human oversight occurred, and what action or outcome followed.

01Loan workflowincome / document / fraud / servicing
02AI influencetool, model, output, policy
03Human / system actionreview, approval, state change
04Portable evidencesigned, exportable, independently verifiable
WHAT THE CURRENT GSE MATERIAL ACTUALLY SAYS

Separate the requirement from LoopGrid's implementation.

We do not claim that Fannie Mae or Freddie Mac require cryptographic LoopGrid-style evidence. Their 2026 materials create governance, disclosure, vendor-risk and audit pressure; LoopGrid's portable verification is one technical way to strengthen the evidence layer around those workflows.

FANNIE MAE · LL-2026-04

AI/ML governance and vendor oversight

Published April 8, 2026 and effective 120 days from publication. The letter requires policies/procedures for AI/ML risk, compliance with information-security requirements, governance of subcontractor/vendor AI use that is no less protective, and prompt disclosure of AI/ML use and safeguards upon request.

Read the official Lender Letter →
FREDDIE MAC · GUIDE §1302.8

Governance, monitoring and audits

Effective March 3, 2026. Freddie Mac requires AI/ML governance frameworks, documented roles and risk management, regular monitoring, and internal/external audits, along with disclosure obligations and indemnification language.

Read the official Guide section →
WHERE LOOPGRID FITS

Cross-organizational evidence, not another underwriting model.

LoopGrid does not score borrowers or determine eligibility. It sits around AI-influenced workflow decisions so a lender, vendor, investigator or reviewer can reconstruct the captured decision path and verify the integrity/provenance of the exported evidence.

01

Which AI

Agent/service identity, deployment and model/context provenance.

02

Which authority

Who the system acted for, what it was allowed to do and under which policy.

03

Which oversight

Human approval, rejection or adjudication preserved as signed history.

04

What happened

External action plus the observed outcome reported by the downstream system.

10-MINUTE ARTIFACT

Start with a fake loan workflow, not production data.

A Design Partner can begin with a synthetic income-verification or fraud-decision event, export the evidence, verify it offline, then change a byte and confirm verification fails. That lets the technical team evaluate the evidence model before discussing sensitive loan data.

Boundary

LoopGrid preserves evidence around an AI-influenced workflow. It does not provide underwriting recommendations, consumer credit scoring, legal advice, or a compliance determination.