Freddie Mac’s own repurchase data holds a lesson for every loan buyer. Income represented 35% of all defects on Freddie Mac repurchased loans in Q3 2025, according to Freddie Mac’s Q3 2025 Loan Delivery & Repurchase Trend Reporting, and the decline in repurchase count that quarter came primarily from fewer income defects [1]. That is progress, but it is not resolution. Income still accounts for more than a third of what goes wrong in loans that get pushed back. For whole-loan buyers and securitization teams without independent IRS income verification, the problem is structural: you inherit income defects you did not create, and you carry the pricing and repurchase exposure that follows. The real question is not whether income risk exists in your pools. It is whether you hold independent evidence that the income in each file is real and correctly calculated.
Falling buyback counts do not mean income risk is solved
The headline trend looks reassuring. Freddie Mac repurchase volume on performing loans fell 26% in Q4 2025 compared with Q2 2025, according to Freddie Mac’s Q4 2025 trend reporting, while new business activity rose to $118 billion from $100 billion a year earlier [2]. More loans are moving, and fewer are coming back.
Read that pairing carefully. Higher volume with fewer repurchases does not mean every loan in the pipeline is clean. It means the agencies are finding and enforcing fewer defects. The defects that remain still sit in loan files, and many of those files now sit with investors and securitizers rather than the originators who built them.
Random sampling confirms that income errors, including the misrepresentation behind income fraud in lending, are far from rare. Four of the top 10 initial significant defects in Fannie Mae’s Q3 to Q4 2025 random sample involve income, including misrepresentation of income and incorrect base income calculation, according to Fannie Mae’s Quality Insider [3]. A random sample reflects ordinary production, not a targeted review of problem loans.
The stakes: whoever holds the loan carries the burden of proof
When a loan changes hands, the income risk changes hands with it. A whole-loan buyer that accepts an originator’s file at face value is accepting the originator’s income calculation, documentation, and judgment. If that income turns out to be misrepresented or miscalculated, the buyer absorbs the consequences.
Those consequences land in three places:
- Pricing. Loans with income defects carry a different risk profile than the tape suggests, which distorts pool valuation and execution.
- Repurchase position. A buyer that later needs to put a loan back to the seller needs evidence that the defect existed at origination. Without independent documentation, that claim rests on the seller’s own file.
- Pool quality. In a securitization, a cluster of income defects affects performance across the deal, not just a single loan.
Declining repurchase counts shift this burden rather than remove it. As upstream reviews catch fewer defects, more of the responsibility for proving loan quality moves to whoever holds the asset.
Why traditional diligence misses income defects and income fraud
Most due diligence processes still review income the same way the originator produced it: by reading the documents in the file and checking the worksheet. That approach has two built-in weaknesses.
First, it inherits the source documents. If the income in the file was misrepresented, reviewing the same paperwork reproduces the misrepresentation. A reviewer confirming that pay stubs match a worksheet has confirmed internal consistency, not accuracy.
Second, manual recalculation is slow and uneven compared with automated income calculation. Base, rental, and self-employment income each follow different rules, and the Fannie Mae data shows that calculation errors in these categories persist in ordinary production [3]. Diligence teams working against settlement deadlines sample a subset of files and re-read the worksheets on the rest. The errors that slip past the originator’s underwriter often slip past the reviewer for the same reasons.
Legacy IRS transcript verification adds friction of its own. The traditional transcript ordering process was slow and error-prone, and it gave lenders a single snapshot rather than a durable record. For an investor reviewing loans after the fact, waiting days for a single snapshot does not scale across a pool.
What works: IRS income verification at purchase
The approach that closes this gap is straightforward. Instead of re-reading the originator’s documents, verify income against an independent source and recalculate qualifying income from that verified data. The result is an income verification audit trail that belongs to the buyer, not the seller.
TrueTax® retrieves verified income data directly from the IRS, replacing the legacy transcript ordering process. For a loan buyer, that means the income evidence in the file traces to the IRS rather than to documents the borrower or originator supplied. If the stated income and the IRS-verified income do not align, the discrepancy surfaces before the loan prices into a pool.
Self-employed income calculation with verified data
TrueCalc™ completes the picture for self-employed borrowers, whose income calculation errors are hardest to catch. It automatically calculates qualifying income using AI and IRS-validated data, turning hours of underwriter work into minutes. Diligence teams get an independent qualifying income figure to compare against the originator’s worksheet, rather than a second read of the same math.
Together, TrueTax® and TrueCalc give investors a documented, repeatable income check. The audit trail supports pricing decisions at purchase and strengthens the buyer’s position if a repurchase conversation follows. It turns income review from a judgment call on someone else’s file into evidence the buyer controls.
Practical steps for loan buyers and securitizers
These steps deliver the most direct improvement without overhauling the entire diligence process:
- Make IRS income verification a purchase standard. Require IRS-verified income data in the file, or obtain it independently, before a loan enters a pool.
- Recalculate rather than re-read. For base, rental, and self-employment income, compare the originator’s qualifying income against an independent calculation from verified data.
- Prioritize the defect categories the agencies flag. Fannie Mae’s random sample points to misrepresentation of income and incorrect base income calculation [3]. Focus review effort there first.
- Preserve the audit trail. Store verification results with the loan record so they are available for pricing review, investor reporting, and any repurchase claim.
- Track discrepancy rates by seller. Income mismatches concentrated in a single originator’s loans are a signal for pricing, eligibility, and counterparty decisions.
Decide with certainty at the point of purchase
The repurchase data shows real improvement, and the improvement came mainly from fewer income defects [1]. That proves income quality responds to better verification. It also proves the work is not finished: income remains a persistent source of defects in both repurchased loans and random production samples [1][3].
For investors and securitizers, the lesson is clear. Loan quality you cannot document is loan quality you cannot defend. An independent IRS income verification audit trail protects pool quality, supports accurate pricing, and strengthens your repurchase position. Capital that would have been lost to bad loans stays available to put to work.
Halcyon helps loan buyers replace inherited assumptions with verified evidence. See how TrueTax® delivers IRS income verification for every loan you buy and builds the audit trail your pools need.
References
- Freddie Mac. (2025). “Loan Delivery & Repurchase Trend Reporting (Q3 2025).” https://sf.freddiemac.com/docs/pdf/loan-reporting-data-trends-q1-2025.pdf
- Freddie Mac. (2025). “Loan Delivery & Repurchase Trend Reporting (Q4 2025).” https://sf.freddiemac.com/docs/pdf/loan-reporting-data-trends-q4-2025.pdf
- Fannie Mae. (2026). “Quality Insider: Understand Top Defects to Help Strengthen Loan Quality.” https://singlefamily.fanniemae.com/originating-underwriting/loan-quality/quality-insider/june-2026
