US Residential Mortgage
The live prototype first - the market and the spec are below.
How the agents work together
One file, the whole fleet - a safeguard on every handoff.
Reads every document, extracts fields with provenance, flags tampering.
Watch a single agent in depth
Fully instrumented. Run it live.
- 1INTAKE
- 2EXTRACT
- 3DERIVE
- 4TEST
- 5CHECKPOINT
- 6LEDGER
Classify the file & documents
AutoIdentified a conforming purchase with self-employed income; loaded 18 documents.
The market, from zero
No finance background needed - tap any step.
01Application (Apply)
Day 0; often completed in 1-3 daysThe borrower fills out a standard form (the URLA / Form 1003) telling the lender who they are, how much they earn, what they own, and which house they want to buy. Think of it as the master intake form for the whole loan.
Who: Borrower + Loan Officer (the salesperson at the lender who guides them)
Where Arbiter fits
The first workflow to automate - and where a human stays in.
Automated income calculation on conforming purchase loans
Income calc is the most error-prone step, and bad math forces costly GSE buybacks.
- Classify each income source, pick the method
- Average variable bonus & commission income
- Reconcile the calc vs 1003 and AUS
- Underwriter signs the final qualifying income
- Human adjudicates declining self-employed income
The PRD
Tap any section to expand it.
Who's involved
Who touches the deal, and what each does.
The homebuyer. They supply all the documents, pay closing costs and a down payment, and make the monthly payment for years.
The person who helps the borrower apply, picks a loan product, and quotes a rate. A loan officer works for one lender; a broker shops multiple lenders. They earn commission, so they're motivated to get loans to close.
The behind-the-scenes coordinator who collects every document, orders the appraisal and title, and chases missing items so the file is complete before a decision.
The risk gatekeeper. They verify the borrower can actually repay and the file follows the rulebook, then approve (often 'conditionally') or decline. The most judgment-heavy human in the chain.
A licensed, neutral expert who decides what the home is actually worth so the lender doesn't over-lend. Required by law to be independent from the loan's sales side.
The business whose money actually buys the house at closing. Can be a bank or an independent mortgage bank (IMB). Most lenders sell the loan soon after, recycling their cash into the next loan.
Two huge quasi-government companies that buy 'normal' (conforming) mortgages from lenders, guarantee them, and bundle them into bonds. They effectively write the rulebook (Selling Guide) that most US loans must follow. GSE = Government-Sponsored Enterprise.
A government agency that doesn't buy loans itself but guarantees the bonds made from FHA and VA (government-insured) loans, making them safe for investors. Backed by the full faith of the US government.
Pension funds, insurers, banks, and foreign governments who buy mortgage-backed securities for steady returns. Their money is the ultimate source of nearly all US mortgage funding.
The company the borrower actually pays each month. It distributes the money, runs the escrow account for taxes and insurance, and handles hardship cases. Often a different company than the lender or the loan owner.
A neutral third party that confirms the seller really owns the home (clear title), holds everyone's money safely during the deal, and handles the signing and transfer of ownership at closing.
Every document, decoded
Tap a document - what it is, why it matters, an example.
URLA / Form 1003 (Uniform Residential Loan Application)
The master application form every borrower fills out. It captures who you are, your job and income, what you own and owe, and details of the home and loan you want. Standardized by Fannie Mae and Freddie Mac so every lender uses the same form.
It's the single source of truth the entire loan is built on. Every other document exists to prove what the borrower wrote here is true.
Jane Smith, SSN 123-45-6789, born 1988; employed as a nurse at City Hospital for 4 years earning $7,500/month base plus $500/month overtime; has $40,000 in a Chase savings account; applying for a $360,000 loan to buy 12 Oak Street for $450,000.
What it costs
Who pays for what - illustrative figures.
One-time fees paid at closing: lender origination fee, appraisal, title insurance, escrow setup, recording, and prepaid taxes/insurance. On a $360,000 loan, 2-5% is roughly $7,200-$18,000.
The borrower's own cash put toward the purchase, separate from closing costs. As low as 3% on some conforming loans; under 20% usually triggers extra mortgage insurance.
What it costs the lender to make one loan: loan officer commissions, processing/underwriting labor, technology, compliance, and overhead. This is the cost an AI digital worker most directly attacks.
Margins are razor-thin and swing between profit and loss year to year, which is exactly why lenders are desperate to cut the ~$11k cost-to-originate.
PITI = Principal, Interest, Taxes, Insurance. The servicer collects this and routes the tax and insurance portions through the escrow account.
Hero metrics
The numbers the worker has to move.
The total it costs a lender to produce one mortgage, from labor to technology to compliance. The headline efficiency number for the industry.
How many days from application to the loan funding. Faster is better for the borrower's experience and the lender's cost.
Of all the applications a lender takes, the share that actually make it to a funded loan. Low pull-through means wasted work and cost on loans that never close.
The share of closed loans found to contain a mistake (most often a miscalculated income figure) during quality-control review. Defects can force the lender to fix or buy the loan back.
How often Fannie Mae or Freddie Mac forces the lender to buy back a loan it already sold, because the loan broke the rules (often a bad income calculation). Each repurchase is very expensive for the lender.
Who else is here
7 players already serving this vertical, and the gap each leaves.
Operates Encompass, the dominant US mortgage LOS / system-of-record, plus a servicing platform. Layering "Aurora" agentic AI and Mortgage Analyzers …
Gap: Explicitly keeps AI out of final approval/pricing/disclosure decisions, so it assists rather than decides; legacy arch…
Rocket's proprietary lender-native AI platform is Rocket Logic (and Navigator), built on 10+ petabytes of proprietary data and 50M+ annual call tran…
Gap: Primarily a captive tool optimizing Rocket's own pipeline, not an open platform competitors can buy; underwriter overs…
Leading digital origination / POS platform for banks, credit unions and mortgage lenders (powered $1.2T in applications in 2024). Launched "Intellig…
Gap: Historically a front-end (conversion) layer, not the decision engine; profitability pressure as a public company; agen…
Mortgage technology and services provider behind FinXperience (collaboration POS), FinConnect (130+ integrations/data services), and the newer TOUCH…
Gap: Overlay/services model means less ownership of the system of record or final decision than ICE or in-house lender AI; …
Loan Engineering System (LES) powered by CogniTech expert-systems / "autonomous machine" technology (US patent awarded Sept 2022). Performs income, …
Gap: Single-vertical (mortgage) point engine dependent on integrating into others' LOS/POS; smaller scale and distribution …
Document-AI platform that extracts and structures data from 100s of document types (bank statements, pay stubs, tax forms) at 99%+ accuracy with hum…
Gap: Sits below the decision - it verifies and feeds data but does not make the credit decision, so it is a component vulne…
Cloud bank operating system (on Salesforce) spanning onboarding, account opening, loan origination, credit analysis, and portfolio management. nIQ D…
Gap: AI is largely an assistive copilot/data-recognition layer, not autonomous decisioning - bankers still drive credit dec…
Jargon, decoded
Every term on this page - search it.
A mortgage that follows Fannie Mae and Freddie Mac's rules and stays under their size limit, so it can be sold to them.
e.g. A $360,000 loan that meets credit, income, and size guidelines is conforming; a $2 million loan exceeds the limit and is 'jumbo' (non-conforming).
A quasi-government company chartered by Congress to support a market; in mortgages this means Fannie Mae and Freddie Mac.
e.g. When a lender says 'the GSEs require two years of tax returns,' they mean Fannie Mae and Freddie Mac's shared rulebook demands it.
The marketplace where lenders sell loans they've already made to bigger buyers, instead of holding them.
e.g. A local lender sells your fresh mortgage to Fannie Mae a month after closing so it gets its cash back to lend again.
A bond made by pooling thousands of mortgages together so investors can buy a slice of the monthly payments.
e.g. A pension fund buys $10 million of a Fannie Mae MBS and earns returns from the combined monthly payments of thousands of homeowners.
The process of bundling many loans into a tradable bond (an MBS) and selling it to investors.
e.g. Freddie Mac takes 5,000 conforming loans, guarantees them, and securitizes them into a bond it sells on Wall Street.
Software that instantly checks a loan against the rules and recommends approve or deny.
e.g. The lender runs the file through Desktop Underwriter and gets back 'Approve/Eligible' in seconds.
The two main automated underwriting systems: DU is Fannie Mae's, LPA is Freddie Mac's.
e.g. A self-employed borrower's file is run through LPA because Freddie Mac's system is historically more flexible on non-traditional income.
The process of evaluating whether a borrower and property are safe enough to lend on, ending in an approve/deny decision.
e.g. During underwriting, the underwriter recalculates the borrower's income from tax returns and confirms the appraised value covers the loan.
A holding account the servicer uses to collect a slice of each monthly payment and pay the borrower's property taxes and insurance when due.
e.g. Jane's $2,400 monthly payment includes $400 that goes into escrow, which the servicer uses to pay her $3,600 property tax bill and $1,200 insurance bill each year.
The four parts of a typical monthly mortgage payment: Principal, Interest, Taxes, and Insurance.
e.g. A $2,400 PITI payment might be $1,500 principal+interest, $700 taxes, and $200 homeowner's insurance.
The ongoing job of collecting payments, running escrow, and handling the loan day-to-day after it closes.
e.g. Three months after closing, Jane gets a letter saying her servicing has transferred and she now pays a company she's never heard of.
The reliable monthly income figure an underwriter calculates and uses to decide how big a loan the borrower can afford.
e.g. A freelancer reports wildly different yearly earnings, so the underwriter averages two years of tax returns to set qualifying income at $6,250/month.
A mistake found in a closed loan during quality-control review, most commonly a miscalculated income figure.
e.g. A QC review finds the underwriter counted a one-time bonus as recurring income, creating an income-calculation defect.
When Fannie or Freddie forces a lender to buy back a sold loan because it violated the rules.
e.g. Because the income was overstated by a defect, Fannie Mae demands the lender repurchase the $360,000 loan at full price.
The share of loan applications that actually close and fund.
e.g. If a lender takes 100 applications and 77 close, its pull-through rate is 77%.
An underwriter's 'yes, but' - approval that depends on the borrower supplying a final list of items.
e.g. The loan is approved on the condition the borrower provides one more pay stub and a letter explaining a $5,000 deposit.
The loan amount as a percentage of the home's value; lower means more borrower equity and less lender risk.
e.g. A $360,000 loan on a $450,000 home is an 80% LTV, meaning the borrower put 20% down.