US Commercial Lending (Commercial Real Estate + C&I business loans)
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 the financial package and provenance-tags every statement line.
Watch a single agent in depth
Fully instrumented. Run it live.
- 1INTAKE
- 2SPREAD
- 3RATIOS
- 4COVENANTS
- 5MEMO
- 6LEDGER
Classify the borrower & deal
AutoIdentified an LLC borrowing against a 12-unit multifamily; loaded 2 years of returns, financial statements, a rent roll and the loan docs.
The market, from zero
No finance background needed - tap any step.
01Origination / Sourcing
Days to several weeks, depending on how fast the borrower sends documentsA banker (the relationship manager) finds, or is approached by, a business that wants to borrow. They talk through what the company needs the money for, how much, and roughly what the deal would look like, then collect the first batch of documents.
Who: Relationship Manager (the salesperson-banker) and the borrower
Where Arbiter fits
The first workflow to automate - and where a human stays in.
Automated credit spreading & covenant extraction before committee
Spreading is the slow, error-prone front step whose mistakes poison every downstream ratio.
- Map each statement line to the template
- Compute DSCR, LTV, debt yield, cash flow
- Extract covenants and existing debt
- Analyst reviews low-confidence flagged cells
- Committee keeps the lend-or-decline vote
The PRD
Tap any section to expand it.
Who's involved
Who touches the deal, and what each does.
The face of the bank to the business. They bring in the deal, figure out what the client needs, and shepherd it through the bank, but they don't usually do the number-crunching themselves. Think of them as the account owner who sells and negotiates.
The person who does the grunt work: re-types the financial statements into the bank's template (spreading), calculates the ratios, and drafts the credit memo. Most of the manual hours on a deal are theirs.
A senior banker (or a panel of them) who reads the credit memo and votes yes or no. They are the gatekeepers protecting the bank from bad loans; bigger or riskier loans need more senior or more people to sign off.
An outside expert hired to give a professional, unbiased estimate of what a building is worth. The bank needs this to know how big a loan is safe versus the value of the collateral.
Writes the binding legal contract, including the covenants (rules the borrower must follow), makes sure the bank's claim on the collateral is legally airtight, and handles the closing.
The company that wants the money, plus the owners who personally promise to repay if the business can't (the guarantors). Their tax returns and financials are the raw material the whole process runs on.
Every document, decoded
Tap a document - what it is, why it matters, an example.
Business tax returns
The tax forms the company files with the IRS, showing its income and expenses. Banks use these because they're hard to fake and give a few years of history.
They are the most trusted source of a company's real earnings and are the starting point for spreading and cash-flow analysis.
A 3-year stack of Form 1120-S returns for 'Maple Street Diner LLC' showing $1.2M revenue and $180K net profit in the most recent year, used to confirm the business earns enough to cover a new $500K equipment loan.
What it costs
Who pays for what - illustrative figures.
More for large or complex properties; a common cause of delay as well as cost.
Checks the property for contamination risk; often required on CRE deals.
The bank's upfront charge for making the loan.
Lawyers drafting and closing the loan; scales with deal complexity.
The labor the AI wedge targets; spreading one entity's return alone is ~30-60 minutes.
Hero metrics
The numbers the worker has to move.
How much human time an analyst spends to take one loan from raw documents to a committee-ready memo. Lower is better and means cheaper, faster lending.
How long from receiving the borrower's documents until the finished memo is ready for a decision.
How often a number gets mistyped or mis-mapped when financials are copied into the bank's template. Errors here poison every downstream ratio and decision.
The share of memos that reach the committee complete and correct the first time, without being bounced back for missing data or mistakes.
Cash the business or property generates divided by the loan payments. Above 1.0 means it earns more than enough to pay; banks want a cushion.
Loan amount divided by the appraised value of what backs it. Lower means the bank has more cushion if it has to sell the collateral.
Who else is here
10 players already serving this vertical, and the gap each leaves.
Builds client-tailored ML credit underwriting models (600+ live models, 50+ patents) plus fraud detection. Optimizes policies/cut-offs to auto-decis…
Gap: Sells the decision engine but not the system of record, so depends on LOS partners for distribution; concentrated in c…
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…
AI-driven business-lending origination platform automating the SMB/commercial lending workflow from application to decision to closing (incl. SBA au…
Gap: Decisioning still largely supports human credit approval rather than fully automating it; SMB/commercial credit is het…
Commercial-lending credit platform for consistent financial spreading, dual risk-rating models (or bank-configured policies), benchmarking, and BPMN…
Gap: Primarily a spreading/risk-rating and workflow tool that informs human credit committees rather than auto-deciding; co…
Compliance, credit-risk and lending platform for 2,400+ community banks/CUs: loan origination, Sageworks credit analysis/spreading, CECL/ALM modelin…
Gap: AI is assistive (narratives, extraction, review acceleration) rather than autonomous decisioning; serves smaller insti…
Dominant P&C insurance core suite (InsuranceSuite: PolicyCenter, ClaimCenter, BillingCenter, plus UnderwritingCenter) on Guidewire Cloud. Adding an …
Gap: Core-platform conservatism and human-in-the-loop governance cap autonomy; AI is largely an orchestration/assist layer …
End-to-end P&C core SaaS (Duck Creek OnDemand: policy, billing, claims) and the main challenger to Guidewire. Launched an insurance-native Agentic A…
Gap: Smaller installed base than Guidewire; agentic apps are newly launched and unproven at scale; like all core suites it …
Actuarial AI platform that automates insurance pricing and reserving using proprietary Transparent Machine Learning (TML) on GLM/GAM structures - bu…
Gap: Automates model-building, not the bind/decision - actuaries retain control and regulators approve rates, so it acceler…
Generative-AI underwriting solution that ingests an insurer's own guidelines/risk appetite, then assesses submissions (SOVs, applications, loss runs…
Gap: Early-stage and venture-funded vs. entrenched cores; produces a risk assessment/score that supports the underwriter ra…
Jargon, decoded
Every term on this page - search it.
Re-typing a borrower's tax returns and financial statements line-by-line into the bank's standardized template so every borrower can be compared the same way.
e.g. An analyst enters each line of 'Maple Street Diner's' 3 years of tax returns into the bank's credit software to build a clean, comparable financial picture.
The structured write-up that summarizes the analysis, ratios, risks, and a recommendation, and is the document the decision-makers actually read.
e.g. A 12-page memo concluding 'recommend approval of a $500K equipment loan to Maple Street Diner with a 1.40x debt-service coverage and a personal guaranty.'
A panel of senior bankers who read the memo and vote to approve or decline larger or riskier loans.
e.g. On Thursday the committee reviews five memos and approves the diner loan with a condition that the owners keep $100K in reserves.
The cash available to pay debt divided by the debt payments owed; it answers 'can they comfortably afford this?'
e.g. A property with $125,000 of net operating income and $100,000 of annual loan payments has a DSCR of 1.25x.
The loan amount divided by the appraised value of the collateral; it answers 'how much skin does the borrower have versus the bank?'
e.g. A $750,000 loan on a building appraised at $1,000,000 is a 75% LTV.
The property's annual net income divided by the loan amount, showing the bank's plain cash return if it had to take the property over, independent of interest rates or appraised value.
e.g. A property earning $100,000 net income with a $1,000,000 loan has a 10% debt yield.
A combined view of all the income and expenses of both the business and its owners (guarantors), to see the total ability to repay.
e.g. A property that barely covers its own loan still qualifies because the owner's separate $200,000 salary is added in to show total repayment capacity.
For a property, the rent collected minus the cost of running the building, before any loan payments.
e.g. An apartment building collecting $360,000 of rent with $135,000 of operating costs has an NOI of $225,000.
A rule written into the loan contract that the borrower must keep following, acting as an early-warning tripwire for the bank.
e.g. A covenant requiring the borrower to keep total debt below 3x annual earnings; exceeding it is a breach the bank can act on.
The dollar limit on a revolving credit line, set by the value of the borrower's invoices and inventory and recalculated regularly.
e.g. With $2M of eligible invoices at an 80% advance rate, the borrowing base allows up to $1.6M to be drawn that month.
A person (usually a business owner) who personally promises to repay the loan if the business cannot.
e.g. The two 50% owners of the diner each sign a personal guaranty, putting their own assets on the line for the $500K loan.
A commercial-and-industrial loan to an operating business for working capital, equipment, or growth, repaid from the company's profits.
e.g. A $250K revolving line of credit a manufacturer draws on to buy raw materials and repays as customers pay their invoices.
A commercial real estate loan to buy, build, or refinance an income-producing property, repaid from the rent the property earns.
e.g. A $3M loan to purchase a strip mall, repaid from the rent its tenants pay.