29%
of small business credit applicants applied at online lenders in 2025, up from 17% in 2020. (Federal Reserve Banks, Small Business Credit Survey, 2026)
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Agentic Loan Processing
Xebia Agentic Loan Processing is an agentic AI solution for US banks and credit unions that collects, verifies and analyzes retail and commercial loan applications, then gives underwriters and credit teams a decision-ready file, with every value linked to its source and the credit decision left to people.
29%
of small business credit applicants applied at online lenders in 2025, up from 17% in 2020. (Federal Reserve Banks, Small Business Credit Survey, 2026)
$2.1T
in US single-family mortgage originations forecast for 2026. (Mortgage Bankers Association, October 2026)
20–60%
potential productivity increase when AI agents draft credit-risk memos, in a proof of concept at a retail bank, including a 30% improvement in credit turnaround. (McKinsey, 2025)
Why it matters
Most of the time goes before anyone makes a credit decision: re-keying, mailed verifications and cash flow built by hand.
Figures are re-entered into the LOS, and errors surface at underwriting.
A written VOE or 4506-C request can sit for three to ten days.
Analysts categorize bank statements line by line before analysis starts.
Small business borrowers leave at the document stage, often for an online lender.
What it is
Every application becomes a verified, decision-ready file, not a stack of documents waiting in a queue.
Agents chase missing files and cross-check names, IDs and figures across every upload.
01
IRS, payroll, bank and bureau data come in directly. Conflicts the agents can’t settle go to a person.
02
Transactions become a monthly cash-flow view, with DTI, DSCR, reserves and a retail score.
03
Retail files arrive with plain-language reasons, commercial files with a draft loan credit memo.
04
How it works
| Stage | Input | What the agents do | Output |
|---|---|---|---|
| Stage 01 Apply | Online, mobile or loan officer-led applications | Verify identity and run KYC or KYB checks | Verified applicant and open application |
| Stage 02 Collect | Pay stubs, tax returns, financials, bank statements | Show the checklist and chase missing files | Complete, classified document set |
| Stage 03 Check | Uploaded files and verified-source data | Mask personal data, extract and cross-check every value | Pre-filled application with discrepancy flags |
| Stage 04 Verify | IRS, payroll, employer and bank data | Verify income and assets at source, categorize transactions | Verified income, assets and ledger |
| Stage 05 Analyze | Verified data and bureau data | Build cash flow; compute DTI, DSCR and reserves | Cash-flow view, metrics and retail score |
| Stage 06 Recommend | Stages 01 to 05 and your credit policy | Draft the reasons or credit memo and route the file. A person decides. | Recommendation or credit memo for your team |
Six stages from application to a decision-ready file. Your institution decides which steps wait for a person’s approval.
Every automated step can be set to require a person’s review, and your institution decides which. You set the thresholds that route files to an analyst, an underwriter or the credit committee. Your people or your decision engine make the credit decision.
| Outcome | Most organizations today | With Xebia Agentic Loan Processing |
|---|---|---|
Borrower experience |
Borrowers re-send documents and can’t see where their application stands. | Ask once. Agents request exactly what’s missing, and status is visible live. |
Time to a ready file |
Mailed VOE and 4506-C requests can take three to ten days each. | Verification without the wait. Agents pull income and asset data at source, in parallel. |
Underwriter and analyst time |
Underwriters read whole files; analysts spread statements line by line. | Exceptions, not every line. The file and cash-flow view are built before review. |
Compliance and fair lending |
Reasons and notes are written after the fact. | Every value on record. Sources, plain-language reasons, reviewer and timestamp are logged. |
Illustrative Example
Challenge: An S-corp borrower brings two years of tax returns, interim financials, three months of bank statements and formation papers, with figures that may not match across documents.
Approach: Agents extract and cross-check every value against IRS and bank data, build a monthly cash-flow view with DSCR, and send unusual transactions to an analyst before the credit memo reaches the credit team.
US banks and credit unions, across commercial and retail lending. Each build is configured to your credit policy, systems and loan products.
In use today. Builds the monthly cash-flow view, computes DSCR and drafts the loan credit memo.
In use today. Verifies income and assets at source and clears routine conditions before underwriting.
Configured per institution. The same agents and stages, set up for each product’s rules and checklists.
Start with a pilot
We’ll run the solution on one loan product you choose and measure it against your current process.
Our ideas

Demand isn’t the problem. The time goes before anyone makes a decision.

Interview with Xebia’s Naveen Gupta on where loan files stall, and how AI agents build a decision-ready file.

How agentic AI turns document-heavy underwriting files into clear, traceable decisions.
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