Business loan · amount, tenure, financials, collateral
Status: evidence in · waiting on a recommendation
The application, the policy, and the evidence sit on one case. The agent compares them and recommends approve, decline, or refer, with the rule named. An underwriter binds the decision. The file stays on your network.
Cap: facility must sit inside the product limit.
Collateral: must be registered before drawdown.
Two items on this file are still open.
Credit policy · collateral · §4The screens above are a sample of the workspace. They play on their own. Select a step to hold it.
Underwriters re-read the same policy against every application. The recommendation lives in a note that audit rebuilds later. Capacity, not demand, sets how many cases clear.
EazyAI prepares the case from the evidence you uploaded and names the rule. The underwriter binds approve, decline, or refer. The model does not release the risk.
Four moves. The sources are yours. The answer names them. A person keeps the decision that matters.
Application, financials, collateral, and the policy. The file stays on your network.
The agent checks the evidence you supplied and names the clause.
Approve, decline, or refer. Missing evidence stays an open item.
The underwriter signs. The report is the record of the case.
Underwriting Intelligence runs every product on the same case model. Agri, personal, EMI, and insurance reuse it.
Application or restructure opens one case.
Documents, KYC, bureau, and collateral land together.
Named risk dimensions, each tied to a source and a policy rule.
Recommend approve, decline, or refer. Gaps stay open.
The audit is written with the officer’s bind.
From the same pattern used for Underwriting Intelligence engagements: Dual RAG over policy, KYC, and bureau data; officer binds every call.
The model scores named dimensions and cites the rule. Approve, decline, or refer is never automatic. The trail is written with the decision.
Agri applications arrived as PDFs, photos, and spreadsheets. Officers spent days assembling land, crop, income, and collateral evidence before analysis even started. Every product line had its own process, and the audit was rebuilt after the decision.
Underwriting Intelligence on the lender’s own network. Intake opens one case. Evidence cross-checks documents. Analysis scores risk dimensions with citations. The officer binds. The report is generated from the same case.
Throughput rose because officers started at analysis instead of document hunting. Risk scores were comparable across files, and exceptions were queued for people rather than buried. The same case model extended to EMI restructuring and insurance with no new stack.
Where the agent takes over routine work, where it speeds judgment, and where a committee still decides.
File assembly and KYC chasing. Retail loan analysis against named policy rules with citations. Routine files reach the officer ready to bind.
Agri and microfinance dimensions (land, crop, weather, repayment, collateral). EMI restructuring options drafted from ability-to-pay evidence.
Credit committee packs with dissent listed. Insurance claims assist: coverage check and packet prep; the adjuster decides.
One workspace. Your policy. A person binds each product line.
Personal, business, home, auto, and microfinance through the same five steps.
Crop facilities and restructuring without a second stack or a new control gap.
Sum insured and claims assist sit on the book you already govern.
On your premises or your private cloud. Dual RAG cites the passage. The model you serve is the one you register. A demo is the way onto a first workflow.
The questions a credit committee asks about Underwriting Intelligence.
No. It recommends approve, decline, or refer from the evidence. A person binds the decision. Funds are not released by the agent.
For agri files, land, crop, weather, repayment capacity, and collateral are each scored with their evidence. An officer can challenge any one dimension.
Yes. The same Intake → Evidence → Analysis → Decision → Report pattern extends without a new platform.
On infrastructure you control. Hybrid sovereignty: data and models stay where you put them; EazyAI orchestrates via secure APIs.
Same platform. A different set of sources and a different person in the loop.
Book a demo. A first workflow in two to three days. Your data stays where it is.