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Solutions · Loan Underwriting

Retail loan underwriting, automated and audited.

The agent reads the loan application, the bureau report, the income proofs, and the credit policy. It outputs a cited decision — approve, decline, or refer — with every clause and bureau line that fed the decision linked back. Your credit officers see the recommendation in their existing console; they confirm or override, never start from scratch.

Reference
Solution architecture in repo · pilots open
RBI-grade
Audit chain reconstructable from cold storage
Multilingual
Document ingest in English, Hindi, regional

Products in scope

Personal loan

Salaried and self-employed, ticket sizes up to ~₹10L. Highest-volume retail product; touchless rate tuned per pilot.

Two-wheeler loan

Volume-heavy, narrow policy. Quick to deploy because the policy corpus is compact; touchless rate tuned per pilot.

Gold loan

Asset-backed, fast turnaround. The agent verifies the asset photos, weighment, and KYC against the policy; touchless rate tuned per pilot.

Education loan

Long-form documentation, multilingual transcripts, institution-wise eligibility — agent handles the parsing burden.

Loan underwriting FAQ

Which products does this work for?

Strong fit for retail credit: personal loans, two-wheeler, gold loans, education, agri-credit, small-ticket business loans. Mortgage and large-ticket commercial credit need additional engagement scoping but use the same primitives.

How does it integrate with existing LOS?

Vihaya plugs into your existing Loan Origination System as a decisioning service. The LOS continues to be the system of record; Vihaya is called for the underwriting decision and returns approve / decline / refer with cited rationale.

What about rule engines like FICO Origination Manager?

Rule engines stay for hard-policy filters (income thresholds, score cutoffs). Vihaya handles document parsing, judgement-grade evaluations, and exception cases the rule engine can't decide.

Is this RBI-examiner defensible?

Yes. Every decision row links to the policy clauses, bureau-data points, and exception paths that produced it. The audit chain is reconstructable from cold storage years later — exactly what RBI examiners ask for.

Want to see this in your environment?

30-minute discovery call. Draft SOW within 5 business days.

Talk to us about a pilot