Calculator

Estimate your verification-effort savings.

A transparent model of the operational effort saved when evidence assembly moves to a reusable, pre-verified pack. Every assumption is a slider — adjust them to your reality.

200
90 min
₹800
30%
30%

You still review the pack — this is the share of today’s effort that remains. Repeat borrowers reuse an existing pack, so they cost about half this.

Estimated manual hours avoided / month

224 hrs

of 300 hrs spent today

Estimated operational cost avoided

₹1,78,800 /mo

₹21,45,600 / year

Cost per reviewed application

₹1,200₹306
Talk to us about a pilot →

What this is — and isn’t

This estimates operational verification effort only — staff time and its cost. It is not a projection of credit approvals, default rates, recovery, or financing outcomes. AssureLocker is a technology service provider; lenders own all credit decisions. Figures are indicative and depend on the assumptions you set above.

AssureLocker
Right Vectors India
3rd floor, Innov8, SKCL Tech Square,
SIDCO Industrial Estate, Guindy,
Chennai, TN 600032

AssureLocker is a verification & orchestration platform — not a lender. It supplies verified evidence and risk signals checked against authoritative sources (GSTN, MCA21, EPFO, CERSAI, Account Aggregator) and orchestrates the assessment room. It does not lend, hold or move funds, operate escrow, set advance rates, or make the credit decision — the lender's system of record makes that decision and disburses. Right Vectors India, the provider of AssureLocker, operates strictly as a Technology Service Provider. Every signal is labelled by evidence tier — registry-verified, lender-side, issuer-confirmed, document-signed or self-declared (missing where unresolved); some integrations are in sandbox, lender-side or pilot, and records are written to an immutable registry (hashes only — never raw PII). Signals and figures are point-in-time and consent-bound; confidential to the named parties.

Explainable, evidence-tiered signals — auditable on request. Our algorithmic-accountability approach →

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