Every lender we speak to has a version of the same story: the borrower looked fine — in our book. The stress was accumulating somewhere else: another programme, another lender, a charge registered last quarter, drawdowns quietly accelerating. By the time the bureau cycle told everyone, the conversation had become a provision.
AssureLens is our answer, and it becomes the fourth suite of the AssureLocker platform today — alongside AssureCLA (co-lending assurance), AssureSCF (supply-chain-finance evidence) and AssureVerifID (source-verified identity).
Two modules, one discipline
AssureMap answers the structural question: what is connected, exposed, and supportable? The entity resolved on identifiers (GSTIN, PAN, CIN, Udyam — never on name spellings), facilities assembled with point-in-time history, security mapped with potential overlaps surfaced, capacity compared against your thresholds, and every coverage gap named rather than averaged away.
AssurePulse answers the temporal one: what is accumulating, and how quickly? Facilities, drawdowns and refinancing counted over 7/30/90-day windows against the book's own baseline; debt growth compared with revenue growth; repayment timing measured against the borrower's own history. Growth alone is not a signal — growth beyond capacity is.
The discipline they share: exposure is presented by source class — lender-known, programme, bureau-reported, inferred — and never blended into a total no source supports. "Total exposure across all lenders" is a number nobody in India can honestly compute, so our engine refuses to construct it. And every alert carries its metric, window, baseline, threshold, sources, confidence and limitations — an alert that cannot explain itself is noise with a timestamp.
See it run today
The live simulation computes everything from the real engine on a deterministic synthetic borrower — an elevated facility-velocity call at 300% of baseline, debt outgrowing revenue, repayment drift from 1.3 to 14.5 days, and a surfaced collateral overlap. No mocked numbers.
Where this stands, honestly
AssureLens is at design-partner stage. The engine is built and synthetic-tested; production evaluation stays locked until a design partner's data rights exist. We are selecting one lender portfolio — business loans, MSME, secured or co-lending — to run in shadow mode: historical data replayed through the engine, zero integration risk, results measured against what actually happened. If that sounds like your book, start the conversation.
As with everything we build: signals only — the lender decides.