Platform / Analytics
The book, explained - not another export to Excel
Operations dashboards, AI cohort intelligence, recovery forecasts and agent performance, computed on the live book and rendered in the units Indian lending actually uses.
How it runs
Analytics end to end
The same shape on every account: the flow acts, the world answers, the account is written. Nothing depends on someone remembering.
- 1CaptureEvery contact, disposition, promise and payment is written as it happens.
- 2CohortCut by bucket, product, vintage, campaign, channel and caller.
- 3CompareRoll rate and cure rate on a fixed cohort, not a moving denominator.
- 4ForecastExpected recovery on the live book, with the assumptions visible.
- 5ActThe finding changes a flow, a cap or an allocation rule, not a slide.
The change lands in the strategy, and the next cohort measures whether it worked.
What it does
The working parts
Each part is a real record in the platform, not a feature on a slide. 4 of them make up analytics.
Operations dashboard
Portfolio health, contact funnels, channel performance, batch lifecycle - filtered by campaign, DPD bucket, status and risk tier.
AI intelligence
Risk distribution, predictive cures, settlement opportunity, contact-time heatmaps and risk migration - cohort views that tell you where to spend the next rupee of effort.
Recovery forecast
Expected recovery by cohort with the assumptions visible, so risk and finance argue about inputs, not arithmetic.
Agent and campaign performance
Human and AI agents on the same yardstick: connects, promises, cures, complaint rates.
- Live book
- Fixed cohort
- Every cut
Reporting runs on the working data, not a nightly copy.
Both directions, because holding an account static is not success.
A number on a dashboard opens the accounts behind it.
- Accounts allocated10,000
- Contact attempted9,40094% of previous
- Connected5,80062% of previous
Right party, not just answered.
- Promise captured with a date1,95034% of previous
- Promise kept1,18061% of previous
The only rung that becomes money.
Illustrative shape, not a claim about a real book. The point is that the platform computes every rung from records it already holds, so the drop between any two is traceable to the accounts inside it.
Controls and outputs
What you set, and what you get back
Every control is a setting in the admin app with an audit trail; every output is a record on the borrower, not a spreadsheet.
Settings are per tenant and per campaign, and every change is attributable. Outputs are written as the work happens, not assembled afterwards.
Part of one system
Analytics does not work alone
The signals it produces are read by the rest of the platform the same second. These two are the closest neighbours.
Payments
The shortest path from promise to money in the account
Payment links, UPI and NACH, promises tracked to the day, and a self-service portal where a borrower can settle at midnight without speaking to anyone.
Open paymentsCompliance
Compliance as physics, not policy
Quiet hours, consent, contact caps and evidence are enforced by the engine itself. A call that would breach the rules is not flagged afterwards - it is never placed.
Open complianceQuestions
Before a pilot on analytics
The questions a collections head or an infosec team asks first. Anything else, an engineer answers on the demo call.
Can we pivot the raw data ourselves?
Yes. A browser pivot over the account and touch data, saved views, and scheduled reports by email. For deeper work, exports and a read API.
Is there borrower-level intelligence?
Each account carries a risk tier, a propensity estimate, a best channel and time, and a conversation prep for the caller. Cohort views aggregate the same signals.
How fresh are the dashboards?
Operational views read live data. Heavier aggregates refresh on a schedule you can see on the page, and every figure states its as-at time.
Further reading
Notes that go deeper
Written for practitioners, ungated, and specific to Indian lending.
Roll rates: the number that tells you about next quarter
Recovery percentage tells you how last month went. Roll rate tells you what is coming. It is the closest thing collections has to a leading indicator, and it is usually calculated wrong.
ReadCost to collect, computed honestly
Most cost-to-collect numbers are a commission rate with some overhead added. The useful version tells you which rupees you are spending to chase rupees you were never going to get.
ReadBring one delinquent cohort. We will run it.
A demo here is not a slideshow. Pick a segment of your book, watch a flow built for it, and hear an agent call a test number in your language.