Kisti and collections

Predicting a default before it happens: six signals in your own data

Partial payments, slipping payment dates, ignored reminders and channel switches — how to score risk and act two months early.

· PropERP· 3 min read

পড়ুন বাংলায়

An early-warning indicator on a collections dashboard
Warning sign shows gas alert in industrial area by Shixart1985 (CC BY 2.0)

Buyers almost never stop paying suddenly. The pattern is consistent: payment dates start slipping, amounts start arriving short, reminders stop getting replies, and only then does a full instalment get missed. Every step of that is already recorded in your own system, which means default is predictable two to four months ahead without any new data collection.

The six signals

SignalWhat to measureWhy it predicts
Date driftAverage days late, this quarter versus lastDrift precedes default more reliably than any single late payment
Partial paymentsCount of instalments settled in more than one receiptIndicates the instalment size no longer fits the buyer's cash flow
Reminder engagementReplies and payments within 72 hours of a reminderDisengagement is the strongest single signal
Channel switchingBank to MFS, or larger to smaller amountsOften signals a change in who is paying or how
Contact reachabilityCalls answered, numbers changedAn unreachable buyer is already a recovery case
Balance trajectoryOutstanding as a share of price versus expected at this stageCatches buyers slipping quietly across a long plan

None of these requires new data. All six are already in the receipt history, the message log and the call log — assuming those live in the same place as the schedule.

Building a score you can explain

Keep it simple enough to defend:

  • Date drift over 15 days: 3 points.
  • Two or more partial payments in the last quarter: 2 points.
  • No reply to the last two reminders: 3 points.
  • Number unreachable in the last 30 days: 2 points.
  • Outstanding more than 10 percent above the expected curve: 2 points.

Six or more points puts a buyer on the priority list. Ten or more means a manager calls this week. The specific weights matter far less than applying them consistently and reviewing them against outcomes after a quarter.

What to do with the list

The point of a risk score is to change who gets called first, not to change how they are spoken to. A high-risk buyer at month three still has options: a restructure from the outstanding balance, a shorter payment holiday, a revised schedule that matches their actual income pattern. Those conversations work when the balance is still manageable and fail when it is not. The mechanics of doing them properly are in the overdue recovery playbook.

The project-level signal nobody watches

If risk scores rise across a whole project rather than among individual buyers, the cause is usually the site. Buyers who drive past a stalled construction site stop paying, and no amount of individual follow-up fixes that. The response is progress communication and, where the plan allows, milestone-linked billing that only charges for work actually done. See milestone billing and what a delay costs.

Measuring whether the score works

After one quarter, compare: what share of buyers who actually went 90 days overdue were flagged at least two months earlier, and what share of flagged buyers turned out fine. The first number is the value; the second is the cost. A score that flags forty percent of your book is not a score, it is an alarm nobody will listen to. Tune until the flagged list is small enough for someone to actually call.

What to do next

Take the buyers who went 90 days overdue in the last year and look at their payment history in the six months before. If the drift and partial payments were visible — and they usually are — the same pattern is visible right now in buyers who have not defaulted yet — see risk built from the payment history.

Frequently asked

Do we need machine learning for this?
No. A six-factor score built from your own payment history outperforms intuition immediately, and it can be computed with arithmetic. Models help at scale, but the first version should be a rule you can explain to a collection officer.
How early can a default be seen?
Typically two to four months. The pattern almost always starts with dates slipping and payments arriving short, well before a full instalment is missed.
What do we do with a high-risk buyer?
Talk to them earlier and offer a restructure while the balance is still manageable. A restructure at month three is a customer retained; the same conversation at month twelve is a cancellation negotiation.
Does risk scoring damage the customer relationship?
Only if it is used to be aggressive. Used to prioritise a helpful call before the buyer becomes embarrassed about arrears, it usually improves the relationship.

/solutions/installments

Read next

All articles

Next step

See this working on your own project

Forty minutes, configured on one of your real projects. If the problem in this article is yours, that call is the fastest way to know whether it is solved here.

40 minutes · walked through on your project structure · no card required