Regularity of collections, average settlement time, sales seasonality, reminder history: which signals really announce a delay? This study explains how Kweli's proprietary credit score combines these variables, what it brings to the distributor when delivering on credit, and how it opens access to stock financing with our partners.
A simple question, poorly equipped
Should this point of sale be delivered on credit? It is a distributor's most frequent decision, and the least equipped. It relies on the rep's memory, the personal relationship and the urge to sell. Kweli's credit score does not replace that judgement - it gives it a basis: the POS's real payment history, observed receivable by receivable.
What the score looks at
The score combines four families of signals. Settlement regularity - a POS that always pays on D+2 is better than one that alternates D+0 and D+15. Average settlement time, and above all its recent trend. Sales seasonality, so as not to penalise an expected dip. And reminder history: a POS that needed three reminders last month is slipping, even if it ended up paying.
Regularity weighs more than volume
This is the most useful lesson for reps: a small point of sale that pays on time scores higher than a large one that pays late. The score measures reliability, not size. It naturally shifts sales effort towards the POS worth developing, rather than those that bring volume at the cost of receivables.
How it is used in the field
When preparing a delivery, the rep sees the POS score and the recommended credit limit. Above the threshold, the delivery is confirmed. Below, it switches to Mobile Money prepayment - without argument, because the rule is the same for all and known in advance. The score updates with every collection: a POS that recovers regains its credit within weeks.
From collection to financing
A network whose points of sale are scored is a legible network. That is what allows Kweli to present to its financing partners distributors whose payment discipline is proven, and to open stock financing to them. Collection data stops being an observation and becomes an asset.