1.1 Credit Is an Investment in Your Customer (Start Here)

Trade credit is an unsecured, interest-free loan of goods or services to a customer. When we deliver today and agree to be paid in 30 days, we have lent the customer the value of the goods for a month. Every sale on credit is therefore an investment of our cash in that customer, and credit management is how we protect that investment and get it back, in full and on time.

The point of credit management

Credit sells: most business customers expect terms, and a supplier that demands cash loses work to one that does not. But a sale is finished only when the cash is in the bank. Credit management has two jobs: say yes to the right customers on the right terms, and collect on time. Done well, it is a sales tool and a risk control at once, not a “debt police” function that exists to say no.

A new credit controller’s first week

Kudzai Chinembiri, Credit Controller, joins Kuvanya Mining Supplies, which sells spares, protective equipment, fuel and reagents on credit to mines, contractors and a state-owned client, the Power Authority, from depots in Kitwe, Bulawayo and Rustenburg. She works from Kuvanya Shared Services in Harare. Sales are up and profit is healthy, yet Tendai Musarurwa, Group CFO, is negotiating a larger overdraft. Pieter van Wyk, Operations Manager, Mining Supplies, wants to keep supplying a gold mine that pays at about 90 days, two months beyond terms, “because they always pay eventually”. Profit and cash are telling different stories, and Kudzai sets out four implications that run through the whole course.

Implication 1: receivables are an asset only if they are collected

Trade receivables sit among the assets, but an invoice is worth only the cash it eventually brings in. Late debt ties up money, so the business borrows more. Accounting rules also require an allowance for the losses expected on receivables, which cuts profit as soon as the risk is there, before any customer fails and before any write-off. Course 47, Finance for Non-Finance Managers, explains how to read these lines in the accounts.

Implication 2: slow collection costs real money

For Mining Supplies, credit sales of USD 24.0m a year and receivables of USD 3.6m give debtor days of about 55 against terms of 30 days. Debtor days measure how many days of sales are waiting to be collected, and bringing debtor days to 40 would release about USD 970,000 of cash and save about USD 136,000 a year in interest at a fictional 14%. One customer explains almost all of the gap: the Power Authority pays about two months beyond terms, which ties up about USD 967,000 and costs about USD 135,000 a year. A single large, slow customer can do more damage than dozens of small ones, a point Module 3 returns to under concentration.

Worked example W1: What slow collection costs Mining Supplies

What it shows: the cost of slow collection, with the workings on each row. Amounts are in USD thousands; the 14% rate is fictional.

Try it: Enter your own credit sales and receivables, work out your debtor days, then the cash released if you reached your terms plus ten days, priced at your own borrowing rate.

Implication 3: a bad debt costs far more than its face value

When a customer never pays, the business loses the whole invoice, not just the profit on it, and must earn that cash again from new sales: at an 18% gross margin, a USD 180,000 bad debt needs about USD 1,000,000 of new sales to replace. Preventing one loss is often worth more than winning many new orders.

Worked example W2: New sales needed to replace a bad debt

What it shows: that the thinner the margin, the more new sales a bad debt takes to replace.

Try it: Take one overdue balance and your gross margin. How much new business would replace it if it were never paid?

Implication 4: the biggest balance is not always the biggest risk

Risk depends on how likely a customer is to fail to pay (probability of default, PD), how much we would lose if it did (loss given default, LGD) and how much it owes (exposure). Multiplied together, they give the expected loss, taught in lesson 1.3.

Worked example W3: Where the risk really sits

What it shows: the smallest balance carrying the largest expected loss. The Power Authority owes most but is unlikely to fail outright; the drilling contractor owes little but is fragile, with a Z-score of about 1.25 (lesson 1.3). PD and LGD are fictional.

Try it: List your five largest balances and the five customers you worry about most. How many appear on both lists?

Five common mistakes

Kudzai’s review of the old files finds the mistakes behind most credit losses. Lesson 2.1 gives a fix for each.

1. No written credit policy.
2. Limits set once and never reviewed.
3. Sales and credit working against each other.
4. Chasing the wrong person, often the buyer.
5. No early, firm contact before a debt is old.

The credit cycle

How to use this course

Each module ends with a toolkit, and each worked table can be rebuilt with your own figures. Story figures are fictional and come from one data set. Published methods are credited where they are used. No country’s law is taught; Module 5 gives legal principles to check where you and your customers trade.

This course is independent. It explains published credit and collection methods in its own words and credits each one where it is used. It is not endorsed by, or affiliated with, any author, institute, standard-setter, credit agency or organisation named in it.

About the case company: Kuvanya Group, its subsidiaries (Kuvanya Bank, KuvaTel, KuvaPay, Kuvanya Mining Supplies and Kuvanya Shared Services), its client “the Power Authority” and every person named in this course are fictional. They were created by EunoiaData for teaching purposes only. Any resemblance to real organisations or people is coincidental. Countries, laws and regulators are real and are described as they stood in 2026.

Example: in an old file Kudzai finds a Lusaka contractor, a past case from before she joined, that ordered steadily for a year, doubled its orders for two months and then stopped answering calls. The signs were there: a jump in volume with no new contract behind it, payments slipping from 30 to 60 days, and a new contact name on every order. No one reviewed the limit. Kudzai adds “sharp change in ordering” to her review triggers.

Three views

• As the credit controller: I protect the cash we invest in customers and help sales say yes safely.
• As the sales manager: Terms help me win business; I want quick answers and the rules up front.
• As the finance director: Debtor days drive borrowing. I want cash released and no allowance surprises.

Check before you act: Examples use the fictional Kuvanya Group, its people and figures for illustration only. Rates, scores, limits and loss figures are illustrative, not benchmarks. Adapt each tool to your organisation’s credit policy and ask your finance team which definitions apply.

Key takeaway

Every credit sale is cash invested in a customer. Managing credit decides how much of that cash comes back, how soon and at what cost.