This document discusses managing credit and debt collection for businesses. It covers setting appropriate payment terms, analyzing credit risk, making credit decisions, and collection policies. Statistical techniques like credit scoring and multiple discriminant analysis can help determine customer credit risk. The key considerations for businesses include balancing increased sales from offering credit with costs of potential bad debts and reduced cash flow. Factoring is also presented as an option to speed up cash flow from sales.

1. Managing debtors
One of the key advantages of offering credit to
customers is an increase in sales.
Credit is often used as a competitive marketing
device to attract new customers.
Against the increased sales must be set the cost
of offering credit:-
• Increased investment in debtors and reduced
cash-flow to the firm.
• Increase in bad debt losses.

2. Managing debtors
The main issues which have to be considered
by a firm in setting credit policy are:
• Establish payment terms
• analyze credit risk
• Decide when and whom to offer credit
• How to collect the debt

3. Payment terms
Payment term refers to when customers have to pay
the invoice and what discounts are available for
prompt payment.
Payment terms can include:-
• cash term
• Credit term
Cash terms
This offers the greatest protection to the seller.
The buyers pays either in advance (CASH IN
ADVANCE) or upon taking delivery of the goods
(CASH ON DELIVERY).

4. Payment terms
Credit terms
The seller delivers the goods and the buyer pays later,
but the buyers does not sign a formal debt contract.
Credit terms (i.e. credit period and the cash discount for
prompt payment) are usually stated on the invoice.
3/15 net 45 implies 3% discount if payment is within 15
days otherwise full payment required within 45 days.
The implicit interest rate in the above credit term is
about 45%. A buyer should forego the discount only if
alternative finance cannot be obtained.

5. Setting credit terms
If a buyer is willing to borrow at this rate, then it is
highly likely that they are desperate for cash.
The interest rate implicit in the credit term is found
from the following formula:-
365
Interest rate = [ 1 + D ] N -1
100 – D
D is the cash discount percentage and N is the
number of days that payment can be delayed by
foregoing the discount.

6. Setting credit terms: Example
Credit terms usually follow industry norms however a firm can
vary its credit terms to suit its purpose. In setting credit terms,
you have to balance the trade off between increase in sales,
reduced cash flow and the cost of the discount.
Example
Mistral Plc currently offers credit terms to its customers of 2/10
net 30, but is thinking of changing the policy to 1/15 net 45.
Average collection period is expected to increase from 10 days
to 40 days. Credit sales are expected to rise from £ 10 to 15m
per annum. The firm estimates that the percentage of
customers taking advantage of the discount will drop from 80
% to 20%. The company makes a profit margin on cost of 5%. If
a return of 20% is required on investment in debtors should it
switch policy?

7. Setting credit terms: Example
Current average debtor balance 10,000,000 * 10 = 273,973
365
Net average debtor balance 15,000,000 * 40 = 1,643,836
365
Interest cost of increase in debtors 20% * ( 1%*1,643,836 – 273,973) =
(273,973)
Present cost pf cash discount 80% * (2% * 10,000,000) = 160,000
Net cost of cash discount 20% * (1% * 15,000,000) = 30,000
Saving on cash discount 160,000 – 30,000 = 130,000
Profit from increased sales 5 *(15,000,000 – 10,000,000)
105
= 238,095
Net change in profit = 94,122

8. Managing credit risk
In order to decide whether to grant credit the company
must evaluate the risk of default by classifying
customers into good and bad risk.
There are two types of errors involved:-
Type I error implies classifying a good buyer as a bad
risk
Type II error implies classifying a bad customer as a
good risk.

9. Managing credit risk
Determining a particular customer’s credit risk is not
easy, however useful information sources include:-
bank references
References from existing suppliers
Trade association reports
Credit rating agencies (e.g. Dun & Bradstreet)
Published accounts
Salespeople’s reports
Company’s own sales ledger
Direct interview
In the US the exercise is more scientific because of the
provisions of the every lender take same decision
under same facts.

10. Statistical techniques for determining
credit risk
The main scientific techniques include:-
Credit scoring:- a numerical index of various
measures used to predict the probability that the
buyer will default. Usually information provided
by the credit applicant in a questionnaire is used
to calculate the credit score.
Multiple discount Analysis (MDA):- this uses
statistical techniques to develop a model which
assigns weights to difference factors so that the
model discriminates between good and bad credit
risk.

11. Statistical techniques for determining
credit risk
MDA was first used in the prediction of
corporate bankruptcy (Altman, 1968).
The composite index developed in
bankruptcy prediction is called a Z score.
The main UK work on Z-scores in Taffler
(1963).
Most Z score models are proprietary and only
available commercially.

12. Making the credit decision
This implies deciding the point on your credit
risk index below which a customer is refused
credit.
Grant credit if the expected profit from granting
credit is greater than the expected loss from
refusing credit.
Since the granting of credit is equivalent to
making an investment in debtors, the firm
should grant credit so long as the NPV of the
credit decision is greater than zero.

13. Making the credit decision
Customer pays _______ PV Revenue – cost
Probability (P)
Offer
Credit
Credit
Decision Customer default
Probability (1-P) --- - PV cost
NPV of offering credit
Refuse 0
Credit
P * PV Rev – PV Cost – ( 1 – P) * PV Cost > 0

14. Making credit decision: Example
Vents Ltd sells on credit with average collection
period of 45 days
The selling price of each item is $500 with a
profit margin on cost of 10%
If the company required return on debtors is
15% per annum, what probability of collection
is required for the company to extend credit
to a customer

15. Making credit decision: Example
Interest rate for 45 days 15 % * 45 = 1.85 %
365
Present value of a credit sale 500 = 491
(1 + 1.85%)
Present value of cost 455 = 447
(1 + 1.85%)
The expected profit from offering credit is set equal to zero
when
P * (491 – 447) = (1 – P) * 447
P = 91.04% Offer credit if the probability of collection
of greater than 91.04%.

16. Incentive problems in making credit
decisions
There are potentially some incentive problems in
making credit decisions.
If sales managers are judged solely on the basis of
sales targets, then they are more willing to grant
credit in order to increase sales, irrespective of the
bad debt losses incurred or the resources tied up in
debtors.
A possible approach is to base compensation for sales
people on the profitability of credit sales, including
the cost of funds tied up in debtors.

17. Collection policy
Collecting debts can be arduous.
Once an account is overdue the seller has two
choices:-
• Collect the debt yourself. Send statements, write
insistent letters and make phone calls.
• Hire a professional debt collector or lawyer. They
are expensive and can cost between 15% and 40%
of the amount collected.
• Factoring.
• Another way of spending up cash-flow from sales is
factoring.
• A factor buys a company’s debt on a non-recourse
basis.

18. Factoring
The factor pays the seller based on the agreed average
collection period irrespective of when the buyer paid the
debt. This is called maturity factoring.
For this service the factor can charge fees of about 1% to 2% of
the invoice value.
The advantages of factoring include:-
• The seller is guaranteed payment on time.
• The seller does not risk the business relationship with the
buyer, by chasing the buyer for the debt. Let the factor be
the bad guy.
• The factor guarantees implicit claims made by the seller