WCM
Receivables Management
and Factoring
Saturday, March 12,
2016
1
Topics
• Nature and Goals of Credit
Policy
• Optimum Credit Policy
• Credit Policy Variables
• Credit Evaluation of Individual
Accounts
• Monitoring Receivable
Saturday, March 12,
2016
2
Nature of Credit Policy
• Investment in receivable
depends on:
– volume of credit sales
– collection period
These two depend on the credit policy
• Credit policy:
three decision variables
– credit standards- type of customer
– credit terms-duration of credit
– collection efforts-actual collection period
Saturday, March 12,
2016
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Goals of Credit Policy
• Marketing tool for sales expansion:
- competition
- company’s bargaining power
- industry practice
• Maximisation of sales Vs. incremental profit
– production and selling costs (FC increases, if capacity is
added)- with loosening of CP, opportunity cost of lost
sales comes down, but cost of admin. and bad debt loss
increases- Trade off
– administration costs (supervision & collection cost rise)
– bad-debt losses
Saturday, March 12,
2016
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Cont…
Change in sales
Change in cost
Change in contribution
Loose credit policy:
Increases contribution (reduces
opportunity loss)
Admin cost [credit investigation and
supervision cost & collection costs] rise
Bad debt loss rises
Saturday, March 12,
2016
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Costs of credit policy
Cost of admin &
Bad debt losses
Costs &
Benefits
Opportunity loss
Tight
Saturday, March 12,
2016
Credit policy
Loose
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Optimum Credit Policy
• Estimation of incremental
operating profit IOP
• Estimation of incremental
investment (II)in
receivable
• Estimation of incremental
rate of return (IRR)IOP/ II
• Comparison of incremental rate of return
with required rate of
return (RRR)
• Optimum credit policy:
IRR = RRR
Saturday, March 12,
2016
Costs & Return (%)
Marginal cost of capital
Marginal rate of return
Tight
Credit
policy
Loose
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Incremental cost-benefit analysis
Change in cont. (lost cont. due to tightening of CP) =
change in sales X PV ratio
Change in OP= change in cont- avoidable cost of bad
debt and admin. cost associated with a loose policy
Investment in debtors = credit sales per day X
average collection period
Find the incremental rate of return: Change in OP(1tax rate) / Investment in debtors
Sheet-2
Saturday, March 12,
2016
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Credit Policy Variables
• Credit standards-
criteria for choosing
customer- trade off between incremental return and
cost
• Credit analysis
– collection period
– default rate : bad debt loss %
• Character- willingness to pay
• Capacity-ability to pay
• Condition-economy’s impact on ability to
pay
• collateral
Saturday, March 12,
2016
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Cont……..
– customer categories
• good accounts
• bad accounts
• marginal accounts (in between good and
bad)
– Creditworthiness-numerical
credit scoring
• ad hoc approach (scoring on a scale of
factors with due weightage)
• simple discriminant approach
• multiple discriminant approach
Saturday, March 12,
2016
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Multiple-discriminant
analysis
Altman:
Z = 0.012 (NWC/TA) + 0.014(RE/TA)
+ 0.033(EBIT/S) + 0.006 (MV/D) +
0.010(S/TA)
Z > 2.675
MV=Book value of equity
D=Book value of debt
Saturday, March 12,
2016
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Credit Policy Variables
Credit-Granting Decision
CREDIT GRANTING
DECISION
GRANT CREDIT
NO CREDIT
PAYMENT
RECEIVED
BENEFIT
PV OF FUTURE
NET CASH
FLOWS
PAYMENT
NOT RECEIVED
COST
PV OF LOST
INVESTMENT
NO PAYOFF
NET PAYOFF
PV OF
(BENEFIT - COST)
Credit-granting Decision
Saturday, March 12,
2016
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Credit Policy Variables
• Credit terms
– credit period
– cash discount (compare after tax cost of
discount with opportunity of reduced
investment in debtors)
• Collection policy and procedures
– regularity of collections
– clarity of collection procedures
– responsibility for collection and follow-up
– case-by-case approach
– cash discount for prompt payment
Saturday, March 12,
2016
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Credit Evaluation of
Customers
• Credit information
– financial statements
– bank references
– trade references
• Credit investigation and analysis
– analysis of credit file
– financial analysis
– analysis of business and management
• Credit limit
• Collection efforts
Saturday, March 12,
2016
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Monitoring Receivable
• Collection period
• Aging schedule
• Collection experience matrix
Saturday, March 12,
2016
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Collection experience matrix
Sales and receivables
Month
Sales
Receivables
July
Aug
Sept
Oct
Nov
Dec
Saturday, March 12,
2016
Rs. In lacs
July Aug Sept. Oct. Nov Dec.
400 410 370 220 205 350
330
242 320
80
245 320
0
76 210 162
0
0
72
120 160
0
0
0
40 130 285
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Cont….
Month
Sales
Receivables %
July
Aug
Sept
Oct
Nov
Dec
July
400
82.5
60.5
20.0
0
0
0
Aug Sept. Oct.
410 370 220
Rs. in lacs
Nov Dec.
205 350
78.0
59.8 86.5
18.5 56.8 73.6
0
19.5 54.5
0
0
18.2
78.0
63.0 81.4
Moving down the diagonals tells the collection experience
Saturday, March 12,
2016
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