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Management of Inventory
UNIT 5 MANAGEMENT OF RECEIVABLES
Objectives

The objectives of this unit are to:

• Highlight the need for offering credit in the operation of business enterprises.
• Discuss and design various elements of credit policy.
• Analyse the impact of changes in the terms of credit policy.
• Discuss different credit evaluation models in evaluating the credit worthiness
of customers.
• Discuss various techniques available in monitoring receivables in order to
speed up the collection process.
• Explain options available before the credit managers in dealing with delinquent
customers.
• Analyse the strategic importance of receivables management in designing
business strategies.

Structure
5.1 Introduction
5.2 Credit Policy
5.3 Credit Evaluation Models
5.4 Monitoring Receivables
5.5 Collecting Receivables
5.6 Strategic Issues in Receivables Management
5.7 Summary
5.8 Key Words
5.9 Self Assessment Questions
5.10 Further Readings

5.1 INTRODUCTION
“Buy now, pay later” philosophy is increasingly gaining importance in the way
of living of the Indian Families. In other words, consumer credit has become a
major selling factor. When consumers expect credit, business units in turn expect
credit form their suppliers to match their investment in credit extended to
consumers. If you ask a practising manager why her/his firm offers credit for the
purchases, the manager is likely to be perplexed. The use of credit in the
purchase of goods and services is so common that it is taken for granted. The
granting of credit from one business firm to another, for purchase of goods and
services popularly known as trade credit, has been part of the business scene for
several years. Trade credit provided the major means of obtaining debt financing
by businesses before the existence of banks. Though commercial banks provide a
significant part of requirements for working capital, trade credit continues to be a
major source of funds for firms and accounts receivables that result from
granting trade credit are major investment for the firm. The importance of
accounts receivables can be seen from Table 5.1, which presents investments in
accounts receivables for different industries over the years. This is expected to
provide an idea of the size of investment in receivables in the Indian Industry.

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Management of Current Table 5.1 : Industry-wise Investments in Trade Credit Receivables

Assets Rupees in Crores

Industry 1999 2000 2001 2002 2003

Chemicals 3502.22 3561.63 3412.65 3768.37 3614.45

Food & beverages 7171.87 7195.32 7369.03 7172.42 6046.75

Machinery 21101.05 27928.26 28818.50 28980.45 28796.07

Metals & metal products 3513.62 3885.98 4252.64 4606.84 3907.31

Non-metallic mineral products 12944.11 13147.85 13456.84 12196.30 11923.14

Textiles 21912.86 24989.77 28720.10 29095.38 28889.75

Transport equipment 7003.26 7304.55 7652.69 7622.18 7199.14

Diversified 5888.22 6631.51 6945.93 8620.85 8891.48

Miscellaneous manufacturing 2146.93 2478.04 2751.78 2953.06 2745.85

All Manufacturing 85184.14 97122.91 103380.16 105015.85 102013.94

Two important conclusions emerge from the analysis of Table 5.1:

Investment in accounts receivable is high and shows a positive growth over
the years; and

Value of accounts receivable differs significantly between industries even
after adjusting the differences in number of companies between industries.
The investment in accounts receivable is an important aspect which requires
careful managment. Besides the cost of investment, there are two types of risks
which are associated with the accounts receivable management. One is the risk
of OPPORTUNITY LOSS and the other LIQUIDITY risk. The firm has to
extend credit to its customers to generate enough sales. The grant of credit is an
important tool to realize the operating plans and budgets of the company. But at
the same time management has to see that the company has not extended too
much of credit to its customers which has resulted in high degree of liquidity risk.
By liquidity risk we mean the ability to collect back the amounts due from the
customers. This would happen if the company extends the credit to customers
whose financial position is doubtful or week and subsequently the funds tied up
with them are recovered after a long period or they are not at all realised. If this
happens it would result in the companies ability to meet its own obligations and
thus affecting short term and long term solvency of the company. The decision to
extend the credit to its customers also determines the timing and amount of cash
flows accruing to the company.

At the same time minimisation of liquidity risk would imply the risk of opportunity
loss. The opportunity loss here means loss of sales by refusing the credits to its
potential customers. This would further affect the loss of revenue and the loss of
profits. Thus the objective of accounts receivable management is to arrive at an
optimum balance of these two risks and help the company to realize its operating
plans. This balancing is not a static but a dynamic one. To arrive at the balancing
of these two risk, the company would frequently require to adjust their credit
standards, credit terms and credit policies. Management of the company would
also be required to consider general economic conditions while making such
adjustments.

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Management of Inventory

While high investments in accounts receivable warrant efficient management,

significant differences between industries call for proper structuring of credit
policy that match the industry norms. These two are essential issues in
management of receivables. The receivables management system thus involves
the following:

Terms of credit

Assessing customers’ credit worthiness to grant credit

Monitoring the level of accounts receivables and improving collection efficiency.
Setting of terms of credit is first step in the receivables management. It is a
corporate policy and thus has a close interrelationship with other corporate
policies. For example, if a company pursues a policy of market leadership, then it
requires aggressive credit policy to achieve maximum sales volume. Terms of
credit requires management to decide period of credit, a broad guideline on the
eligibility of credit, credit limit for different customers and discount rate offered to
customers who settles the bill within a predetermined period. Credit policy is
determined by trading off risk associated with granting credit and additional
revenue available from granting credit. The credit policy once determined is fixed
in the short-run and may warrant periodic adjustment depending on the changes
in environment and corporate policies.

Determining creditworthiness of customers, first, requires a system to collect

basic information about the customers and then fit the data into a Model that
determines the suitability of the customer in granting credit and other credit
terms. Once credit is granted, the focus is shifted to collection of dues in time.
The efficiency of receivables management is measured by comparing the extent
to which collection flows are in line with credit terms.

The objectives that drive the above issues of receivables management are:
1) Obtain maximum (optimum) volume of sales.
2) Maintain proper control over the quantum or amount of investment in debtors.
3) Exercise control over the cost of credit and collections.
Activity 5.1

1) Why companies sell/provide goods/services on credit basis?

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2) How does the decision on granting credits affect the finance of the company?

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Management of Current …………………………………………………………………………………….

Assets

5.2 CREDIT POLICY

Designing credit policy is the first step in receivables management. In designing
credit policy, the management can follow two broad approaches. Firstly, the
policy can be designed under the assumption of unlimited production/sales and
funds available for investment in receivables. If credit policy is designed under
this assumption and subsequently some constraints are experienced on sales or
funds available for receivables, then managers have to restrict the credit at the
time of implementing the credit policy. But this may cause certain difficulties to
customers because of deviation from the announced credit policy. For example, if
a company announces that credit will be unlimited to certain categories of
customers based on unlimited funds assumption and subsequently refuse to grant
credit due to limited funds available for investment in receivables, it will create
hardship to the customer. Under the second approach, the credit policy could be
designed keeping in mind the limitations on production/sales volume and funds
available for investment in receivables. This is aimed to achieve optimum
utilisation of production capacity and funds available for receivables. It also
ensures consistency of credit policy.
The credit policy consists of the following components:
• Credit Period
• Discount
• Credit Eligibility
• Credit Limit
a) Credit Period

Decision on credit period is determined by several factors. It is important to

check the credit period given by other firms in the industry. It would be difficult
to sustain by adopting a completely different credit policy as compared to that of
industry. For example, if the industry practice is 30 days of credit period, a firm
which offers 120 days credit would certainly attract more business but the cost
associated with managing longer credit period also increases simultaneously. On
the other hand, if the firm reduces the credit period to 10 days, it would certainly
reduce the cost of carrying receivables but volume would also decline because
many customers would prefer other firms, which offer 30 days credit. In other
words, granting trade credit is an aspect of price.

The time that the buyer gets before payment is due, is one of the dimensions of
the product (like quality, service, etc.) which determine the attractiveness of the
product. Like other aspects of price, the firm’s terms of credit affect its volume.
All other things being equal, longer credit period and more liberal credit-granting
policies increase sales, while shorter credit period and more stringent credit-
granting policies decrease sales. These policies also affect the level and timing
of certain costs. Evaluation of credit policy changes must compare with the
changes in sales and additional revenues generated by the sales as a result of
this policy change and costs effects. While additional volume and revenue
associated with such additional volume are clear and measurable, the cost effects
require further analysis.

Cost of Extending Credit Period

Lengthening credit period delays the cash inflows. For example, suppose a firm
increases the credit period from 30 days to 90 days. Customers, old as well as
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new, will now pay at the end of 90 days and the cash inflows from these sales Management of Inventory
would occur further into the future. That means, the firm has to delay in settling
its dues to others or resort to short-term borrowing if the payments cannot be
delayed. The interest cost of short-term borrowing arises mainly on account of
extending the credit period.

Example 5.1

Flysafe Travels is one of the large air-ticket sellers in the city. It offers one-
month credit for the air-tickets booked through the firm. Since it also gets one-
month credit from the air-lines, the payables and receivables are by and large
matched and there is no need of additional investment. The present annual
turnover of the firm is around Rs.40 crores. The firm is now contemplating to
increase the credit period from one-month to two-months and this is expected to
increase the volume by 40% and nearly 80% of the customers (old and new) are
expected to avail the new credit facility. The firm has just concluded a credit
proposal with a nationalised bank to meet payment liability at 15%. How much
more it costs for Flysafe Travels to meet the increased credit volume.
Revised Sales Rs. 40 cr. × 1.40 = Rs. 56.00 cr.
Customers, who are expected to use additional
credit period = 80%
Sales which are likely to be collected at the end of
second month = Rs. 56 x 0.80 = 44.80 cr.
Total Credit Period = 2 months
Less: Credit given by Air-line operators = 1 month
Funds required for additional credit period of 1 month
Interest cost per year = 15%
Additional interest cost to sustain 1 month credit = Rs. 44.80 x 15%
= Rs. 6.72 cr.
The cost of Rs. 6.72 cr. is compared with the additional profit generated by the
new sales to decide whether it is desirable to increase the credit period or not.

Changes in credit period also affect the cost of carrying inventory. This arises
mainly on account of increased volume attracted by the extended credit period,
which in turn requires more inventory to support increased volume. For example,
if expected additional sales is Rs. 5 cr. and the firm’s present operating cycle
requires an inventory at 20% of its sales value, the additional inventory
requirement is Rs. 1 cr. Again, inventory is a idle investment and consumes cost
in the form of cost of storage and cost of carrying inventory. If the two costs
together amount to 17%, the changes in credit policy has caused an additional
cost of Rs. 17 lakhs.

Another cost associated with extending credit term and increase in sales volume
on account of extended credit term is discount and bad debts expenses.
Increase in credit sales and period would prompt firms to announce attractive
discount policy for prompt payment. Similarly, bad debts will also go up due to
increased volume of credit sales.

The cost of collection also goes up when the credit period is increased and
more credit volume is done. The cost of collection includes cost of maintaining
records of credit sales, telephone calls, letters, personal visits to customers, etc.
These costs tend to show an uptrend with increased volume and credit sales.

Example 5.2
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Management of Current Suppose the cost of collection for the Flysafe Travels is 1% and bad debts are
Assets
likely to increase from 0.50% to 0.75% due to increased credit period. These
costs are to be added along with interest cost on additional investments in
receivables arising out of changes in credit period. These two costs are
computed as follows:

Cost of Collection
Case Sales (Rs.) Cost of Collection (Rs.)
Present 56.00 cr. 0.56 cr.
Previous 40.00 cr. 0.40 cr.
Difference 16.00 cr. 0.16 cr.

Cost of Bad Debts

If we follow the methodology adopted earlier in computing cost of collection, then
the additional bad debts works out to Rs. 0.22 cr. (i.e., 0.75% of Rs. 56 cr. less
0.50% of Rs. 40 cr.). However, the entire value of additional bad debts is not
on account of change in credit period. A part of it is on account of increase in
sales. The actual impact of increase in bad debts can be computed in two stages
as follows:
Increased cost of bad debts for existing sales of Rs. 40 cr.
Bad debts as per revised percentage of bad debts, 0.75% of Rs. 40 cr.= 0.30 cr.
Bad debts as per earlier percentage of bad debts, 0.50% of Rs. 40 cr. = 0.20 cr.
Increased value of bad debts attributable to new credit policy = 0.10 cr.
Increased cost of bad debts for additional sales of Rs. 16 cr.
Bad debts as per revised percentage of bad debts, 0.75% of Rs. 16 cr.= 0.12 cr.
Bad debts as per existing percentage of bad debts, 0.50% of Rs. 16 cr.= 0.08 cr.
Increased value of bad debts attributable to new credit policy = 0.04 cr.
Total value of bad debts attributable to new credit policy (0.10+0.04) = Rs. 0.14 cr.
The balance of Rs.0.08 cr. is on account of increase in sales.
b) Discount
When a firm pursues aggressive credit policy, it affects cash flows in the form of
delayed collection and bad debts. Discounts are offered to the customers, who
purchased the goods on credit, as an incentive to give up the credit period and
pay much earlier. For example, suppose the terms of credit is “3/10 net 60”. It
means if the customer, who gets 60 days credit period can pay within 10 days
from the date of purchase and get a discount of 3% on the value of order.
Since the customer uses the opportunity cost of funds and availability of cash in
taking decision, the cash discount should be set attractive. The discount quantum
should be greater than interest rate of short-term borrowings.
Example 5.3

Excel Industries is presently offering a credit period of 60 days to some of their

customers. It now intends to introduce a discount policy of “3/10 net 60”. We
will now see how a customer would evaluate the discount policy here. If a
customer bought goods worth of Rs. 1 lakh, the amount due at the end of 60
days is Rs. 1 lakh and if he pays within 10 days, it costs Rs. 97,000. The customer
evaluates the interest cost of Rs.97,000 for 50 days to take a decision on availing
the discount and advancing the payment. Suppose the interest cost is 15%, then
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cost of interest for 50 days on Rs.97,000 is Rs. 97,000 x 0.15 x (50/365), which Management of Inventory
works out to Rs. 1,993.15. Since the discount value is greater than the cost, it is
profitable for the customer to pay the money earlier within 10 days and avail the
discount. In other words, if the customer borrows money for 50 days at 15%
interest cost in the short-term market or bank and uses the money to settle the
account within 10 days, the loan amount due at the end of two months is Rs.
98,993.15, which is lower than Rs. 1,00,000 due at the end of the period in the
normal course. If the cost of borrowing is 24%, the customer would take a
different decision. The interest cost of borrowing for 50 days in this case is
Rs.3189, which is greater than the discount benefit. Of course, the customer will
look into the availability of funds and other options available to the firm before
deciding whether to accept the offer or not.

How do we evaluate the discount terms of the company? Cost of funds is an

important factor but it is not the only factor in evaluating the discount term. For
instance, if the cost of borrowing is 15% of this firm also, then the discount
value of Rs. 3000 is to be compared to the interest cost of Rs.97000 at 15% for
50 days, which works out to Rs.1993.15. In other words, if the company is in a
position to raise a loan of Rs. 97,000 for 50 days at 15% cost, there is no need
to raise Rs. 97000 in the form of offering discount to the customers, where the
cost of offering discount works out to Rs.3000. But, there are other issues in
deciding the discount policy. Cash discount reduces the probabilities of delayed
collection as well as bad debts. In the above example, we have assumed that the
customer, who has not availed the discount, promptly pays up the dues at the end
of 50 days. The interest cost of Rs.1993.15 will undergo a change if the
customer fails to pay at the end of 50 days. Further, the value of bad debts will
go up if more credit sales are made and period of credit increases.

Example 5.4

Royal Textiles is contemplating to increase the credit period from 30 days to 60

days. This is expected to increase the sales from Rs. 20 cr. to Rs. 23 cr. but
the bad debts is also expected to go up from 0.5% on sales to 1% on sales.
Marketing Director felt that by giving 3% discount for payment within 10 days
would prompt several customers to avail the facility and thus would bring back
the bad debts value to 0.5% on sales. The interest cost of short-term borrowing
is 15% and nearly 40% worth of sales are expected to be collected at the end
of 10 days. Is it desirable to introduce the discount policy?

As far as interest cost component is concerned, our earlier working on Excel

Industries shows the interest cost of 15% is higher than the discount value of
3%. We will work out the interest cost and discount value again. The 40% sales,
which is expected to be collected at the end of 10 days works out to Rs. 9.20
cr. (23 x 0.4). The discount to be given on this value at 3% is Rs.0.276 cr. or
Rs. 27,60,000 (i.e. 9.2 x 0.03). The net collection is Rs. 8.924 cr. (i.e. 9.2 -
0.276). If the company is in a position to borrow this money at 15%, the
interest cost for 50 days would be Rs. 18,33,700 (i.e. 8.924 x .15 x (50/365).
Since the discount value is greater than cost of borrowing, 3% discount is not
economical if interest cost alone is considered. However, it is not correct to
ignore the impact of discount policy on bad debts.

The discount policy will bring down the value of bad debts from 1% to 0.50%.
The savings in terms of values is Rs. 11,50,000 i.e. 23,00,00,000 x (1% - 0.50%).
If this saving is deducted from the discount value of Rs. 27,60,000, the net
discount cost is Rs. 16,10,000. When the net discount cost of Rs. 16,10,000 is
compared with the interest cost of Rs. 18,33,700, then offering 3% discount for
payment within 10 days is economical. (However, before implementing this new
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Management of Current credit policy, the overall impact of the policy on profit is to be assessed and this
Assets
will be discussed later).

The above analysis also highlights the factors that are involved in evaluating the
discount policy. The discount policy is judged on the basis of discount percent
(3%), discount period (10 days), percentage of customers expected to avail the
discount term (40%), and interest cost (15%). For example, if 80% of the
customers are likely to avail this facility, then the discount value and interest cost
will double to Rs. 55,20,000 and Rs. 36,67,400 respectively. If there is no
change in reduction of bad debts value, then the cost (Rs.55.20 - 11.50 lakhs)
exceeds benefit (Rs.36.674 lakhs) and thus, the discount policy is uneconomical.
To make the policy economical, the company has to reduce the discount rate
from 3% to lower level, which will cut down the discount cost as well as
percentage of customers using the discount offer.

Example 5.5: Cost-Benefit Analysis

American Pharama is a multinational pharmaceutical company selling certain

premium tablets in the domestic market for the last three years. The company
has not offered any credit on sales and the annual turnover for the year was Rs.
10 cr. Due to increased competition, the company is now evaluating new credit
policy, which it intends to introduce. As per the policy, the company will offer 30
days credit and a discount of 2% if the amount is paid within a day (i.e., 2/1 net
30). Without this new credit policy, the sales are expected to increase to Rs. 12
crore and with the new policy, the sales will be Rs. 15 cr. It is estimated that
40% of the customers would avail the discount. The contribution margin for its
sales is 30% and the company is operating above break-even point. The new
credit policy will cause additional costs in terms of collection charges at 1% and
bad debts at 0.5%. The interest cost is 16%. Evaluate the credit policy and its
implication on profit.
Increase in sales on account of credit policy (Rs.15 cr. less Rs. 12 cr.): Rs. 3.00 cr.
Contribution from increased sales (30% on Rs. 3 cr.) : Rs. 0.90 cr.
Cost associated with credit policy
1. Collection charges @ 1% on Rs. 15 cr. Rs. 0.150 cr.
2. Bad debts at 0.5% on Rs. 15 cr. Rs. 0.075 cr.
3. Discount at 2% on 40% of Rs. 15 cr. Rs. 0.120 cr.
4. Interest cost on receivables @ 16%
Sales not likely to take discount: Rs. 9 cr.
Investments on 30 days receivable
Rs. 9 cr. x (30/365) = Rs. 0.74 cr.
Interest on Rs. 0.74 cr. at 16% Rs. 0.118 cr. Rs. 0.463 cr.
Net benefit before tax
Rs. 0.437 cr.
c) Credit Eligibility

Having designed credit period and discount rate, the next logical step is to define
the customers, who are eligible for the credit terms. The credit-granting decision
is critical for the seller since credit-granting has economic value to buyers and
buyers decision on purchase is directly affected by this policy. For instance, if the
credit eligibility terms reject a particular customer and requires the customer to
make cash purchase, the customer may not buy the product from the company
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and may look forward to someone who is agreeable to grant credit. Nevertheless, Management of Inventory
it may not be desirable to grant credit to all customers. It may instead analyse
each potential buyer before deciding whether to grant credit or not based on the
attributes of that particular buyer. While the earlier two terms of credit policy
viz. credit period and discount rate are not changed frequently in order to
maintain consistency in the policy, credit eligibility is periodically reviewed. For
instance, an entry of new customer would warrant a review of credit eligibility of
existing customers.

The decision whether a particular customer is eligible for credit terms generally
involves a detailed analysis of some of the attributes of the customer. Credit
analysts normally group the attributes in order to assess the credit worthiness of
customers. One traditional way of organising the information is by characterising
the applicant along five dimensions namely, Capital, Character, Collateral, Capacity
and Conditions. These five dimensions are also popularly called Five Cs of credit
analysis.

Capital: The term capital here refers to financial position of the applicant firm.
It requires an analysis of financial strength and weakness of the firm in relation
to other firms in the industry to assess the credit worthiness of the firm.
Financial information is normally derived from the financial statements of the firm
and analysed through ratio analysis. The liquidity ratios like current ratio, debt-
service coverage ratio, etc. are often used to get a preliminary idea on the
financial strength of the firm. Further analysis includes trend analysis and
comparison with the other industry norm or other firms in the industry.

Character: A prospective customer may have high liquidity but delay payment to
their suppliers. The character thus relates to willingness to pay the debts.
Some relevant questions relating to character are:
• What is the applicant’s history of payments to the trade?
• Has the firm defaulted to other trade suppliers?
• Does the applicant’s management make a good-faith effort to honour
debts as they become due?
Information on these areas are useful to assess the applicant’s character.
Collateral: If a debt is supported by collateral, then the debt enjoys lower risk
because in the event of default, the debt holder can liquidate the collateral to
recover the dues. The collateral causes hardship to other debt holders. Thus,
the analysts should look into both the availability of collateral for the debt and the
amount of collateral the firm has given to others. In computing the liquidity of
the firm, the analysts should remove the assets used for collateral and take into
account only the free assets. The credit worthiness improves if the customer is
willing to offer collateral assets or the value of collateral asset backed loan is
low.
Capacity: The capacity has two dimension - management’s capacity to run the
business and applicant firm’s plant capacity. The future of the firm depends on
the management’s ability to meet the challenges. Similarly, the facility should
exist to exploit the opportunity. Since the assessment of capacity is a
judgement on the part of analysts, a lot of care should be taken in assessing this
feature.
Conditions: These are the economic conditions in the applicant’s industry and in
the economy in general. Scope for failure and default is high when the industry
and economy are in contraction phase. Credit policy is required to be modified
when the conditions are not favourable. The policy changes include liberal
discount for payment within a stipulated period and imposing lower credit limit. 9
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Management of Current The information collected under five Cs can be analysed in general to decide
Assets
whether the customer is eligible for credit or fit into a statistical model to get an
unbiased credit rating of the customer. Discussion on credit evaluation model is
presented in the next section.
d) Credit Limit
If a customer falls within the desired limit of credit worthiness, the next issue is
fixing the credit amount. This is some thing similar to banks fixing overdraft limit
for the account holders. If a customer is new, normally the credit limit is fixed
at the lowest level initially and expanded over the period based on the
performance of the customer in meeting the liability. Credit limit may undergo a
change depending on the changes in the credit worthiness of the customer and
changes in the performance of customer’s industry.

Example 5.6

Alpha Electronics is presently grouping its customers into three categories. It

offers unlimited credit to first group, a maximum credit of Rs. 1 cr. to second
group and Rs. 5 lakhs for third group. It is presently doing a turnover of Rs. 50
cr. at 60% production capacity. One of the proposals received to increase the
capacity utilisation during the annual review meeting is increasing the credit limit
for second and third groups of customers. Instead of relaxing credit limit to all
groups, the Marketing Chief felt it is desirable to upgrade some of the customers
based on their past performance by relaxing the review procedure. The
Marketing Chief felt this will also give a right signal to their customers. After
completing the upgrading exercise, the marketing manager projected that the sales
will go up by another Rs. 10 cr. Based on the average collection period of 40
days, the Finance Manager estimated the revised investments in receivables at
Rs. 6.58 cr. against the earlier figure of Rs. 5.48 cr. The interest cost on short-
term borrowing is 14%. No major change is expected in collection and bad
debts values on account of this regrouping. The firm presently has a contribution
margin of 20% and operating above break-even level.

The additional contribution on account of increase in sales works out to Rs. 2 cr.
(20% of Rs. 10 cr.). The investment in receivables has gone up by Rs. 1.10 cr.
and it costs additional interest burden of Rs. 0.154 cr. per year. Since additional
contribution of Rs. 2 cr. is higher than the additional cost of Rs. 0.154 cr., the
revision is profitable to the firm.

There are several reasons for limiting the credit facility to the customers. Some
of the important reasons are:
• reduce the impact of deficiencies in credit-granting decision;
• reduce the scope for overbuying by the customers;
• rationally allocate the limited funds available for investment in bills
receivable; and
• mitigate agency problem
The last reason, mitigating agency problem, requires further discussion. Agency
problem arises on account of conflict of interest between the managers (agents)
and equity shareholders (owners or principal). Agents will always try to
maximise their return even if it is at the cost of principal. Two types of agency
problems arise in credit-granting decision. Firstly, managers may collude with
some of the customers and grant credit even to undesirable customers. Credit
limit puts a cap on the potential loss. Secondly, managers may hesitate to give
credit to even creditworthy customers when the performance of the managers is
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assessed on the basis of collection efficiency. Recently, many public sector
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banks were criticised for not granting fresh loan despite comfortable monetary Management of Inventory
position and funds are simply used to buy government securities. The fear of
default and delay in collection would prevent in granting credit even to good
customers and thus, take away the opportunity to maximise the profit. Credit
limit would to some extent take away this fear of managers since default is
restricted and thus would encourage them to accept credit proposals. The
situation will improve further if credit limits are built into the system of
performance evaluation and managers are not penalised as long as they have
restricted the credit.

Activity 5.2

1) What are the major components of credit policy?

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2) List out important factors that are used in assessing credit worthiness.

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…………………………………………………………………………………….

…………………………………………………………………………………….

…………………………………………………………………………………….

3) How do you evaluate alternative credit policies? Identify the principle to be

used in evaluating credit policies.

…………………………………………………………………………………….

…………………………………………………………………………………….

…………………………………………………………………………………….

…………………………………………………………………………………….

…………………………………………………………………………………….

5.3 CREDIT EVALUATION MODELS

In the previous section, how the credit analysts collect the information required
for processing credit application under five Cs was discussed. Credit
evaluation models are useful for the analysts to process the information to
decide credit worthiness of the customer. It is possible to structure credit
evaluation model in different ways. An experienced credit analyst can
evaluate the credit worthiness by simply scanning the information received or
collected for the credit proposal. When the credit transactions increase or
number of customer increases, it may be difficult to apply this methodology. It
11
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Management of Current will also cause delay in processing credit proposals and lead to inconsistent
Assets
decision. Thus, it is always useful to create a credit evaluation system and
standardise the appraisal. Decision-tree model and multivariate statistical model
are generally used to create credit evaluation system

Decision Tree Model: Under decision-tree model, credit applications are rated
under different parameters. For instance, if a company uses five Cs factors, the
analysts rate the credit applicant under each of the five Cs. Decision-tree is
initially created for all possible routes and decisions at the end of each route are
indicated. Figure 5.1 illustrates decision-tree model using three credit information
namely capital, character and collateral. If a character, capital and collateral are
strong, then the applicant firm is granted large amount of credit. On the other

Fig.5.1 : Decision Tree Credit Evalution Model

Should
Credit
be
granted?

Character

Strong Weak

Capital Capital

Strong Strong Weak

Weak

Collateral Collateral Collateral Collateral

Strong
Strong Strong/ Strong/ Weak
Weak Weak

Excellent Risk Fair Risk Dangerous

Fair Risk
Risk

Large Credit Limited Credit Limited to No Credit

Limit Collateral Limit

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hand, if the first two are strong but the collateral is weak, a limited credit could Management of Inventory
be granted.

If character is weak but capital and collateral are strong, then credit is limited to
collateral value. On the other hand, if all the three are weak, it is a dangerous
credit proposal and hence to be rejected. In Figure 5.1, we have taken two
broad ratings, which can be further divided into three or five scale rating.
Increasing the credit variable and rating scale will lead to more branches and
credit limit can be prescribed for each branch separately.

It is also possible to use the above decision-tree to decide whether a detailed

credit evaluation has to be conducted. For example, if character, capacity and
conditions are good but capacity and collateral are weak, it may require a
detailed credit evaluation. That means, the information collected is inadequate and
a rigorous analysis is required.

Multivariate Statistical Model: Many firms have started using sophisticated

statistical techniques in conducting their credit analysis. Multiple Discriminant
Analysis (MDA) employs a series of variables to categorise people or objects
into two or more distinct groups. A credit scoring system utilises multiple
discriminant analysis to categorise potential credit customers into two groups:
good credit risk and bad credit risk. An important advantage of credit scoring
system is that all of the variables are considered simultaneously, rather than
individually as in the decision tree analysis. The model is capable of handling both
numerical measures such as debt-equity ratio, current ratio, profit margin, etc., as
well as non-numerical measures like character of the customer as good, bad,
average. When a credit scoring model is constructed with historical data of a
few customers, the model would produce a equation as given below:
MDA Score Y = b1X1 + b2X2 + b3X3 + ……. + bnXn
where, b1, b2, b3,.. bn are co-efficient values of variables X1, X2, X3 … Xn.
X1, X2, etc. are variables such as debt-equity, current ratio, etc.

The model produces the coefficient values and when a new application is
received for credit scoring, the values of Xs are to be measured and substituted
in the model equation to get the discriminant score. The discriminant is then
compared with the point of separation to place the applicant in one of the two
groups. For example, if the point of separation is 3.80, when the applicant’s
score is above 3.80, then the applicant is placed in fair or excellent risk group. If
the score is below 3.80, then it is risky proposal. Thus, it is possible to evaluate
where a particular customer stands in terms of credit worthiness. No difficulty is
felt when the scores are much above or below the separation point but credit
worthiness of customers, whose scores are close to separation point, are difficult
to assess. In such cases, further analysis is made to understand the credit
worthiness of the customers. It is also possible to outsource credit rating
evaluation from specialised credit rating agencies.

Credit scoring models are periodically updated to take into account changes in the
environment and also reassess the credit worthiness of the customers. An outdated
model may wrongly classify the customers and lead to heavy losses. Further, while
developing the system, it is necessary to ensure good sample for developing the
model. It is equally important that the model is validated before employing it. Many
foreign banks and credit card agencies extensively use credit rating schemes and
found them useful in taking credit decision.

Rating Methodologies of Credit Rating Institutions

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Management of Current Credit rating has become one of the professionalised services in the recent past.
Assets
Though rating is more common with different securities offered by industrial units,
there is also focus on the rating of individuals and institutions as credit applicants.
For instance, CRISIL's rating methodology includes the following key factors for
deciding the credit worthiness of a borrowing company.
A. Business Analysis
• Industry Risk (nature and basis of competition, key sucess factors, demand
supply position, structure of industry, cyclical/seasonal factors. Goverment
policies etc.)
• Market position of the company within the industry (market share, competitive
advantages, selling and distrbution arrangements product and customer
diversity, etc.).
• Operating efficiency of the company (locational advantages, labour
relationships, cost structure, technological advantages and manufacturing
efficiency as compared to those of competitors etc.)
• Legal position (terms of prospectus, trustees and their responsiblities: systems
for timely payment and for protection against forgery/fraud; etc.)
B . Financial Analysis
• Accounting quality (overstatement/understatement of profits; auditors
qualifications; method of income recognition; inventory valuation and
depreciation policies; off balance sheet liabilities; etc.)
• Earnings protection (sources of future earnings growth; profitability ratios;
earnings in relation to fixed income charges; etc.)
• Adequacy of cash flows (in relation to debt and fixed and working capital
needs; sustainability of cash flow; capital spending flexibility; working capital
managment etc.)
• Financial flexibility (alternative financing plans in times of stress; ability to
raise funds; asset redeployment potential; etc.)
C. Management Evaluation
• Track record of the management; planning and control systems; depth of
managerial talent; succession plans.
• Evaluation of capacity to overcome adverse situations
• Goals, philosophy and strategies
The above factors are considered for companies with manufacturing activities.
The assessment of finance companies lays emphasis on the following factors
in addition to the financial analysis and management evaluation as outlined
above.
D. Regulatory and Competitive Environment
• Strucutre and regulatory framework of the financial system

• Trends in regulation/deregulation and their impact on the company.

E. Fundamental Analysis
• Capital Adequacy (assessment of true net worth of the company, its
adequacy in relation to the volume of business and the risk profile of the
assets.)
• Asset Quality (quality of the company's credit-risk management systems for
14
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monitoring credit; sector risk; exposure to individual borrowers; management Management of Inventory
of problem credits; etc.)
• Liquidity Management (capital structure; term matching of assets and
liabilities; policy on liquid assets in relation to financing commitments and
maturing deposits.)
• Profitability and Financial Position (historic profits; spreads on fund
deployment; revenues on non-fund based services; accretion to reserves; etc.)
• Interest and Tax Sensitivity (exposure to interest rate changes; tax law
changes and hedge against interest rate; etc.)
Individual Credit Rating: As indicated earlier, credit rating has become more
popular now, with financial instruments than individuals. Nevertheless, there are
now costing institutions like the Onida Individual credit Rating Agency
(ONICRA), developing specific methodology to help in rating individuals as
consumers. The ONICRA model considers the following three parametres as
important:
I. Individual Considerations
i) Personal strenghts - Qualification Occupation.
ii) Stability - Job Tenure
Duration of stay in personal
place of residence
iii) Capability - Income
Future Job Prospects
iv) Strenghts - Financial aspects
Discipline
Willingness to pay
II. Transaction Considerations
i) Risk - Security
Ownership of the asset
Control over end use of the product
colleteral
Exposure
ii) Modalities of payment - Direct deduction from salary
Advance post dated cheques
Automated debiting of bank account
Payment on due date
Payment on demand
III. Environmental Considerations- Economy
Activity 5.3

1) Why do we need models to evaluate credit proposals?

…………………………………………………………………………………….

…………………………………………………………………………………….
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Management of Current …………………………………………………………………………………….

Assets
2) List down some of the important inputs required in evaluating credit proposals.

…………………………………………………………………………………….

…………………………………………………………………………………….

…………………………………………………………………………………….

…………………………………………………………………………………….

3) Briefly explain multivariate discriminant model of credit evaluation.

…………………………………………………………………………………….

…………………………………………………………………………………….

…………………………………………………………………………………….

5.4 MONITORING RECEIVABLES

Managing receivables does not end with granting of credit as dictated by the
credit policy. It is necessary to ensure that customers make payment as per the
credit term and in the event of any deviation, corrective actions are required.
Thus, monitoring the payment behaviour of the customers assumes importance.
There are several possible reasons for customers to deviate from the payment
terms. Three of these possible reasons and their implications in credit
management are discussed below:

Changing Customer Business Characteristics: The customers, who have

earlier agreed to make payment within a certain period of time, may deviate from
their acceptance and delay the payment. For example, economic slow down or
slow down in the industry of the customers business may force the customers to
delay the payment. In fact, the bills payable become discretionary cash outflow
item in economic recession. Thus, a close watch on the performance of
customer’s industry is required.

Inaccurate Policy Forecasts: A wide deviation from the credit terms and actual
flow of cash flows show inaccurate forecast and defective credit policy. It is
quiet possible that a firm uses defective credit rating model or wrongly assesses
the credit variable. For example, it is quiet possible to overestimate the collateral
value and then lend more credit. If this is the reason for wide deviation, it
requires updating the model or training the employees.

Improper Policy Implementation: Often wide deviation is noticed in practice

while implementing credit policy. This may not be intentional but frequently in
the form of accommodating special requests of the customers. For example, a
customer may not be eligible for credit or higher credit as per the model in
force. The customer may personally see the concerned manager and request
her/him to relax the credit restriction. If there is no policy in place to deal with
these types of request and ad hoc decisions are made, then wide deviation is
possible. Often these deviations become costly for the firm. Intervention of top
officials and ad hoc decisions are cited as major reasons for widespread defaults
in many public financial institutions. Thus, it is necessary to ensure that policies
are implemented in letter and spirit.

Monitoring provides signals of deviation from expectations. There are several

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monitoring techniques available to the credit managers. The monitoring system Management of Inventory
begins with aggregate analysis and then move down to account-specific analysis.

Investments in Receivables: The decision to supply on credit basis leads to

investments in receivables. Credit policy is designed in such a way that
investment needs of receivables are optimised i.e. return is greater than cost
associated with investments. Credit monitoring starts with an assessment of
investment in receivables as a percentage of total assets. The investments in
receivables are then compared with the budget. Any deviation from budgeted
value shows delay in collection or managers deviating form the credit policy. For
example, if a firm based on credit policy worked out that investments in
receivables is 12%, the actual value for the last three months is around 18%,
there are two possible reasons. Firstly, some of the customers are not paying
and thus, the receivables value has gone up. Secondly, the managers would be
giving more credit than the prescribed limit or extend the credit period. In either
case, it requires an investigation and explanation from managers for the increased
investment in receivables.

Collection Period: Receivables can be related to sales in different ways. The

simplest form of analysis is comparing sales and receivables for different periods
to know the trend. While this analysis gives a reasonable understanding on how
the receivables have moved over the period, it fails to give an implication of the
changes in the trend. For example, if sales and receivables of two periods are
Rs. 90 lakhs, 120 lakhs and Rs.120 lakhs, Rs.140 lakhs respectively, the figures
show (i) the sales value has gone up during the period, and (ii) receivables have
also gone up along with sales. A shaper focus on changes in the trend can be
obtained by computing the collection period of the two periods. The collection
period is computed as follows:

Accounts Receivable
Collection Period = ––––––––––––––––––––––
Credit Sales per day

Credit sales per day is computed by dividing the total credit sale of the period by
the number of days of the period. If the sales value given above are related to
quarterly sales value, then sales per day for the two quarters are Rs. 1 lakh
(Rs.90 lakhs/90 days) and Rs. 1.33 lakh (Rs.120 lakhs/90 days) respectively.
The collection period for the two quarters are:

Period 1: 120/1 = 120 days Period 2: 140/1.33 =105 days

The collection period shows a decline and thus improved performance, which was
not visible earlier in simple comparison. If the sales value for the second period
is Rs. 100 lakhs instead of 120 lakhs, then average credit sales per day is Rs.
1.11 lakh and collection period is 126 days. The collection performance in this
case has marginally come down. The collection period of manufacturing
companies in BSE-30 index (Sensex) for the last five years is given in Table 5.2.
The Table shows the average collection period for companies such as Hindustan
Petroleum, Nestle, Hindustan Lever, Bajaj Auto, Gujarat Ambuja Cements, ACC,
and Colgate are low whereas BHEL, L&T, Telco, Tisco, Grasim, etc., have
experienced longer days for collection.

If customers are granted different credit periods, then customers of similar nature
are to be grouped separately and then sales, receivables and collection period
relating to each group of customers are to be computed separately. Otherwise, it
will give a distorted figure. In addition to comparing collection period of one
period with other periods, they are also compared with credit terms. Any
abnormal deviation warrants customer-wise analysis. That is, all these three
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Management of Current values for two periods can be computed for each customer to know the trends in
Assets
collection period of different customers. Such an analysis will help to narrow
down the customers who take longer time for paying the dues.

Table 5.2 : Average Collection Days of Manufacturing Companies in BSE-30 Index

Company Name 1999 2000 2001 2002 2003

Associated Cement Cos. Ltd. 44.64 40.75 24.63 27.67 23.60

Bajaj Auto Ltd. 25.78 21.51 14.43 19.88 14.42

Bharat Heavy Electricals Ltd. 194.87 231.53 249.48 240.67 209.65

Cipla Ltd. 36.25 41.88 55.63 72.35 88.92

Dr. Reddy’s Laboratories Ltd. 137.37 107.27 113.40 99.74 97.09

Grasim Industries Ltd. 62.47 53.19 50.43 41.54 34.01

Gujarat Ambuja Cements Ltd. 8.37 9.30 11.26 9.62 10.30

Hero Honda Motors Ltd. 6.32 5.22 4.87 8.15 10.13

Hindalco Industries Ltd. 33.83 33.31 32.95 42.74 41.09

Hindustan Lever Ltd. 7.47 8.43 9.12 14.58 13.44

Hindustan Petroleum Corpn. Ltd. 6.64 7.30 4.53 7.08 6.36

I T C Ltd. 35.03 10.91 9.17 14.07 13.64

Infosys Technologies Ltd. 60.76 56.27 58.13 47.28 51.68

Larsen & Toubro Ltd. 52.51 67.63 71.29 69.09 82.16

Mahanagar Telephone Nigam Ltd. 40.63 42.77 36.20 67.69 65.97

Oil & Natural Gas Corpn. Ltd. 38.76 36.64 30.24 40.92 49.85

Ranbaxy Laboratories Ltd. 107.22 98.14 80.00 83.00 76.33

Reliance Energy Ltd. 109.72 112.03 140.27 118.62 73.58

Reliance Industries Ltd. 13.30 17.32 16.36 18.58 18.02

Satyam Computer Services Ltd. 100.64 117.04 112.33 83.53 86.70

Tata Iron & Steel Co. Ltd. 75.53 64.70 61.95 53.33 37.18

Tata Motors Ltd. 103.42 43.79 33.60 41.93 42.49

Tata Power Co. Ltd. 48.91 77.59 63.59 76.55 78.32

Wipro Ltd. 64.98 71.91 74.06 68.28 72.63

18 Zee Telefilms Ltd. 159.26 167.21 162.35 246.44 236.62

 ignoumbasupport.blogspot.in

Management of Inventory

Ageing Schedule or Age Analysis: Public limited companies in their annual

report disclose debtors outstanding more than six month separately. The
receivables outstanding more than six months as a percentage of total receivables
of manufacturing companies in BSE-30 index (Sensex) for the last five years are
given in Table 5.4. The outstanding receivables for more than six months as a
percentage of total receivables is negligible in companies such as Bajaj Auto,
Colgate, Hindalco, Nestle and Ranbaxy. The percentage is high in many of the
commodity and engineering companies. While the above figures gives some
insight on the nature of receivables, a more detailed analysis is normally done
internally. Such analysis involves preparing an ageing schedule as shown below:
Table 5.3 : Ageing Schedule for Four Quarters (Rs. in thousands)
Accounts Receivable
Interval Quarter 1 Quarter 2 Quarter 3 Quarter 4

0 to 30 days 4340.00 5880.00 9100.00 13720.00

(in ) 52.69 56.62 51.89 55.97

31-60 days 2884.00 3430.00 5950.00 8232.00

(in ) 35.01 33.03 33.93 33.58

61-90 days 840.00 840.00 2240.00 2002.00

(in ) 10.20 8.09 12.77 8.17

91-120 days 168.00 224.00 238.00 546.00

(in ) 2.04 2.16 1.36 2.23

Above 120 days 5.60 11.20 8.40 14.00

(in ) 0.07 0.11 0.05 0.06

Total 8238.00 10385.00 17536.00 24514.00

The above analysis shows that while debtors for 0 to 90 days is more or less in line
with previous quarters values, debtors for 91-120 days have gone up to the highest
level. Further investigation in the form of break-up details would help to initiate
corrective steps. While feeding this type of information to top management, the
names and other details of the customers for the last two categories are also given.

Table 5.4 : Receivables Outstanding more than 6 months as a percentage of Total Receivables

Company 1999 2000 2001 2002 2003

Associated Cement Cos. Ltd. 28.15 23.08 21.01 22.09 34.14
ACC 35.15% 42.29% 27.47% 43.42% 46.74%
Bajaj Auto 0.40% 0.61% 0.84% 0.96% 0.74%
BHEL 39.16% 38.60% 41.86% 44.07% 37.60%
Cipla 16.04% 13.98% 7.94% 7.61% 8.77%
Dr. Reddy’S Laboratories 28.12% 18.16% 12.52% 5.05% 3.16%
Grasim Industries 15.65% 15.08% 14.49% 11.74% 8.00%
Gujarat Ambuja Cements 6.72% 10.16% 6.95% 11.48% 10.56%
Hero Honda 0.53% 0.68% 0.50% 1.04% 0.59%
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Management of Current Hindalco Industries 4.55% 8.39% 9.81% 2.52% 5.05%

Assets
Hindustan Lever 7.58% 4.58% 2.90% 1.84% 2.09%
HPCL 10.15% 8.75% 12.68% 5.24% 2.25%
ITC 5.15% 7.59% 7.27% 9.83% 6.69%
Infosys Technologies 0.00% 1.62% 0.00% 0.00% 0.00%
Larsen & Toubro 25.51% 33.34% 36.22% 34.77% 30.61%
MTNL 47.78% 47.30% 49.05% 61.69% 66.81%
ONGC 9.01% 7.24% 8.63% 9.41% 5.36%
Ranbaxy Laboratories 9.24% 9.66% 12.78% 8.67% 0.23%
Reliance Energy 24.85% 24.42% 26.82% 43.46% 48.56%
Reliance Industries 12.78% 7.24% 11.41% 4.12% 0.52%
Satyam Computer Services 0.00% 1.50% 6.43% 2.46% 3.01%
Tata Iron & Steel 25.06% 20.64% 22.12% 17.41% 12.99%
Tata Motors 13.06% 14.75% 22.72% 56.25% 67.06%
Tata Power 13.07% 20.50% 34.00% 33.96% 41.71%
Wipro 12.46% 5.79% 7.27% 10.54% 7.88%
Zee Telefilms 18.17% 12.63% 4.49% 44.79% 21.83%

The above two measures namely, average collection period and ageing schedule
may give misleading picture when the sales are seasonal. Suppose the average
sales per month of a quarter is Rs. 10 lakhs. The sales figures for the three
months are Rs.10 lakhs, Rs.15 lakhs and Rs.5 lakhs. Suppose the collection
pattern shows that 50 per cent of the sales is collected in the same month, 25
in the following month and the remaining 25 in the third month. If there is no
outstanding receivables at the beginning of the quarter, then the receivables
values at the end of each month are Rs. 5 lakhs, Rs.10 lakhs and Rs.12.5 lakhs.
The average collection period for the last month will be very high compared to
other months though there is no change in the payment pattern of the customers.
In order to overcome this problem, particularly in a seasonal sales pattern, the
following alternatives are suggested:
• Ratio of receivables outstanding to original sales, and
• Sales-weighted Collection Period.
Both the above measures require decomposing receivable outstanding at the end
of each month to trace the receivables with original sales. Such a decomposition
will be useful even for a non-seasonal firms.
Decomposing Receivables Outstanding at the End of Month: Another way to
spot changes in customer behaviour is to decompose outstanding receivables at
the end of each month. This is achieved by preparing a schedule of the
percentage portions of each month’s sales that are still outstanding at the end of
successive months. An illustrative table is given below:
Table 5.5 Percentage of Receivables Outstanding at the end of month
Percentage outstanding after January February March
Current Month 94 98 96
1 month 70 80 78
2 months 21 28 32
3 months 6 9 12
4 months and above 1 1 2

The following example will help you to understand the figures in the above Table.
20 Suppose Rs. 40 lakhs is outstanding receivables at the end of January, this
 ignoumbasupport.blogspot.in

consists of 94% of January’s sales, 70% of December's sales, 21% of Management of Inventory
November’s salary, 6% of October's sales and 1% of September's sales. If the
credit period is 30 days, the above analysis shows that a significant part of the
debtors takes more than one month in settling dues. While a significant part of
the customers settle down their dues by the end of second month, outstanding
beyond 2 months is also high and more importantly growing. Receivables
outstanding more than two months have gone up from 21% to 32%. The growing
trend in non-collection of dues continues for other two months too. This clearly
shows the customers have slowed down in settling their dues and thus requires
more careful analysis. If this Table 5.5 is supplemented with the names of
customers along with their dues for the second, third and fourth months, it is
helpful for follow up and appropriate action.

Sales-weighted Collection Period: In the above Table 5.5, percentages of

receivables outstanding to original sales are given. To compute sales-weighted
collection period, the values are to be summed up for each month and then
multiplied by 30. The sales-weighted collection period for January, February and
March are 57.60 days (1.92 x 30), 64.80 days (2.16 x 30) and 66 days (2.20 x
30) respectively. The general equation is:

n
Sales-weighted Collection Period =Σ (ARt/St) × 30 days
t=0

Where, ARt is Accounts Receivables of the month ‘t’ and

St is Sales of the month ‘t’

A similar table prepared for each customer will be useful to evaluate the
behaviour of each customer in settling the dues. An analysis of this behaviour for
a year can be used to assign ranks to the customers and such ranking can be
used while taking credit policy or credit decision. Instead of using outstanding
receivables values, some organisations use the payment values. However, both
should lead to same conclusion.

Conversion Matrix: This is a simple technique, whereby credit sales of each

month are patterned as per their collection. This shows how the credit sales of a
month are collected in the subsequent months. This reveals the laxity or
otherwise of the collection department. Look at the following conversion matrix to
judge whether the collection pattern is improving, stable or deteriorating.
Conversion Matrix

Month Credit
Sales
(Rs.) Jan Feb Mar Apr May June July Aug Sept

Jan 1,00,000 10,000 40,000 30,000 20,000

(10%) (40%) (30%) (20%)

Feb 80,000 11,000 28,000 32,000 9,000

(14%) (35%) (21%) (24%)

Mar 1,20,000 18,000 48,000 25,000 29,000

(15%) (40%) (21%) (24%)

Apr 1,60,000 19,500 72,500 38,000 30,000

(12%) (45%) (24%) (19%)

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Management of Current May 2,00,000 20,000 72,000 60,000 48,000

Assets
(10%) (36%) (30%) (24%)

June 1,60,000 14,500 56,000 49,00040,500

(9%) (35%) (31%) (25%)

Total Collection 10,000 51,000 76,000 1,19,500 1,26,500 1,53,500 1,46,000 97,000 40,500

It may be observed from the above data that our Hypothetical company, making
a sale of Rs. 1 lakh could collect only 10% in the same month and around 50%
after two months. The above represents a case of deteriorating collection
efficiency.

Receivables Variance Analysis: Receivables budget can be prepared from sales

budget and credit policy. This information is any way required to prepare cash
budget. In receivables variance analysis, the actual reason for actual value of
receivables varying with budgeted value. Actual receivables vary with that of
budget for two reasons - the level of sales and ratio of receivable outstanding.
For example, if the budgeted sales for a month is Rs. 20 lakhs and normally 80
per cent of the sales are outstanding at the end of month, then receivables at the
end of month as per the budget should be Rs. 16 lakhs. If the actual
receivables is Rs. 18 lakhs, it could be due to increase in the actual sales from
Rs. 20 lakhs to Rs. 22.50 lakhs or alternatively increase in the percentage of
credit sales from 80 to 90 or combination of both. In order to compute the
causes for variance, three inputs are required: budgeted receivables, revised
budgeted receivables based on actual sales and actual receivables. The revised
budgeted receivables is computed based on actual sales and credit policy. In
other words, it is the budgeted receivables value for the actual sales. The
difference between the first two values (budgeted receivables and revised
budgeted receivables for actual sales) explains the part of receivable variance
arising out of changes in the sales. The difference between the second and third
values (revised budgeted receivables and actual receivables) is on account of
changes in the collection efficiency. The difference between the first and last
values is the total receivables variance.

Other simple measures of receivables management are ratio of credit sales to

total sales, Number of credit proposals rejected to total credit proposals received
and bad debt loss index.

Activity 5.4

1) Why customers often fail to adhere the credit terms?

…………………………………………………………………………………….

…………………………………………………………………………………….

…………………………………………………………………………………….

2) List down various indicators used in macro-analysis of receivables.

…………………………………………………………………………………….

…………………………………………………………………………………….

…………………………………………………………………………………….

22
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3) How do you set right the seasonal variation in sales affecting some of the Management of Inventory
indicators used in receivables analysis?

…………………………………………………………………………………….

…………………………………………………………………………………….

…………………………………………………………………………………….

5.5 COLLECTING RECEIVABLES

The analysis explained earlier are useful to know the trend of collection and
identify customers, who are not paying on due dates. This should enable the
management to take appropriate action to collect the dues, which is the main
objective of receivables management. Collecting receivables begins with timely
mailing of invoices. There are several procedures available to credit managers,
who must judiciously decide when, where and to what extent pressure should be
applied to delinquent customers. Management of collection activity should be
based on careful comparison of likely benefits and costs.

Inexpensive procedures include periodical mailing of duplicate bills reminding the

customers that the account is not settled or sending a formal letter informing non-
payment of bill and requesting the customer to pay immediately. Written follow-up
on an overdue account is referred to as dunning. If a customer fails to respond
to these reminders, then expensive procedures are initiated. Personal telephone
calls and reminder through registered post are initially tried. Even if these steps
fail to deliver the desired results, a personal visit by the credit manager or
representative to sort out the issue would be useful. If the credit manager
realises that the customer is wilfully defaulting or is in deep trouble and hence
unlikely to pay the dues, a formal legal action is initiated either to recover the
dues or file a liquidation petition before the court to recover the dues. It is
difficult to prescribe exactly as to which and when these collection procedures
should be adopted. If collection policy is strict, then it would reduce the
outstanding receivables but at the same time frightened many potential customers
from doing business. On the other hand, a liberal collection policy would invite
many wilful defaulters to do business with the company.

The above discussion assumes that the firm takes the responsibility of collection.
Two alternatives are available to firms in collecting the receivables. The first one
called factoring enables the firm to transfer the receivables to factoring agent,
who takes the responsibility of collection. Some factoring agents takes the credit
risk (i.e. the factoring agents bear the loss on account of bad debts) and others
accept factoring without credit risk. In India, we have factoring subsidiaries of
Canara Bank, SBI, etc. and Exim Bank does the factoring service relating to
export bills. The second one is called receivables securitisation. Securitisation is
somewhat similar to factoring but here the securitising agent sells the units of
receivables to investors in the market. Though the concept of securitisation is
popular in finance related receivables like housing loans, credit cards receivables,
lease rentals, etc., the concept is slowly spreading to other types of receivables.
A few securitisation deals have already been completed in India and the market
will witness more such transactions in the near future.

5.6 STRATEGIC ISSUES IN RECEIVABLES

MANAGEMENT
Business management today involves continuous formulation of strategies and
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Management of Current also, to develop and carry out tactics to implement the strategies to gain
Assets
competitive advantage. The discussion on receivables management so far focused
on operational issues such as how changes in credit policy affects investments in
receivables, how to monitor collection pattern, what are the options available in
dealing with delinquent customers, etc. Receivables management, however, can
support the strategies being pursued by the organisation to gain certain
competitive strength.

Firms pursuing strategies to acquire cost leadership need a suitable credit policy
to support their strategies. For instance, if a firm is trying to achieve cost
leadership through economies of scale of production, then it has to generate a
large volume of sales. Since credit term is an economic variable in buying
decision, the credit terms should be supportive to sell large volume. That means,
the firm may have to offer more days of credit particularly for those who buy in
large quantity. Of course, the cost of investment in receivables will go up initially
but without a liberal credit policy, the assets created to achieve economics of sale
will be idle. In fact, the additional cost of investments in receivables need to be
considered while computing the benefit arising out of economies of scale.

Firms pursuing strategies to acquire product differentiation have limited customer

base. In order to gain access to this segment, the firm may have to pursue
liberal credit term but once the brand acquired the desired value, credit terms can
be made tight. For instance, many established multinational firms now require the
dealers and distributors to deposit the entire amount of the consignment before
lifting the delivery. Similarly, firms pursuing market penetration may have to work
with low profit margin or selling just above the variable cost. Liberal credit terms
would add cost and increase bad debts value. Firms may be reluctant to have
liberal policy at this stage unless it is essential to achieve penetration. Firms with
a large market share in a low growth industry would not invest additional capital
in receivables since the strategy is to harvest the benefit. In other words,
instead of allowing the market to decide the credit terms of the company, it is
possible for the firm to influence the market through credit policy.

Credit policy can also be used to change the product life cycle and investment
pattern. For instance, the life cycle of a product X is 10 years, which is worked
out on the basis of existing credit terms and volume of turnover. Assume the
total sales during the period is 2,50,000 units. The volume achieved is initially low,
then it increases to reach a peak at the end of 4th year and then declines over
the remaining 6 years. Based on different capacity options, it is found that a
capacity of 20,000 units for six-year period is optimum and offers highest net
present value. The firm now found that by increasing the credit period, it can
sell more units and thus can go for a capacity of 30,000 units and achieve same
NPV in four-year period. The second option may be suitable on account of
increased uncertainty on the product as the product moves into the latter part of
the life cycle and also getting economies of scale, which was not possible with
lower turnover in the first case. Shortening product life cycle has certain
advantages as well as disadvantages. The advantages are obvious. It increases
NPV and removes uncertainty. At the same time, it requires more R&D to
come out with a new and improved product and additional investment much
earlier than originally visualised. If competitors are able to come out with better
product version, the firm has to suffer higher loss because of higher capacity.
The firm has to develop various scenarios and study their impact on the overall
organisation goal.

Credit policy and its terms assume strategic importance if a firm is primarily
supplying its products or services to select firms. Suppose company R is one of
the ten customers of Company L. Company R is now going for massive
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Company R since the debt-capacity remaining is not adequate. If Company L has Management of Inventory
reasonable borrowing capacity or internal generation, it can extend the terms of
credit. L&T had come out with a major issue some years back to provide
suppliers credit to Reliance Industries for their expansion projects. Such kind of
suppliers credit may also be feasible when the interest cost of a domestic firm is
much higher than the interest cost of supplier firm located in a different country.

A firm dealing with a large number of customers may find it difficult to manage
the receivables within the existing organisational set up. If a few other group
companies also face similar problems, it may start a separate subsidiary to
manage the receivables of all group companies. Many companies have started
their subsidiary to manage share transfer jobs of group companies. It is also
equally possible to centralise the credit rating service of the customers through
subsidiaries. Instead of starting their own subsidiaries, it is also possible to go in
for factoring services and credit rating agencies to outsource these services.
Many foreign banks outsource the services not directly related to their core
activities in order to keep the organisation lean. It is a way to convert many of
the fixed costs into variable costs. All these decisions have strategic implications
and thus, it is difficult to visualise the receivables management as a operational
issues of management in the modern business environment.

Activity 5.5

1) List down a few inexpensive and expensive methods of credit follow-up.

…………………………………………………………………………………….

…………………………………………………………………………………….

…………………………………………………………………………………….

2) A firm in high-growth industry would like to build up more market share.

What type of credit policy is suitable to be consistent with this strategy?

…………………………………………………………………………………….

…………………………………………………………………………………….

…………………………………………………………………………………….

3) How credit policy affects investment decisions?

…………………………………………………………………………………….

…………………………………………………………………………………….

…………………………………………………………………………………….

5.7 SUMMARY
The use of credit in the purchase of goods and services is so common that it is
taken for granted. Selling goods or providing services on credit basis lead to
accounts receivables. Though a lot of discussion is going on in the Indian industry
on how to cut down the investments in inventories through concepts such as
Just-in-Time (JIT), MRP, etc., investments in receivables have gone up and firms
are demanding more credit from banks and specialised institutions to deal with
receivables. Since investment in receivables has a cost, managing receivables
assumes importance. Receivables management starts with designing appropriate
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Management of Current credit policy. Credit policy involves fixing credit period, discount to be offered in
Assets
the event of early payment, conditions to be fulfilled to grant credit and fixing
credit limit for different types of customers. It is essential for the operating
managers to strictly follow the credit policy in evaluating credit proposals and
granting credit. To evaluate the credit proposal, it is necessary to know the
credit worthiness of the customers. Credit worthiness is assessed by collecting
information about the customers and then fitting the values into credit evaluation
models. There are number of credit evaluation models which range from simple
decision tree analysis to sophisticated multivariate statistical models. The firm
has to develop a suitable model, test the model with historical data to validate the
model and use it for credit evaluation. Models also need to be periodically
updated. Once the credit is granted, then it should be monitored for collection.
Different methodologies are available to get a macro picture on collection
efficiency. Micro analysis in the form of individual customer analysis is done
wherever there is a deviation from the expectation. It is equally important in
dealing with delinquent customers. There are several options, simple reminders to
legal action, available before the credit managers in dealing with such default
accounts and appropriate method is to be selected with an objective of benefit
exceeding cost. The use of credit policy and credit analysis is not restricted to
the operational managers in dealing with day-to-day activities of the firm. In the
competitive world, credit policy and analysis provide a lot of strategic inputs.
Credit policy of an organisation is in line with the desired strategy that the
organisation wants to pursue to gain certain competitive advantages.

5.8 Key Words

Terms of Credit : These refer to eligibility conditions and payment details for
granting credit by the company to a customer.

Creditworthiness : Capacity of the customer to meet payment obligations.

Credit Policy : Decision of the firm to grant or not to grant credit. It consists
of the components such as credit period, discount, credit eligibility and credit limit.

Credit Period : Refers to the minimum and maximum time limits for which
credit is granted.

Credit limit : Is the limit upto which credit is granted

Decision Tree : Is a model indicating decision points and chance events for
taking a decision.

Credit Scoring System : A system which attempts to rank customers as good, bad
or average by a scoring mechanism.

Business Analysis : An examination of risk factors influencing business

prospects in terms of competition, demand and supply position, structure of
industry, cost structure, labour relations, etc.

Financial Analysis : An examination of financial performance and ability of a

business unit to generate income.

Fundamental Analysis : Refers to capital adequacy asset quality, liquidity

management and interest over tax sensitivity.

Collection Period : Indicates the time taken by the collection department in

collecting its book debts. A comparison of collection period with credit period tells
us whether the debts were collected within the stipulated time or not.
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Ageing Schedule : A method of classifying debts according to the number of Management of Inventory
days the debt remained outstanding.

Conversion matrix: Sequencing of debts in the order of their collection.

Variance Analysis : A comparison of Budgeted figures with Actuals to note

down deviations.

9.9 SELF-ASSESSMENT QUESTIONS

1. Explain important components of receivables management system?

2. Why do we need a credit policy? How do you evaluate credit policy?

3. How do you assess the credit worthiness of customers?

4. Discuss a few important financial ratios and analysis used in managing receivables.

5. Assume a customer, who used to pay the dues in time earlier, has suddenly
defaulted. A couple of reminders sent to him fail to get any response. As a
credit manager, you have two issues to decide. You have to first decide
whether to continue the supply to the customer on credit basis. The second
issue is how to deal with the customer to recover the dues. In the normal
course, you have to initiate legal process to recover the dues but this may
strain your firm’s relationship with the customer. You can’t also be silent
since the money involved is quiet high and your firm is incurring interest cost
on this credit. How do you deal with this customer and decide the two
issues?

6. Hindustan Automobiles is manufacturing heavy vehicles and presently offering

a credit period of 45 days. In order to increase the sales from its current
level of Rs. 400 crore., it is contemplating to increase the credit period to 60
days. This is expected to bring additional sales of Rs. 40 crore. There is
no change in the collection and bad debts cost. The company is likely to earn
a contribution margin of 20%. The short-term borrowing cost is 15%.
Evaluate the new credit period and its impact on profitability.

7. Regal Industries found that a very few debtors avail the discount, which is
“1.5/10 net 60”. The firm is presently borrowing at 15%. Since finance for
receivables is limited, it is turning down many credit proposals and thus loose
the opportunity to increase the sales. The firm now wants to revise the
discount policy and make it attractive to motivate some of the existing
customers to avail the discount. The funds released could be used for
accepting new customers. The additional details available to you are:
Contribution margin is 20%; Average collection period is 60 days; Sales could
be increased to any level. With these additional details evaluate the proposed
discount policy of “4/10 net 60”. Compute the impact of new policy on
profitability of the firm.

8. The proposed credit policy of R.K. mills would cut down the bad debts from
4% to 2%. It will also improve the collection period from 60 days to 30
days. The firms current sale of Rs. 80 lakhs will decline by 20% on account
of this new policy. If the contribution margin cost of borrowing are 15% and
14% respectively, how the new credit policy affect the profit of the firm.

9. Your firm is following a credit rating model developed internally to assess the
credit worthiness of customers. The cut-off score is 4.8 points. Your analysis
of historical behaviour of customers with different points shows the
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