Managing Accounts Receivable

FIN 340

Prof. David Allen

Managing Account Receivable• The firm faces a tradeoff between costs (slow payers

and bad debts) and benefits (attracting sales).

Credit Policy• Credit period

• Length of time buyers are given to pay for purchases• e.g. net 30• Often determined by competitive situation

• Discounts• e.g. 2/10 net 30• Provides an incentive for customers to pay early• Reduces DSO, and thus the amount of financing for

receivables.

Credit Policy• Credit standards

• Required financial strength customers need to qualify for credit.

• Collection policy• How tough or lax is the firm in trying to collect on slow-

paying accounts?• Dunning letters• Collection agency

Setting the Credit Period and Standards• Credit period

• Often determined by competitive situation

• Setting credit standards• Firm needs a method to determine likelihood of payment, i.e.

credit quality.• an external credit report (D&B, TRW)• An internally generated credit score (similar to Altman Z)• Five C’s

• Character• Capacity• Capital (net worth)• Collateral• Conditions

Setting the Credit Period and Standards• Business credit information is available at:

• https://www.dnb.com/product/birsampl.htm

• The D&B PAYDEX® Score: D&B's unique dollar-weighted numerical indicator of how a firm paid its bills over the past year, based on trade experiences reported to D&B by various vendors. The D&B PAYDEX Score ranges from 1 to 100, with higher scores indicating better payment performance.

Setting the Credit Period and Standards• Key to the D&B Rating

Setting the Credit Period and Standards• Key to the D&B Rating

Collection Policy• The firm needs a procedure for dealing with past due

accounts.• Dunning letters• Collection agency

Other Factors Influencing Credit Policy• Profit potential

• Interest on past due accounts may be a significant source of profit

• Legal considerations• Robinson-Patman Act – makes it illegal to offer more

favorable credit terms to one customer (or class of customers) than another, unless the differences are cost-justified.

Basic Objectives:• Managing delinquencies: The older an account

becomes, the more difficult it is to collect. So, we need to manage accounts so that few become delinquent, and to identify those that will become a problem as early as possible.

• Managing credit risk: The goal here is to minimize the company’s losses on accounts that will not be fully collected. Continued business with the account is unlikely.

• Forecasting: As a part of its ongoing cash budgeting process, the firm needs to forecast the cash flows from the accounts receivable (AR) portfolio, and to estimate bad debt losses.

Measuring Accounts Receivable Performance• Individual accounts are monitored for compliance with

payments standards in order to initiate appropriate actions when customers delay payment beyond agreed upon terms.

• On the aggregate level, monitoring is important in setting overall policy guidelines with respect to risk and return and in forecasting cash flows and bad debt losses.

Days Sales Outstanding• In our earlier coverage of ratio analysis, we used the

“days sales outstanding” (DSO, also known as average collection period or average age of receivables) to measure the average length of time it takes to collect accounts receivable.

• It can be shown that the DSO is biased when the firm’s sales are seasonal or cyclical in nature.

Days Sales Outstanding• DSO = accounts receivable / average daily sales• So, for annual data,

DSO = accounts receivable / (annual sales / 365)

• If we are measuring DSO before year-end, we need to adjust the equation as follows:

• DSOsub-period = accounts receivable / (sub-period sales / days in sub-period)

• For example, if we measure DSO at the end of each quarter, then:

• DSOquarterly = accounts receivable / (quarterly sales / 91)

• where 91 = approx. number of days in one quarter

Aging Schedule• The aging schedule is one of the primary tools used to

measure accounts receivable performance.• It shows accounts receivable in dollar or percentage

terms, as a function of age of invoice and month of sale.

DSO and Aging Schedule - Assumptions• In this example, we assume that customer payment

behavior is constant, and sales are flat.SALES DATA AND PAYMENT BEHAVIOR

% of sales paid in month of sale 50%% of sales paid 1 month after sale 30%% of sales paid 2 months after sale 20%

Amounts still outstanding

MonthMonthly

Sales At end of month 1 month later 2 months laterNovember 100$ 50$ 20$ -$ December 100$ 50$ 20$ -$ January 100$ 50$ 20$ -$ February 100$ 50$ 20$ -$ March 100$ 50$ 20$ -$ April 100$ 50$ 20$ -$ May 100$ 50$ 20$ -$ June 100$ 50$ 20$ -$ July 100$ 50$ 20$ -$ August 100$ 50$ 20$ -$ September 100$ 50$ 20$ -$ October 100$ 50$ 20$ -$ November 100$ 50$ 20$ -$ December 100$ 50$ 20$ -$

DSO and Aging Schedule - Flat SalesAGING SCHEDULE - DOLLARS

Month

Accounts Receivable

at Month EndAmount current at month end

Amount past due 1 to 30 days

at month end

January 70$ 50$ 20$ February 70$ 50$ 20$ March 70$ 50$ 20$ April 70$ 50$ 20$ May 70$ 50$ 20$ June 70$ 50$ 20$ July 70$ 50$ 20$ August 70$ 50$ 20$ September 70$ 50$ 20$ October 70$ 50$ 20$ November 70$ 50$ 20$ December 70$ 50$ 20$

DSO and Aging Schedule - Flat SalesAGING SCHEDULE - PERCENT

Month

Accounts Receivable

at Month EndPercent current at month end

Percent past due 1 to 30 days

at month end

January 70$ 71.4% 28.6%February 70$ 71.4% 28.6%March 70$ 71.4% 28.6%April 70$ 71.4% 28.6%May 70$ 71.4% 28.6%June 70$ 71.4% 28.6%July 70$ 71.4% 28.6%August 70$ 71.4% 28.6%September 70$ 71.4% 28.6%October 70$ 71.4% 28.6%November 70$ 71.4% 28.6%December 70$ 71.4% 28.6%

DSO and Aging Schedule - Flat Sales• Here we are assuming that customers do not change their payment

behavior over time. The percentages paid each month, relative to the sale date, do not vary.

• Note that in every case the DSO is the same, regardless of the month, or whether we used quarterly sales or year-to-date sales figures.

DSO CALCULATIONS Based on Quarterly Sales DataBased on Year-to-Date

Sales Data

MonthMonthly

Sales

Receivables Outstanding At End of Month

ADS = quarterly sales / 91 DSO ADS DSO

January 100$ 70$ February 100$ 70$ March 100$ 70$ 3.30$ 21.2 days 3.30$ 21.2 daysApril 100$ 70$ May 100$ 70$ June 100$ 70$ 3.30$ 21.2 days 3.30$ 21.2 daysJuly 100$ 70$ August 100$ 70$ September 100$ 70$ 3.30$ 21.2 days 3.30$ 21.2 daysOctober 100$ 70$ November 100$ 70$ December 100$ 70$ 3.30$ 21.2 days 3.30$ 21.2 days

DSO and Aging Schedule - Assumptions• In this example, we assume that customer payment

behavior is constant, and sales are seasonal.SALES DATA AND PAYMENT BEHAVIOR

% of sales paid in month of sale 50%% of sales paid 1 month after sale 30%% of sales paid 2 months after sale 20%

Amounts still outstanding

MonthMonthly

SalesAt end of

month1 month

later2 months

later

November 100$ 50$ 20$ -$ December 100$ 50$ 20$ -$ January 100$ 50$ 20$ -$ February 120$ 60$ 24$ -$ March 140$ 70$ 28$ -$ April 120$ 60$ 24$ -$ May 100$ 50$ 20$ -$ June 80$ 40$ 16$ -$ July 100$ 50$ 20$ -$ August 100$ 50$ 20$ -$ September 100$ 50$ 20$ -$ October 150$ 75$ 30$ -$ November 150$ 75$ 30$ -$ December 150$ 75$ 30$ -$

DSO and Aging Schedule - Seasonal SalesAGING SCHEDULE - DOLLARS

Month

Accounts Receivable

at Month End

Amount current at

month end

Amount past due 1 to 30 days at month

end

January 70$ 50$ 20$ February 80$ 60$ 20$ March 94$ 70$ 24$ April 88$ 60$ 28$ May 74$ 50$ 24$ June 60$ 40$ 20$ July 66$ 50$ 16$ August 70$ 50$ 20$ September 70$ 50$ 20$ October 95$ 75$ 20$ November 105$ 75$ 30$ December 105$ 75$ 30$

DSO and Aging Schedule - Seasonal SalesAGING SCHEDULE - PERCENT

Month

Accounts Receivable

at Month End

Percent current at

month end

Percent past due 1 to 30 days at month

end

January 70$ 71.4% 28.6%February 80$ 75.0% 25.0%March 94$ 74.5% 25.5%April 88$ 68.2% 31.8%May 74$ 67.6% 32.4%June 60$ 66.7% 33.3%July 66$ 75.8% 24.2%August 70$ 71.4% 28.6%September 70$ 71.4% 28.6%October 95$ 78.9% 21.1%November 105$ 71.4% 28.6%December 105$ 71.4% 28.6%

DSO and Aging Schedule - Seasonal Sales• Note that DSO is changing over time, even though the customers’ payment

behavior is not.• So, DSO cannot be used to accurately monitor receivables if the firm’s sales

are seasonal or cyclical.

DSO CALCULATIONBased on Quarterly

Sales DataBased on Year-to-Date

Sales Data

MonthMonthly

Sales

Receivables Outstanding

At End of Month

ADS = quarterly sales / 91 DSO ADS DSO

January 100$ 50$ February 120$ 80$ March 140$ 94$ 3.96$ 23.8 days 3.96$ 23.8 daysApril 120$ 88$ May 100$ 74$ June 80$ 60$ 3.30$ 18.2 days 3.63$ 16.5 daysJuly 100$ 66$ August 100$ 70$ September 100$ 70$ 3.30$ 21.2 days 3.52$ 19.9 daysOctober 150$ 95$ November 150$ 105$ December 150$ 105$ 4.95$ 21.2 days 3.87$ 27.1 days

DSO and Aging Schedule - Seasonal Sales• So, as sales increase, the DSO is an upwards biased

measure of the true payment behavior of the firm’s customers (i.e. DSO overestimates collection time).

• Likewise, as sales decrease, the DSO is a downwards biased measure of the true payment behavior of the firm’s customers (i.e. DSO underestimates collection time).

Payment Patterns Approach to Monitoring AR• In the previous section, we showed that the DSO

measure is biased when sales are changing over the measurement period, even if our customers do not change their payment behaviors.

• We will now introduce a technique know as the “payments pattern approach” that allows us to more accurately determine trends in the payment behavior of our customers.

Payment Patterns Approach to Monitoring AR

Amount Collected in Month

MonthCredit Sales Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar

Oct 1,000 300 300 200 200

Nov 1,000 300 300 200 200

Dec 1,000 300 300 200 200

Jan 1,200 480 420 240 60

Feb 1,400 560 490 280 70

Mar 1,600 640 560 320 80

Apr 1,600 800 560 240 -

May 1,600 800 560 240 -

Jun 1,600 800 560 240 -

Jul 1,400 630 420 210 140

Aug 1,200 540 360 180 120

Sep 1,000 450 300 150 100

Oct 1,200 360 360 240 240

Nov 1,200 360 360 240 240

Dec 1,200 360 360 240 240

• In the example below, we do not make the assumption that we know the payment behavior of our customers. Instead, we let the data tell us what is happening.

• The table below reports the credit sales by month and the collections received for that month’s sales.

Payment Patterns Approach to Monitoring AR• Next, we subtract the amount received from the sales

to determine the remaining balance by month:

Amount Still Outstanding at End of Month

MonthCredit Sales Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar

Oct 1,000 700 400 200 -

Nov 1,000 700 400 200 -

Dec 1,000 700 400 200 -

Jan 1,200 720 300 60 -

Feb 1,400 840 350 70 -

Mar 1,600 960 400 80 -

Apr 1,600 800 240 - -

May 1,600 800 240 - -

Jun 1,600 800 240 - -

Jul 1,400 770 350 140 -

Aug 1,200 660 300 120 -

Sep 1,000 550 250 100 -

Oct 1,200 840 480 240 -

Nov 1,200 840 480 240 -

Dec 1,200 840 480 240 -

Payment Patterns Approach to Monitoring AR• Divide each figure by the sales for that month to

convert to percentages:

Amount Still Outstanding at End of Month

MonthCredit Sales Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar

Oct 1,000 70% 40% 20% 0%

Nov 1,000 70% 40% 20% 0%

Dec 1,000 70% 40% 20% 0%

Jan 1,200 60% 25% 5% 0%

Feb 1,400 60% 25% 5% 0%

Mar 1,600 60% 25% 5% 0%

Apr 1,600 50% 15% 0% 0%

May 1,600 50% 15% 0% 0%

Jun 1,600 50% 15% 0% 0%

Jul 1,400 55% 25% 10% 0%

Aug 1,200 55% 25% 10% 0%

Sep 1,000 55% 25% 10% 0%

Oct 1,200 70% 40% 20% 0%

Nov 1,200 70% 40% 20% 0%

Dec 1,200 70% 40% 20% 0%

Payment Patterns Approach to Monitoring AR• Then, measure the time as months since the sale,

rather than by the name of the month:

Amount Outstanding at End of Month

MonthCredit Sales

Month of Sale

1 Month After Sale

2 Months After Sale

3 Months After Sale

Oct 1,000 70% 40% 20% 0%

Nov 1,000 70% 40% 20% 0%

Dec 1,000 70% 40% 20% 0%

Jan 1,200 60% 25% 5% 0%

Feb 1,400 60% 25% 5% 0%

Mar 1,600 60% 25% 5% 0%

Apr 1,600 50% 15% 0% 0%

May 1,600 50% 15% 0% 0%

Jun 1,600 50% 15% 0% 0%

Jul 1,400 55% 25% 10% 0%

Aug 1,200 55% 25% 10% 0%

Sep 1,000 55% 25% 10% 0%

Oct 1,200 70% 40% 20% 0%

Nov 1,200 70% 40% 20% 0%

Dec 1,200 70% 40% 20% 0%

Avg. still outstanding 61% 29% 11% 0%

Amount Collected by Month

MonthCredit Sales

Month of Sale

1 Month After Sale

2 Months After Sale

3 Months After Sale

Oct 1,000 30% 30% 20% 20%

Nov 1,000 30% 30% 20% 20%

Dec 1,000 30% 30% 20% 20%

Jan 1,200 40% 35% 20% 5%

Feb 1,400 40% 35% 20% 5%

Mar 1,600 40% 35% 20% 5%

Apr 1,600 50% 35% 15% 0%

May 1,600 50% 35% 15% 0%

Jun 1,600 50% 35% 15% 0%

Jul 1,400 45% 30% 15% 10%

Aug 1,200 45% 30% 15% 10%

Sep 1,000 45% 30% 15% 10%

Oct 1,200 30% 30% 20% 20%

Nov 1,200 30% 30% 20% 20%

Dec 1,200 30% 30% 20% 20%

Avg. collected 39% 32% 18% 11%

Payment Patterns Approach to Monitoring AR• By examining either table above, we can see that the firm’s customers pay

slowly in the Oct - Dec quarter, and most quickly in the Apr – Jun quarter.

Payment Patterns Approach to Monitoring AR• The Payment Patterns Approach shows the

percentage of credit sales in each period (usually a month) that are outstanding at the end of each subsequent period.

• It is not subject to bias when sales are seasonal, and is useful for projecting receivables and collections in preparing a cash budget.

Managing Credit Risk• Typically, the most important element is controlling the

risk of non-payment. • In international trade, there is also foreign exchange

risk and country risk.

Guarantees and Letters of Credit• A guarantee may be obtained is situations where the

buyer’s credit quality is insufficient. The guarantee may be from the firm’s parent, or some type of government agency that has a stake in the buyer’s success.

• A letter of credit is an obligation of a bank to remit funds when clearly pre-specified terms and conditions are met. It is issued by the buyer’s bank, and facilitates trade when the seller is located in another country.

Credit Insurance And Factoring• Credit Insurance

• The selling firm submits a list of buyers, and typical amounts outstanding to the credit insurer. The insurer replies with a maximum insurable amount for each buyer and a price for the policy.

• The agreement also details the deductible amount and coinsurance of credit losses above a predetermined level.

• If an invoice becomes past due by more than a preset number of days, it is submitted to the insurer, who pays the face value to the seller (less deductibles and coinsurance).

• The insurer is then responsible for collecting the account.

Credit Insurance And Factoring• Credit insurance is often used by small to medium sized

firms that are uncomfortable with their credit exposure to a number of large buyers.

• For the process to be economically feasible, the credit insurer must be superior in evaluating credit risk, and or have some diversification or economies of scale.

• European companies use credit insurance much more than those in the U.S., in large part due to the lack of available credit information.

Factoring• Involves the sale or transfer of title of accounts

receivable to a factoring company, which is usually a subsidiary of a financial services company or bank.

• The factor provides the credit and collection functions.• Options:

• With or without recourse: With recourse means the seller is liable if the factor cannot collect on an account. Most factoring is without recourse.

• With or without notification: With notification means that the buyer knows that its account has been factored and is required to remit directly to the factor. Most factoring is on a notification basis.

Factoring• Maturity or discount factoring:

• With maturity factoring, funds are available to the seller on the average collection date.

• With discount factoring, funds are remitted to the seller sooner than the average collection date. Most users choose discount factoring to speed up cash receipts.

• Pricing: usually a fixed percentage (about 1%) of the invoice is the commission.

• With discount factoring, the interest rate is often the prime rate plus 2% or 3%. In addition, there is also a reserve of about 3% to 5% for returns, disputes, etc.

Factoring• Advantages:

• Having the factor perform the credit and collection function is very useful for companies without expertise in this area.

• Small companies are often not well diversified in their receivables exposure. Factoring mitigates this exposure.

• For firms with highly seasonal sales, the ability to accelerate cash flows is very beneficial.

• The factor performs a useful accounting function for the selling firm.

Factoring• Disadvantages:

• Factoring can be much more expensive for the seller than bank borrowing or credit insurance.

• Since the factor controls the credit and collection function, the seller may lose the ability to enhance revenues through adopting more lenient credit and collection procedures.

• Since the factor will not accept all credits, or may place a limit on its exposure to certain buyers, the seller is still stuck with performing the credit and collection function on some of its customers.

Collections Policy• Issues:

• Promptness: Delinquent accounts tend to perform much worst if not attended to properly.

• Cost/benefits: Certain accounts may not respond to a particular form of collection procedure.

• It is important to understand which procedures make economic sense at a given stage in the collection process.

Collections Policy• Internal Strategies

• It is important at an early stage to distinguish those accounts that are actually delinquent from those delays that are caused by some dispute over the merchandise being invoiced.

• It is prudent for the credit grantor to confirm in writing that the goods as ordered were in fact received before initiating collections efforts.

• Most companies begin with relatively mild reminders so as not to agitate customers that are, in the longer-term, profitable.

• As the delinquency increases, the long-term revenue potential of the customer diminishes.

Collections Policy• External Strategies

• Collection Agencies• The usual agency charges 30-50% of the collected

amount as its fee. • If the seller has an ongoing relationship with the collection

agency, the charges may be based on the historical recovery rate.

• Adjustment Bureaus• Usually organized by a given industry group to aid its

members in the collection of bad debts.

Analyzing Proposed Changes in Credit Policy• The cost to finance (carry) the additional receivables

is:• (DSO)(Sales per day)(variable cost ratio)(cost of funds)

Analyzing Proposed Changes in Credit Policy• Wahoo Corp. sells to its customers on terms on net 30. It is considering relaxing its

credit terms to 2/10 net 30 in order to attract more sales.• In addition, the firm will reduce its spending on credit analysis and collection.• The firm's marketing department believes that this change in policy will result in a 5%

increase in gross sales.

• Under the current policy, 70% of customers pay in 30 days.• Under the current policy, 30% of customers pay in 50 days, or 20 days late.

• Under the proposed policy, 20% of customers are expected to take the offered discount, and pay in 10 days.

• Under the proposed policy, 60% of customers are expected to forego the discount, and pay in 30 days.

• Under the proposed policy, 20% of customers are expected to forego the discount, and pay in 50 days, or 20 days late.

• Under the currrent policy, the firm spends $5,000 per year on credit analysis and collection efforts.

• Under the proposed policy, the firm expects to reduce spending to $3,000 per year on credit analysis and collection efforts.

• Complete the spreadsheet below to determine the effect on the firm's profitability of the proposed change.

Analyzing Proposed Changes in Credit Policy

Inputs:Current Policy

Proposed Policy

Annual sales 365,000$ 383,250$

Variable cost ratio 65% 65%

Cost of funds (financing cost) 12% 12%

Discount for early payment 0% 2%

Early payment period 10 days

Percent of customers taking discount 20%

Full amount due in 30 30 days

Percent of customers paying full amount on time 70% 60%

Age of invoices for customers paying late 50 50 days

Percent of customers paying late 30% 20%

Days per year 365 365

Annual credit analysis and collection expense 5,000$ 3,000$

Bad debt losses as percent of gross sales 3% 2%

Income tax rate 30% 30%

Analyzing Proposed Changes in Credit Policy

• Profits increase under the proposed system, so the firm would adopt it.

Outputs:Current Policy

Proposed Policy

Days sales outstanding 36.00 30.00

Gross sales 365,000 383,250

Less discounts - 1,533

= Net sales 365,000 381,717

Less variable production costs 237,250 249,113

= Profit before credit cost and taxes 127,750 132,605

Less credit related costs:

Cost of carrying receivables 2,808 2,457

Credit analysis and collection expenses 5,000 3,000

Bad debt losses 10,950 7,665

=Profit before taxes 108,992 119,483

Less taxes 32,698 35,845

=Net income 76,294 83,638

Change in net income 7,343