1. Cash Flow Review Techniques
We have all learned how to compute for a borrower’s cashflow. In this session, one will learn how to analyze certain components of the prepared cashflow to be able to establish the accuracy and consistency of the data used in its preparation.

2. Objectives At the end of this session, Account
Officers will be able to –
Review the Cash Flow and test the accuracy and consistency of data using the five Cash Flow Review Technique tools.
Make the adjustments to Cash Flow computations, if needed, to ensure that information contained in the report is accurate and consistent with industry and business standards.

3. Most information on the business is based on “memory” rather than actual financial records
High possibility of biased information from the loan applicant - overstated income and understated expenses.
Why is there a need to review and test the information contained in the cash flow?
Most microenterprise operators normally do not keep records of their business transactions so that AOs have to rely on the verbal information supplied to them by the applicants during the CIBI.
Since loan applicants are biased data sources, two errors are usually committed when preparing the applicant’s cash flow – overstated income and understated expenses

4. (1) Price mark-up or Gross Profit Margin (2) Average Inventory
The income and expense data supplied by the client can be checked for consistency by reviewing:
(1) Price mark-up or Gross Profit Margin
(2)  Average Inventory
Total Monthly Business and Other Household Income
(4)  Total Monthly Household Expenses
(5)  Net Monthly Household Income
How then do we check for the consistency of information provided to the AO by the loan applicant? There are five ways by which consistency and accuracy of information in the cash flow can be tested. These five approaches need not all be applied to each and every loan application reviewed.
(read the bullets)
Let us discuss when and how of these five methods are used.

5. Price Mark-Up / Gross Profit Margin Analysis
The use of Price Mark-up is a way of testing the consistency/validity of sales information in the cash flow and is appropriate for businesses involved in the retail trade (e.g. sari-sari stores, dry goods, etc.)

6. Price Mark-up/Gross Profit Margin
Price mark-up or gross profit margin is computed using the formula:
Sales x 100
Cost of Purchases
Simply put, price mark-up refers to the “patong” , “tubô” or “ganansya” most microentrepreneurs apply to products sold by the business.
Two items are involved in the computation for the price mark-up, the Selling price/Sales (price at which an item is sold to the customer) and the Buying Price/Cost of Purchase (the price at which an item was bought from a supplier). The difference between the Selling price and the Buying price is what is known as the mark-up. The price mark-up actually represents how much the seller makes from the sale (minus the cost of the item).

7. Price Mark-up/Gross Profit Margin
The computed price mark-up or profit margin should not exceed the maximum standard rate set by the MFU for each type of enterprise
For example:
% price mark-up for sari-sari stores,
-25% for other retail shops,
-50% for carenderias and food processing activities
Different areas/regions often have different standards for price mark-up. The MFU will be able to establish the prevailing mark-ups by industry by looking at data of various types of businesses during CIBIs conducted in the past. Shown here are average price mark-ups of various industries which the bank may use as a starting point.
When testing the Sales data in the Cash Flow, computed price mark-up must not exceed the maximum standard rate established by the MFU (based on historical data for various businesses in the area as gathered during previous CIBIs) for each type of enterprise in the area.

8. Price Mark-up/Gross Profit Margin
If the computed mark-up exceeds the standard rate, the reported sales or income should be adjusted by using any acceptable rate and applying this on the cost of purchases.
Between using the reported sales or income and the cost of merchandise purchases, the latter would be easier to verify.
If the computed price mark-up (based on the sales data from the applicant’s cash flow) exceeds the standard rate, the reported sales or income should be adjusted by using any acceptable rate (established by the MFU) and applying this to the cost of purchases.
What would happen if the loan applicant’s price mark-up is higher or lower than the industry standard in the area? Here are two possibilities:
If Price Mark-up is higher than the industry. The applicant could end up with pricing himself out of the market. Meaning – prices of his/her product could be so expensive that customers will not patronize his business. This is especially true if the product the applicant is selling is also sold by competitors at lower prices. High price mark-ups only work if the business is the only source of that specific product (which means, the business can dictate the price) and buyers have no choice but buy from this lone product source; or, if the quality of the product really sets it apart from similar products and customers are more concerned with quality, rather than price.
If Price Mark-up is lower than the industry. If the applicant’s product is the lowest priced in the area, then customers would definitely flock to his business. What one should, however, watch out for is whether the business will be able to sustain its operations (overhead costs) considering the very small income they make from their sales.
Why use the cost of purchases as a basis for re-computing sales? Between using reported sales or income and the cost of merchandise purchases, the latter (purchases) would be easier to verify.

9. Example:
If a sari-sari store owner claims that his weekly sales is P20,000 and his weekly purchases is P15,000, his average price mark-up will be:
(P20,000 / P15,000) – 1 x 100 = 33.3%
If the normal price mark-up for sari-sari stores in the area is only within the range of 10-20%, the reported sales is too high.
To get a better understanding about how price mark-up rates affect sales in the cash flow, let us take a look at this example –
(show slide)
Adjust sales by assuming that the average mark-up, say, is only 15%. A more realistic weekly sales level, therefore, can be computed, as follows:
P15,000 x 1.15 = P17,250

10. Estimating the Average Price Mark-Up
The average price mark-up can also be estimated by comparing the buying and selling prices of, at least, the five (5) fastest selling items in the shop, through the formula:
Total Sales x 100
Total Purchases
Retail businesses usually involve multi-products, thus, computing for the price mark-up of each and every item in the inventory of a loan applicant would be tedious. To simplify things, we can simply compute for the AVERAGE Price Mark-up of the five of the fastest selling items in the business; the use of the fastest selling items in the business would more or less approximate the sales that the business experiences on a regular basis.
Where:
Total Sales = Selling price x Quantity of each item
Total Purchases = Buying price x Quantity of each item

11. Example: Average Current Buying Selling Total Total Price
stock Price Price Sales Purchases Mark-Up
Item A units , ,000
Item B units , ,500
Item C units , ,400
Item D units , ,500
Item E units , ______
Total 18, , ?
Let us take a look at a sample illustration of how the Average Price Mark-up is computed. In this illustration, we simply compute the Total Sales and Total Cost of Sales (cost of purchase) of the these 5 fast selling items. The Average Price Mark-up is thus computed using the TOTAL figures of these two earlier mentioned columns and applying them to the price mark-up formula. Therefore, in this example, the computed average price mark-up is 18.6%.
18, x 100 = 18.6%
15,300

12. Exercise: Question: Is there anything wrong with these data? Analysis:
Type of Business: Sari-sari store
Daily sales: ,500
Weekly Purchases: ,000
Analysis:
Weekly equivalent of daily sales = 1,500 x 7 days
= 10,500
Weekly Purchases = 9,000
Price mark-up = (10,500/9,000) - 1 x 100
= ( ) x 100
= 16.7%
Let us test our understanding of price mark-up.
(Show the slide)
Here we have sales and purchase data of a sari-sari store. (show next bullet). Let’s compute for the price mark-up. You will notice that the sales data is for daily sales, while purchase data is for weekly purchases – in other words, you have financial data of different time frames. We must first convert the daily sales data to its weekly equivalent before we can transpose these figures into the price mark-up formula.
Based on the computation, price mark-up was computed at 16.7%.
(Ask the trainees)
Is this price mark-up acceptable or not? (get responses and explanation of trainees before showing the CONCLUSION bullet)
Conclusion: This price mark-up is acceptable

13. Exercise: Question: Is there anything wrong with these data? Analysis:
Type of Business: Sari-sari store
Daily sales: ,500
Weekly Purchases: ,000
Merchandise Inventory (AO’s estimate): 1,000
Analysis:
Merchandise Inventory: ,000
Daily Sales: 1,500
Derived Cost of Purchase: (1,500/1.15) = 1,304
which means that the
ending inventory cannot
support even one day of
sales
Let’s take a look at another example –
(show slide)
We once again have data on the operations of a sari-sari store. This time, however, we have data on the AO’s estimate of merchandise inventory. Since the AO’s estimate on inventory level is based on an actual site validation, this figure should be considered in our validation. In the analysis show in this slide it is apparent that if we apply the price mark-up for sari-sari stores of 15%, this applicant would need to have P1,304 worth of goods if a sales level of P1,500/day is to be attained. In effect, the present inventory level of P1,000 cannot support even one day of sales.
(Ask the trainees) What is your conclusion from the data and the analysis we just did? (get feedback and explanations from trainees before showing CONCLUSION bullet)
Conclusion: Data on sales & purchases are doubtful

14. What to do -- Check sales receipts or records, if any; or
Check receipts or records of purchases, if any; or
Verify level of regular purchases with client’s suppliers; or
Estimate a more realistic level of sales and purchases based on the client’s average inventory level
If the computed data for sales and purchases in the cash flow appear doubtful, you may request to see the following documents for verification (read each bullet)

15. Average Inventory Analysis
Let us now go into the 2nd method for validating the accuracy and consistency of data provided by the applicant as inputs in the preparation of the Cash Flow Analysis – the Average Inventory Analysis method.

16. Average Inventory
Average inventory, is the total value of stocks usually maintained by the business. Small retail shops usually maintain an inventory equal to 2-4 weeks of regular daily or weekly sales.
(Read the definition in the slide). The Average Inventory method is best suited for evaluation of retail/trading businesses that have clearly established inventory patterns and levels.

17. Average Inventory
The AO should compare the reported average inventory with the total value of the stocks of the shop when he/she visits the business during the CI/BI.
If the discrepancy between the total value of the observed inventory and that of the reported inventory is large, the AO should verify reason for discrepancy from the client.
If the client cannot provide adequate explanation for the discrepancy, the AO should use whichever amount is lower to represent the applicant’ average business inventory.
What are the steps that an AO should take to validate information provided by the applicant during the CIBI on the level of business activity of the business – the amount of inventory a business usually carries provides a good benchmark for establishing the volume of transactions/sales that the business experiences.
(Show and read each of the bullets)

18. Average Inventory
For trading-related activities, such as retail shops, the ending inventory should be compared with the average inventory. The ending inventory should always be equal to, or greater than, the average inventory.
If the ending inventory is lower than the average inventory, the COST OF SALES should be adjusted downwards using the difference between the average inventory and the ending inventory.
We have just shown you the steps an AO goes through to validate the accuracy and consistency of sales and purchase information provided by the applicant. If at the end of the validation process it is established that the actual inventory (as verified by ocular inspection by the AO) is in fact lower than the average inventory data (as supplied by the applicant), the COST OF SALES should be adjusted downward. Once COST OF SALES is adjusted, it follows that the figures for GROSS SALES/SALES will likewise be affected.

19. (1 + Normal Price Mark-up)
Adjusting SALES
Steps
Formula 1
Cost of Sales
Reported Sales
(1 + Normal Price Mark-up) 2
Adjusted Cost of Sales
Plus : Ending Inventory minus
Minus : Average Inventory 3
Adjusted SALES
Multiply by : (1 + Normal Price Mark-up)
This slide shows you the steps that have to be taken to adjust COST OF SALES (and eventually, SALES), if validation of the inventory level of the applicant’s business proves to be lower than the information provided by the applicant during the CIBI.

20. Example Analysis Step 1: COST OF SALES = P1,500 x 7days (1 + 0.167)
Type of Business: Sari-sari store
Daily Sales: P 1,500
Total Weekly Purchases: P 9,000
Merchandise Inventory (AO’s estimate): P 1,000
Average Inventory (Client’s estimate): P 5,000
Analysis
Step 1:
COST OF SALES = P1,500 x 7days
( )
= ,997
Step 2:
ADJUSTED COST = ,997 + (1, ,000)
OF SALES ,997
Through an example, let us go through the process of validating the Inventory level of a sari-sari store business. Let us assume that the Price Mark-up of this business is 16.7%.
This means that the cost of sales of P9,000 should be reduced to P4,997.

21. Step 3:
Adjusted Sales = Adjusted Cost of Sales
x (1 + Normal price mark-up)
Adjusted Sales = 4,997 x ( )
= 4,997 x 1.167
= 5,831
This means that the reported sales of P1,500 per day or P10,500 per week should be reduced to only P5,831 per week, or P833 per day.
Based on the validation, it was established that the level of purchase reported by the applicant was over-stated. If we are to apply the price mark-up of 16.7% to the adjusted COST OF SALES, it will be noted that the daily sales would only be P833 (an almost 50% drop from the reported daily sales of P1,500).

22. *As claimed by the client ** As estimated by the AO
These adjustments are necessary in order to make the average inventory consistent with the average sales and purchases of the business, as shown in the table below.
Before
After
Adjustments
Average Inventory, Beginning
5,000*
5,000
Add: Purchases
9,000
4,997
Less: Cost of Sales
8,997
Equals: Average Inventory, Ending
1,000** (?)
1,000
*As claimed by the client
** As estimated by the AO
Read the slide

23. NOTE : Do the average inventory analysis only if the total value of the inventory is substantially lower than the total cost of purchases reported by the client.
However, if the difference between the observed inventory and the cost of purchases is not large, the price mark-up or gross profit margin analysis would suffice.
The Average Inventory Analysis is to be used ONLY IF THE TOTAL VALUE OF THE INVENTORY IS SUBSTANTIALLY LOWER THAN THE TOTAL COST OF PURCHASES REPORTED BY THE CLIENT.

24. Analysis of Total Monthly Business and Household Income
Let us now take a look at the 3rd approach to testing the consistency and validity of sales and expense information provided by the client.

25. Total Monthly Income from Business and Other Sources
Item
Daily
Weekly
Semi-Monthly
Monthly
MONTHLY TOTALS
Total Business Income:
Total Business Income
Business Expenses:
Total Business Expense
NET BUSINESS INCOME
Total Other Household Income
TOTAL BUSINESS & HOUSEHOLD INCOME
Analyze data here
The 3rd approach to validating cash flow information is the analysis of the TOTAL MONTHLY INCOME FROM BUSINESS AND OTHER SOURCES. This involves analysis of the Monthly Total column in the cash flow involving TOTAL BUSINESS & HOUSEHOLD INCOME. (show the Cash flow format and point out to the trainees the specific column/line to use in the analysis).
What is the importance of this data in the validation process? (Show the next slide)

26. Total Monthly Income from Business and Other Sources
This income represents the regular monthly income of the household before household expenses.
It is, thus, comparable to the monthly salaries received by the AOs (or other employees), in the sense that both are incomes before household expenses.
Read the bullets

27. Total Monthly Income from Business and Other Sources
The AO can verify whether the estimated total monthly household income of the applicant, as shown in the cash flow, is consistent with the living condition of the applicant and his family when he/she visit the borrower’s house during the CIBI.
The AO may compare the applicant’s house and living condition with that of his own, or those of other persons whom he/she knows belong to the same income bracket as that of the applicant.
Read the bullets

28. Total Monthly Income from Business and Other Sources
NOTE : If the estimated total monthly business & household income is not consistent with the living condition of the household, the AO must revise the cash flow. Loan applicants tend to overstate their incomes.

29. Example
Total Monthly Income from Business
& Other Household Sources: P25,000
Analysis
Compare the P25,000 total monthly income (before HH expenses) with the following items:
No. of HH members 4
Household appliances None
House construction materials Temporary
Conclusion: The income data is doubtful. A household with only 4 HH members and receiving a monthly “salary” of P25,000 normally would be owning at least some small HH assets, or is residing in a house made of more durable materials. AO should further verify the discrepancy between the reported HH income & the observed living condition of the HH.
As an example – let us take a look at the following information (show the slide and the first two bullets – do not show the conclusion first)
(Solicit analyses from the trainees on the information provided in the example. After having solicited at least 3-4 reactions, show the CONCLUSION bullet).

30. ANALYSIS OF TOTAL MONTHLY HOUSEHOLD EXPENSES
The 4th approach to cash flow validation is the analysis of the TOTAL MONTHLY HOUSEHOLD EXPENSES.

31. Total Monthly Household Expenses
Item
Daily
Weekly
Semi-Monthly
Monthly
MONTHLY TOTALS
Other Household Income
Remittances
Total Other Household Income
Total Business & Household Income
Household Expenses
Food
Education & School Allowance
Utilities (Light & Water)
Sub-Total
Miscellaneous (10%)
Total Household Expenses
Analyze data here
We now analyze the data shown under the Monthly Totals column for TOTAL HOUSEHOLD EXPENSES. What information should we expect to get by looking at this particular figure in the Cash Flow?
(Show next slide)

32. Total Monthly Household Expenses
The total monthly household expense should be compared with the size of the household and the ages of household members.
The AO should be familiar with the major expenditure items of households in his/her area of assignment and the most common level of expenditures for each item.
For greater conservatism, add at least 10% to the total household expenses as miscellaneous expenses.
Read each bullet

33. Example
Total Monthly Household Expenses: P2,000
Analysis
Compare the P2,000 total monthly expenses with the following items:
Type of client’s business Sari-sari store
No. of HH members 5
Ages of HH members (children) 1 HS, 1 college, 1
grade school
Community where client is residing Urban
Let us use an example to analyze how the information on the TOTAL MONTHLY HOUSEHOLD EXPENSES relate to other information provided by the client during the CIBI –
(Show the EXAMPLE and ANALYSIS bullets. Solicit reactions/analysis from at least 3-4 trainees; establish a consensus on analysis among the participants. Show the CONCLUSION bullet only after most of the participants have given their assessment of the information in the slide).
Conclusion: The expense data appear too small for the household described above. AO should gather more information on the applicant’s HH expenditures and adjust these, if necessary.

34. ANALYSIS OF NET MONTHLY HOUSEHOLD INCOME

35. Net Monthly Household Income
Compute for this data using the Monthly Totals column in the Cash Flow
Formula:
Total Other Household Income
less : Total Household Expense
equals :NET HOUSEHOLD INCOME
The data we are referring to in this validation approach refers to income and expenses from sources other than the business. The NET HOUSEHOLD INCOME is derived by simply deducting Total Household Expense from Total Other Household Income.
What information does this information provide us? (show the next slide)

36. Net Monthly Household Income
The Net Monthly Household Income also represents the monthly savings of the household or the size of its investment funds.
This amount should be checked against the relevant items in the applicant’s balance sheet --i.e. savings deposit, cash on hand, real properties, other household assets, and other investments.
Read the bullets

37. If the amount appears large compared with the amount the applicant intends to borrow, verify from the client the reason why he/she still intends to borrow.
If the applicant cannot provide an adequate explanation for the apparent discrepancy, the AO should review the cash flow and make the necessary adjustments in the applicant’s income and expense data.
Read the bullets

38. Example
Total Net Monthly HH Income: P10,000
Analysis
Compare the P10,000 net monthly income with the following items:
Savings/cash in bank None
Cash on hand P500
Real properties None
Household appliances P10,000
Business assets P10,000
Total Assets P40,000
To get a clearer understanding of the added insight provided by an analysis of the NET MONTHLY HOUSEHOLD INCOME, let us analyze the information provided in this example –
Based on the information provided in this slide, what conclusions can we draw with respect to the validity of the NET MONTHLY HOUSEHOLD INCOME of P10,000? (Solicit for answers from the participants. Show the CONCLUSION bullet only after 3-4 responses have been given by the participants).
Conclusion: The income data is doubtful. It is not clear where the P10,000 net monthly income or “savings” is kept or invested by the applicant. AO should further verify the applicant’s income and expense data.

39. Example
Total Net Monthly HH Income: P3,000
Analysis
Compare the P3,000 net monthly income with the following items:
Savings/cash in bank None
Cash on hand P500
Real properties P300,000
Household appliances P100,000
Business assets P10,000
Total Assets P500,000
Total liabilities None
Conclusion: The income data is doubtful. Monthly net income is too small compared with the HH’s assets. This HH most likely had acquired all these assets from borrowings. AOs should further verify the liabilities of the HH.

40. ANALYSIS OF MONTHLY HOUSEHOLD INCOME STRUCTURE
The last approach that we can use to validate the information in the Cash Flow is the review / ANALYSIS OF MONTHLY HOUSEHOLD INCOME STRUCTURE.

41. Monthly Household Income Structure
This refers to the ratio of the NET BUSINESS INCOME to the TOTAL BUSINESS & HH INCOME The ratio is computed as follows:
Net Business Income x 100
Total Business & HH Income
Read bullet

42. Net Income from Business should be at least 80% of the total household income.
If Other Household Income is more than 20% of the Total Business & HH Income, the AO should gather proof of this income (e.g. pay slip of spouse’s salary).
If Other HH Income is more than 50% of the Total Business & HH Income – that is, most of the HH income come from outside the client’s business, offer the client other loan products of the banks (e.g. salary loan)
By reviewing the ratio of NET BUSINESS INCOME to the NET BUSINESS & HOUSEHOLD INCOME we are trying to establish which cash flow source provides the biggest share of funds entering the household – is it the business or other household fund sources?
Based on the computed ratio, we can deduce the following: (read each bullet)

43. Other HH Income (Spouse’s salary) 4,000
Example
Net Business Income 10,000
Other HH Income (Spouse’s salary) 4,000
Total Business & HH Income 14,000
Analysis
Net Business Income %
Other HH Income (Spouse’s salary) 29.6%
Total Business & HH Income %
Here are some examples for us to analyze. With the above computed ratios, what action should the AO take to validate the accuracy of information? (Solicit answers from the participants before showing the RECOMMENDATION bullet).
Recommendation: AO should present proof of the spouse’s salary (pay slip)

44. Other HH Income (Spouse’s salary) 10,000
Example
Net Business Income 4,000
Other HH Income (Spouse’s salary) 10,000
Total Business & HH Income 14,000
Analysis
Net Business Income %
Other HH Income (Spouse’s salary) 71.4%
Total Business & HH Income %
In this example, what steps would you recommend that the AO take to validate the information in the Cash Flow? (Solicit answers from the participants before showing the RECOMMENDATION bullet)
Recommendation: Client’s spouse should be offered a salary loan instead.

45. Exercise
Review and make adjustments to the Jennifer Delima Case Problem that was done in the previous session.