Auditing and Assurance Services

Table of Contents
Meet the Audit Team 3
Partner Summary 5
Introduction 6
Part 1.1 a) Advanced Analytics in Professional Standards 6
Part 1.1 b) Academic Research on Advanced Analytical 6
Part 1.3 Simple Trend-line Regression 7
Part 2.1 Specific Risk of Material Misstatement 11
Part 2.2 An Appropriate Audit Program 12
Appendix 15
References 16
List of Key Audlish terms 17

Partner Summary
In order to better understand the audit reports, we have documented academic research and existing audit standards relevant to planning stage APRs. This background information will provide a summary of professional standards and guidance directly related to APRs.
First and foremost, every auditor must follow the standards called the Generally Accepted Auditing Standards (GAAS) which are set by the Public Company Accounting Oversight Board (PCAOB). Important sections within the standards required to know include: Independence, Consideration of Fraud in a Financial Statement Audit, and Communications about Control Deficiencies in Financial Statements, which includes nine rules that deal with identifying and reporting deficiencies found in financial statements.
In the second part of our report, we prepared basic ARP’s and identified some key red flags for the Chevron Company. To access client viability, we used vertical and horizontal analysis, where we found information to create concern about their financial strength. We also looked at other factors such as forecast cash flow for next year, ratios, operating losses, and previous audit fees to conclude whether or not Chevron has financial stability.
Three key red flags we found that the audit team should be aware of are: the correctness of valuation when it pertains to recording revenue, Chevron’s ability to pay dividends, and is the selling / administration expenses section of the income statement.

Introduction
The purpose of this report is to introduce into simple and multiple regression analysis and to explain how important these methods for the auditors are. The preparation of the report includes all necessary audit standards and explanations about their meaning and importance.
PART 1
Part 1.1 a) Advanced Analytics in Professional Standards
According to auditing standards, an ARP is governed largely by its relative “effectiveness”. Effectiveness refers to an ARP’s ability to detect material errors and irregularities. However, for ARPs which are equally effective, “efficiency” becomes the dominant attribute. AU 320.72 notes that the auditor’s consideration of effectiveness and efficiency is contingent on the “availability and stability of experience or other criteria for use in analytical review procedures” SAS No.56 provides detailed guidance on using analytical procedures as substantive tests and requires their use both the planning and final review stages of all audits (Knechel,1988, p.74-95).
b) Academic Research on Advanced Analytical
(1) The study conducted by Wheeler, Stephen and Pany, Kurt in their paper - Assessing the Performance of Analytical Procedures: A Best Case Scenario extends the existing research on the audit effectiveness of analytical procedures in a setting that used actual accounting data seeded with "material" simulated accounting errors. Five sample companies, whose revenues represented a wide range of time-series behavior, were selected to analyze the effects of eight commonly encountered accounting errors on 15 often-used analytical procedures (eight ratios and seven accounts). The best predicting of six candidate models (four naive, a regression, and the Census X-11 time-series model) was used to generate quarterly predictions for comparison with actual data seeded with the largest of four empirically based materiality measures (Wheeler & Pany, 1990, p.557-577).
(2) In Knechel’s paper called The Effectiveness of Statistical Analytical Review as a Substantive Auditing Procedure: A Simulation Analysis, he assesses via simulation the effectiveness of various analytical review procedures when used in combination with a partitioned approach to dollar unit sampling for tests of account details. There were three major findings in this study. First, regression based analytical review increased audit effectiveness relative to an audit strategy that did not use analytical review. Second, the use of monthly data greatly increased the effectiveness of analytical review. Finally, regression based analytical review models were very efficient in detecting potentially material misstatements (Knechel, 1988, p.74-95).
(3) The research by Mock, Biggs, and Watkins in their paper “Auditor's Use of Analytical Review in Audit Program Design” presents some descriptive evidence of how auditors perform analytical review in a complex and realistic task setting. Specifically, the research investigates how auditors who differ in terms of experience, design and conduct analytical review and revise audit programs in light of their analytical review judgments. To accomplish this purpose, a comprehensive case was administered to four auditors who performed the task while thinking aloud. The results show that both managers and seniors identified the crucial audit problems embedded in the case. (Biggs, Mock & Watkins, 1988, p.148-161)
Part 1.3 Simple Trend-line Regression
During the preparation of the substantive tests for the revenue process of the customer „Chevron“, we decided to provide our own calculation process with the simple regression analysis. Simple regression shows the relation between selected values which are visible in on the x-axis and observed values which are on the y-axis. The purpose is to analyze a possible dependence on the selected and observed data. We used two types of data to compare which one is more efficient. Firstly, we selected previous revenue amounts for quarterly data for the fiscal years (FY) 2009 until 2012 as follows (Figure: 1&2):
We received a trend line formula which is mentioned in the second graph (Figure 2). Due to this formula we found out that the standard error is 5,076. The exactly table is visible in the attachment documents. We used this information and calculated the first forecast for the fiscal year 2013. In comparison to the revenue data we received from our customer, there are too many differences available which is visible in the calculation table below (Figure 3): Figure 3: Comparison of the auditor´s calculation and the company’s result (FY 2009-2012)
The Difference is bigger than the St. Error, so that the calculation is not exactly enough. The reason could be the environmental, political and technical changes during the last years, which is not considered within our calculation. Therefore we performed a second simple regression analysis in consideration of the quarterly data from the last two years. The procedure is visible in the charts below (Figure 4&5): Figure 4: Revenue for FY 2011 and 2012 Figure 5: Trend line for FY 2011 and 2012
We received a trend line formula which is mentioned in the above graph (Figure 5). Due to this formula we found out that the standard error is 3,186. The exactly table is visible in the attachment documents. We used this information and calculated the first forecast for the fiscal year 2013. Figure 6: Comparison of the auditor´s calculation and the company’s result (FY 2011-2012)
All differences are acceptable and explained with the standard error that is mentioned in the table above (Figure 6).
In comparison to the different periods of time you see that the differences of our audit calculation to the revenue of our customer of 2013 are smaller when we only look on a smaller amount of time then a period of 4 years. This is also stated by the St. Error, where the aberration is smaller in our comparison with 2 years. A possible explanation for these differences could be that there are changes, as already mentioned, around or in the company. These changes affect a company and its operations differently during changing time periods. Changes could depend on environmental, political or technical development effects. By using more data there are more average errors possible which affects the results and the St. Error. The latest data, like the data in our second calculation example does not include too many changes because there is not enough time distance between the FY and quarters available.
Simple regression analysis
The following part describes, how the revenues change regarding to the quarters and describes the basic values of a regression analysis.
R-square: Describes the total spread in percentage. The normal variation is between 0 and 1.0. The smaller the value the more likely the case differs from the lineal correlation. In our case the value of r-square in the comparison of 4 years is 0,706. This high value is good because it describes that the spread is really close to the lineal graph of the regression analysis. In comparison with the graph that describes the 2 years the r-square value is 0,246. This value is too low, because this case differs more from the lineal relationship, meaning the spread of values is really high. Therefore this is not a reliable forecast, because we need more data for significant results. This result does not change the fact that we have more exact data considering other aspects like the St. Error.
F: R-square and corrected r-square - tests overall significance of the regression model. They test the zero hypotheses that all the regressions coefficients are equaled to zero. The F-value is the ratio of the mean regression sum of squares divided by the mean error sum of squares. Its value can range from zero to a very large number.
Sign-F: The probability that the hypothesis for the full model is true. As an example if the sign F value is 0,01 then there is one chance in a hundred that all of the regression parameters are zero.
T stat: The t-statistic is calculated by dividing the estimated value of the parameter by its standard error. This statistic is a measure of the likelihood that the actual value the parameter is not zero. The larger the value of t the less likely it is that the actual value of the parameter could be zero.
P-value: Is the probability of obtaining the estimated value of the parameter if the actual parameter value is zero. The smaller the value the more significant are the results. When we look at the calculation of 4 years, and the rising quarters, the revenues rise at 1,597. The p-value is 0,000, which is significantly high meaning a revenue rise throughout the years. In the 2 years calculation, the revenues decrease in the different quarters at -0,688, but the p-value in this chart is 0,211, which is a very high value meaning this calculation is not significant.
Explanation of the results
The first analysis shows a St. Error which is bigger than in the second one. This could depend on the higher spread. It also concerns the independent and different values of Intercept/FY Q. If you only consider the figure Intercept/FY Q in our first analysis where the coefficient for FY Q is 1,597 it is visible that it increases to 1,597 in consideration of further data. This value is significant because the p-value is 0,000. In our second analysis only the r-square has a good value so that there is a linear dependence available, but in comparison to the other data, which are not significant we can conclude that this good r-square value relates to the small amount of used data. In comparison to the client´s data, we found out that the second analysis which only considered 2 FY is the best one because of the already above mentioned factors if environmental influences and the economic situation. A significant statement to prove our decision states also the revenue differences, which are really low in the 2 year comparison.
The described and analyzed data can be reviewed in the appendix [Figures 6&7].
PART 2
Part 2.1 Specific Risk of Material Misstatement
The Correctness of Revenue and Accounts Receivable
From our previous basic analytical review, one possible material misstatement we realized is whether the recording of sales revenue and accounts receivable are correct and accurate because of continuous fluctuations between years. After conducting simple regression on revenue from 2009 to 2012 (Figure 2), we can further investigate some significant differences in revenue which mostly are overstatement of account balances. For example, the biggest difference in revenue occurs in the second quarter of 2011, which is $8,607,000 higher than the previous quarter. The second significant difference is $6,420,000 which was happened in the third quarter of 2009. Although management assertions are quite reliable, according to auditing experiences, sometimes assertions may not be supported by enough evidence, such as existence and valuation. Existence refers to that accounts receivables exist at the balance sheet date. Valuation is that accounts receivable are valued correctly according to GAAP rules at year end (Stuart, 2012, p.98). One possible reason for Chevron’s overstatement might be early revenue recognition. For example, Chevron might record early revenues from long-term construction contract of oil refining facilities which is supposed to be received after the completion of the construction. Early revenue recognition will result in overstatement of accounts receivable, which is conflict with management assertions of valuation because the company fails to comply with GAAP in recording accounts receivable. Another reason for overstatement might be fluctuations in prices for crude oil that can cause discrepancies when comparing sales revenue to cost of goods sold. Changes in crude oil price makes Chevron difficult record and calculate inventory timely and correctly, so mistakes will be made in recording cost of goods sold with wrong oil prices. In addition, simple regression also shows understatement of account balances. According to management assertions, managers assert that the cut off for sales revenue was in accordance with GAAP (Stuart, 2012, p.98). However, one greatest understatement might be material misstatement, which occurs in the third quarter of 2012 with $4,564,000 lower than the previous quarter. Sharp decrease in revenue may indicate that Chevron recognizes revenue at the end of the year based on invoice date rather than shipping date. By doing so, it can understate revenue and avoid excess tax payments by limiting the taxable income in a certain tax bracket. There might be other reasons for overstatement and understatement which are hard to control and beyond our prediction, such as political issues, economic environment and changes in policies.
Part 2.2 An Appropriate Audit Program
Accounts receivable represents the money owed to the company by client and consumers. In general, auditors typically follow substantive audit procedures to test the balances of accounts receivable accounts. Substantive audit procedures are direct tests by using specific information from the company’s accounting system and financial statements.
Before the substantive testing, there are some things will need: (1) General ledger. (2) Accounts receivable summary. (3) Invoices and cash receipts. 1. Obtain a detailed listing of all accounts receivable balances. Before the procedures start, make sure auditors have all the records, receipts and reports, preferably sorted in the order of the age of receivables.
2. Reconcile the general ledger with the accounts receivable summary report. Compare the entries in the period-end aging accounts receivable report with the general ledger. And also compare the totals in the summary report with totals from the edger. Matching totals will flag any inconsistencies between the two entry files (Kiran, “How to audit accounts receivable”).
3. Grouping accounts by their thematic characteristics will improve the efficiency of ensure, thus identify groups within the accounts receivable population. It could be classified as following groups: (1) significant balances (accounts with significant balances) (2) related party accounts (when the policy of one entity can influence the other, then a related party transaction occurs) (3) unusual accounts (accounts with characteristics like accounts regularly past due dates, an unusual customer name or accounts prone to misstatements) (Kiran, “How to audit accounts receivable”).
4. Select sample. (1) Choose a sample of sales recorded in the sales journals .Check whether the sales invoices and shipping documents gives support to the sales records in the sales accounts. (2) Choose a sample of shipping document for the year. Compare the shipping document to the sales invoice and the sales journal; make sure all the shipping documents have been recorded as sales. (Stuart, 2012, p.105)
5. Confirmation. (1) Positively confirm selected accounts. If the auditor has identified the ledger entries that reconcile with the entries in the summary report, or identified inconsistencies, mark them for confirmation. Send letters of confirmation to management, requesting and explanation for inconsistent accounts. (2) Test accounts where there is no confirmation. Reconcile the accounts for which status cannot be confirmed with the summary report with other documentation, invoices, sales orders, shipping logs and deposit slips should be all included. Send letters again requesting explanations where warranted after making a confirmation.(Stuart, 2012, p.106)
6. Perform sales cutoff tests. (1) Trace sales journal (2) shipping document for 5 to 10 days before and after year-end to check whether they were recorded in the correct time period. (Stuart, 2012, p.106)
7. Assess allowance for doubtful accounts. Additional funds from sales, set aside in order to pay off estimated bad debt are called allowance for doubtful accounts. Review the amount estimated as non-collectible. Determine whether the estimate is consistent with prior years, reasonable for the business and in conformity with the accounting policy.
8. Review bad debt write-offs. Examine the amount and volume of bad debt then compare it with the bad debt from the previous year. Determine whether the reconciliation of the write-offs with the related documentation is properly justified.
9. Check the sales entry. Using samples from the account population, determine whether sales invoices are recorded correctly; also consider whether the credits are accounted for the returned goods.
10. Examine whether the uncollectible accounts are written off by using a timely basis.
N.E.T.S Factor In auditing, NET means nature extent and timing of future audit procedures. To be more precise, it is important for the auditor to aware what is likely to go wrong in a process and thus to plan the audit and consider the nature of the evidence: whether to use internal control testing or substantive .The timing of the evidence collection means before or at year end. What is more, the extent of the evidence to be gathered shows that what is the amount of testing needed. In this case, when talking about the substantive testing of accounts receivable, the audit program will specify focus on nature. From the audit procedures have been discussed, know that all these procedures are part of key substantive tests. Procedure 4 tests the assertion of existence, completeness, and accuracy. Procedure 5 test about existence, rights. Procedure 6 more concerned about cutoff. And procedure 8 is the test of completeness and accuracy, while procedure 10 focuses on valuation. To make this substantive testing more assuring, extent should be consider as well. Like procedure 6 perform cutoff test, there is a time limit and should record in the correct time period. And from procedure 10 can learn that there is also a requirement that should be recorded on a timely basis.
Conclusion
Our financial analysis with the use of two regression forms (single and multiple) allows us to decide that Chevron has a good preparation of its revenue development. In consideration of environmental influences and the St Error, the numbers are not only well prepared but also correct.

Appendix

Figure 7: Summary Output for the FY 2009-2012

Figure 8: Summary Output for the FY 2011-2012

References
Literstur
Bharthapudi, Kiran. (n.d). How to Audit Accounts Receivable. ehow. Retrieved May 3, 2014, from ehow: http://www.ehow.com/how_10065104_audit-accounts-receivable.html
Biggs, Stanley F., Mock, Theodore J., & Watkins, Paul R. (Jan, 1988). Auditor's Use of Analytical Review in Audit Program Design. The Accounting Review. Vol.63. No.1.
Knechel, W. Robert. (Jan, 1988). The Effectiveness of Statistical Analytical Review as a Substantive Auditing Procedure: A Simulation Analysis. The Accounting Review. Vol.63, No.1.
Stuart, Iris.C. (2012). Auditing and Assurance Services: An Applied Approach. New York, NY: McGraw-Hill.
Wheeler, Stephen.,& Pany, Kurt. (Jul, 1990). Assessing the Performance of Analytical Procedures: A Best Case Scenario. The Accounting Review. Vol.65. No. 3
Websites
http://www.chevron.com/documents/pdf/annualreport/Chevron2010AnnualReport_full.pdf ; opened on 04/30/2014 at 1 p.m. http://www.thefreedictionary.com/simple+regression; opened on 05/01/2014 at 10:16 a.m. http://www.chevron.com/annualreport/2012/documents/pdf/Chevron2012AnnualReport.pdf, o pened on 04/30/2014 at 1 p.m. http://www.chevron.com/documents/pdf/annualreport/Chevron2011AnnualReport_full.pdf, opened on 04/30/2014 at 1 p.m.

List of Key Audlish Words:
1. Analytical Review Procedure: A comparison of financial statement amounts with an auditor's expectation.
2. Misstatement: Is a difference between the amounts, classification, presentation, or disclosure of a reported financial statement item and the amount, classification, presentation, or disclosure that is required for the item to be in accordance with the applicable financial reporting framework.
3. N.E.T.: is nature, extent, and timing of audit procedures.
4. Substantive Audit Procedure is a direct test of a financial statement balance designed to detect material misstatements at the assertion level. Substantive procedures comprise tests of details (classes of transactions, account balances, and disclosures), and substantive analytical procedures.
5. Assertion: Management asserts financial statements are correct with regard to existence or occurrence of assets, liabilities or transactions, completeness of information in the financial statements, rights and obligations at a point in time, appropriate valuation or allocation, presentation, and disclosure.
6. Valuation: An assertion made by management that each asset and liability is recorded at an appropriate carrying value.
7. Material: Information important enough to change an investor's decision. Insignificant information has no effect on decisions, so there is no need to report it. Materiality includes the absolute value and relationship of an amount to other information.
8. Audit program: An audit program is a listing of audit procedures to be performed in completing the audit. A computer program (software) is a listing of steps to be performed in processing the data.
9. Substantive Audit Procedure: a direct test of a financial statement balance designed to detect material misstatements at the assertion level. Substantive procedures comprise tests of details (classes of transactions, account balances, and disclosures), and substantive analytical procedures.
10. Extend: multiply one number by another (to test extensions is to test the accuracy of multiplication done by the client). To extend audit procedures is to apply additional audit procedures to obtain more evidence.
11. Nature of audit testing: the type of testing, such as tests of internal controls, tests of transactions, or tests of balances in balance sheet accounts.
12. Timing of audit testing: when the procedure is performed. If you perform a test of balances procedure before year end there is a risk that internal controls are inadequate to provide assurance up through the balance sheet date. There is less risk if you do the procedure as of the balance sheet date.
13. Cutoff: Designating a point of termination. An auditor uses tests of cutoff to obtain evidence that transactions for each year are included in the financial statements of the appropriate year.

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[ 1 ]. Ref.: http://www.thefreedictionary.com/simple+regression; opened on 05/01/2014 at 10:16 a.m.
[ 2 ]. Ref.: http://www.chevron.com/annualreport/2012/documents/pdf/Chevron2012AnnualReport.pdf, http://www.chevron.com/documents/pdf/annualreport/Chevron2011AnnualReport_full.pdf, http://www.chevron.com/documents/pdf/annualreport/Chevron2010AnnualReport_full.pdf ; opened on 04/30/2014 at 1 p.m.