FRAUD RISK ASSESSMENTS OF FORENSIC UNITS

1. 
   What is meant by a predictor variable and what is the equivalent concept called in linear regression?
   
2. 
   What is meant by continuous controls monitoring?
   
3. 
   Briefly describe the risk-score approach or the risk-scoring methodology.
   
4. 
   What problems would arise from having or using predictors that were not valid? For example, where a sales reporting application included a predictor (such as whether the zip code was an odd or an even number) that really had nothing to do with the behavior of interest.
   
5. 
   In what circumstances does the risk scoring methodology work best?
   

6. 
   In the steps used to develop a continuous monitoring application, the system design step occurs before the system documentation step (true/false).
   
7. 
   A final forensic unit of 0 is associated with a low risk of errors, and a final forensic unit of 1 is associated with a high risk of errors (true/false).
   
8. 
   Slovic (1966) notes that little is known about the manner in which human subjects combine information from multiple ______ (views/news/cues).
   
9. 
   Sales reporting errors can be either intentional or unintentional (true/false).
   
10. 
    If a risk scoring system was developed in which the predictors had no predictive ability, then the system would be no worse or better than a random selection of forensic units (true/false).
    

1. 
   The PWC study concluded that continuous auditing is still considered to be a(n) ________ phenomenon.
   

f.Emerging

g.Successful

h.Mature

a.Length

c.Scope

53.A risk score is calculated for each _______ unit.

a.Measurement

b.Inventory

c.Seasonal

d.Forensic

54.The risk score method uses multiple ______ to assess the risk of fraud or error.

a.Predictors

b.Queries

c.Reports

d.Correlations

55.The risk scoring system is a fraud _______ activity.

a.Correction

b.Perfection

c.Prevention

d.Detection

1. 
   Create a predictor P1 that scores each forensic unit with a 1.00 if the state has a newly formed county, and zero otherwise (similar to the P8 variable in the chapter, although P8 had three possible values, not just 0 or 1). A newly formed county would occur when there is a 0 value for the 2000 census and a positive count for the 2010 census.
   
2. 
   Create a predictor P2 that gives each state a score of .1 (with a maximum of 1.00) for each number in either 2000 or 2010 that is an exact multiple of a 100 (e.g., 400, 900, 2,000, or 3600). A state with 4 "round numbers" should score 0.40 for P2 and a state with no round numbers should score 0.00.
   
3. 
   Create a predictor P3 that first calculates the proportion of counties in a state that had population increases of 10 percent or more. The P3 score is equal to the proportion times 3 (with a maximum score of 1.00). Counties with zero populations in 2000 should be scored as if their percentage increase is greater than 10 percent.
   
4. 
   Calculate the final risk scores for each state by giving P1 a weight of 0.10, P2 a weight of 0.30, and P3 a weight of 0.60. Round and display the scores to three decimal places. Sort the results by risk scores decreasing. Export the results to Excel. Save the Census.accdb file.
   

1. 
   Create a neat Access report that shows only the P3 results. The report should show the state name, the two letter state abbreviation, and the P3 score. The result should be sorted by P3 score descending. The data sets for this book include a table of state names and the two letter abbreviations.
   
2. 
   Create an Access report that shows the final risk scores for each state sorted by risk scores descending. The report should show the final scores, the scores for P1 to P3, the state name, and the two letter abbreviation.
   
3. 
   Create a switchboard so that the reports created in (a) and (b) can be displayed with a single click. A switchboard is shown in Figure 15.8.
   

1. 
   Why has the IRS stopped performing the TCMP audits?
   
2. 
   Once the TCMP data table has been completed, the IRS uses discriminant analysis to select returns for audit. What is discriminant analysis?
   
3. 
   Does the DIF system include a message of some sort telling IRS auditors which areas were problematic areas on the taxpayer's tax return?
   
4. 
   What is check kiting? Is it still a problem today?
   
5. 
   Why is Access preferred to Excel in the risk scoring applications?
   

6. 
   The TCMP provided the IRS with an estimate of the level on noncompliance and the noncompliance trend (true/false).
   
7. 
   The two main groups of tax returns are _____ (filed on paper and filed electronically, U.S. resident and resident abroad, business and nonbusiness).
   
8. 
   The IRS audit selection method is conducive to the auditor conducting a simple correspondence audit, office audits, or field audits (true/false).
   
9. 
   The objective of the risk-scoring method is to identify the high-risk cases and to end up with ____ (many/only a few/many or few, it doesn't matter) forensic units with high scores.
   
10. 
    In the risk scoring queries we need to avoid a ______ (division/multiplication/addition) by zero error.
    

1. 
   The first step in the TCMP audit process was,
   

f.Preliminary planning

g.Getting suggestions from IRS auditors

h.Purchasing statistical software

56.Every financial institution has a unique _________.

a.Routing submit code

b.Routing transit code

c.Routing transit digit

d.Routing transit number

57.If a single check kiting predictor was given a weighting of zero, then ________.

a.Final scores could not be calculated because we cannot divide by zero

b.All the final scores would equal zero because any number times zero is zero

c.This predictor would have no influence on the final scores

d.This predictor would be the only predictor influencing the final scores

58.The function in Access that allows for multiple "If" criteria is the ______ function.

a.Switch

c.Which

59.With respect to the risk-scoring method and the DIF scoring procedure, ______ require(s) a manual screening by a skilled investigator to decipher why the forensic unit was given a high score.

a.Neither

b.Both

d.Only the risk scoring procedure

1. 
   Create a predictor P1 that scores each vendor with a 0 if there are six or less invoices each month, and 1 otherwise. See equation 16.18.
   
2. 
   Create a predictor P2 that scores each vendor with a 0 if there are one or more credits or adjustments for the year, and 1 otherwise. See equation 16.19.
   
3. 
   Create a predictor P3 that scores the vendor according to the increase in dollars for H2 as compared to H1 as a proportion. Use the formula in equation 16.20.
   
4. 
   Create a predictor P4 that scores the vendor with a 0 if the total dollars are too small or too large to be a high risk fraud. Use the formula in equation 16.21
   
5. 
   Calculate the final risk scores for each vendor by giving P1 to P4 weightings of 0.15, 0.15, 0.50, and 0.20 respectively.
   
6. 
   Program the required queries in Access following the guidance in the book. Your final result should be list of the sorted 3,363 vendor risk scores in Access as is shown in Figure 16.11. Use the same naming conventions that are used in the book.
   

1. 
   Create a parameter query (qryVendorDetails) that extracts the records for a selected vendor. For example, if you type in "4343" (without the quotes) then you'll see the transactions for that vendor in a format similar to Figure 16.13. Show the Vendor, Date, Amount, ExpenseType, and ID fields. Show the result for vendor #4343.
   
2. 
   Create a new query (qryWeighted3) that shows only the 50 vendors with the highest risk scores.
   
3. 
   Create a neat Access report based on (b) above that shows only the 50 vendors with the highest risk scores. The report should show the details shown in Figure 16.11 and it should be sorted by the risk score descending.
   
4. 
   Create an Access report that shows the vendor details from part (a).
   
5. 
   Create a switchboard so that the reports created in (c) and (d) can be displayed with a single click. A switchboard is shown in Figure 15.8.
   

1. 
   Why is it problematic to use Benford's Law to detect fraud in a single set of financial statements?
   
2. 
   Why should totals and subtotals be ignored when analyzing data for compliance to Benford's Law?
   
3. 
   Figure 17.1 shows the reported numbers of InterOil Corporation (IOC). These numbers were reported in exact dollars. Why is it meaningless to analyze the last-two digits of financial statement numbers that are rounded to the nearest thousand or the nearest million?
   
4. 
   Why should we be at all concerned when accountants and managers round up sales numbers by a small percentage to get a number that just makes a psychological threshold? After all, we're just talking about a manipulation of just (say) 1 percent of revenues.
   
5. 
   Why did the study to detect biased income statement numbers (pp. 395-398) omit foreign companies listed on the NYSE?
   

6. 
   The analysis of the financial statements of the Oceania company showed that the digits of the revenue numbers and the digits of the expense numbers did not conform to Benford's Law using the MAD criterion. However, because there were very few records _____ (all/none) of the differences were statistically significant using the z-statistic.
   
7. 
   Excessive duplication of the digits in the financial statements of a company would not necessarily prove fraud (true/false).
   
8. 
   Fraudulent financial reporting is a phenomena limited to companies. Fraudulent financial reporting does not apply to government agencies or nonprofit organizations (true/false).
   
9. 
   In the analysis of the reported Enron numbers, the _____ (biserial/binomial/nominal) probability distribution was used to calculate the chances of seven second digit 0s in 12 reported numbers.
   
10. 
    Most cases of financial statement fraud involve misstated ______ (revenue/expense/inventory) numbers.
    

1. 
   Fraudulent financial reporting is the intentional misstatement of, or a(n) _________ the financial statements, made with the intent to deceive financial statement users.
   

f.Suspicion on

g.Condition in

h.Omission from

60.Income and expense (or income and deduction) items need to be analyzed _________ because they are manipulated in opposite ways.

a.Together

b.Separately

c.Quickly

d.Graphically

61.The Enron bankruptcy set off a chain of events that resulted in the ________ and brought the topic of corporate fraud and accounting to the attention of the financial press and television.

a.Sarbanes-Presley Act

b.Sarbanes-Oxley Act

c.Bankruptcy of Lehman Brothers

d.John Grisham novel "The Firm"

62.The Enron financial statements for 1997 to 2000 showed an excess of _______.

a.Round numbers

b.Last-two digit 00s

c.Second digit 9s

d.Second digit 0s

63.For the divisional reports the risk scoring system sought to evaluate the risk of intentional and unintentional ______ and biases in the reported numbers of the divisions.

a.Estimates

b.Rounding

c.Corrections

d.Errors
Cases

1. 
   Run the second digit test on the 2010 county populations using Access to calculate the second digit frequencies. Your queries will need to be an adaptation of the queries in Figure 5.3 and Figure 5.4. Use the MID function in Access to calculate the second digits of the 2010 population numbers. Use the Excel template NigriniCycle.xlsx to graph the second digits. The second digit counts (from Access) need to be pasted into the range B15:B24 in the Tables tab. Show the graph that is automatically prepared in the Second Digits tab. Delete all the unneeded tabs. Save the file as Case_17_16.xlsx.
   
2. 
   Do the second digit frequencies show signs of rounding-up behavior?
   
3. 
   Calculate the sum of the 2010 population numbers.
   
4. 
   Do the following for each 2010 population number that has a second digit 9: Increase the number by 1.5 percent (by multiplying by 1.015) and then round the number to the nearest integer. Now rerun part (a) and graph the second results again in Excel using the NigriniCycle.xlsx template. Show the graph that is automatically prepared in the Second Digits tab. Delete all the unneeded tabs. Save the file as Case_17_16b.xlsx.
   
5. 
   Do the second digit frequencies show signs of rounding-up behavior?
   
6. 
   Calculate the inflated sum of the 2010 population numbers as a result of the manipulation in (d).
   

1. 
   What were the overall observations of the forensic accountants as a result of applying the Benford's Law tests (see page 38)?
   
2. 
   What were the conclusions of the forensic accountants as a result of applying the second digit test to the ledger accounts (see page 40)?
   
3. 
   What were the conclusions of the forensic accountants as a result of applying the first-two digits test to the ledger accounts (see page 41)?
   
4. 
   What were the conclusions of the forensic accountants as a result of applying the number duplication test to the ledger accounts (see page 46)? Give a one or two sentence summary for each of the six points in the report
   

1. 
   List the revenues and the net income in dollars for the first quarter of 2001.
   
2. 
   What digit pattern do you notice for these numbers?
   
3. 
   Comment on the magnitude of the revenues.
   

1. 
   What are the three parts of the fraud triangle? Which of these three parts is especially relevant to employee purchasing cards?
   
2. 
   Briefly describe the Locard Exchange Principle. You will need to do an internet search on the term. How could this concept be related to purchasing card fraud and abuse?
   
3. 
   What is a purchasing card?
   
4. 
   What is meant by "waste and abuse" in a purchasing card program?
   
5. 
   What are the types of purchasing card fraud that could be perpetrated by an employee?
   

6. 
   The high-level overview tests for the purchasing card transactions included the _______ (same-same-same test/data profile/inspection test).
   
7. 
   For purchasing card data it is normal that there are no negative numbers from credits, refunds, or other miscellaneous adjustments (true/false).
   
8. 
   For purchasing card data it is normal to run the first-order test on amounts that are ____ ($10/$30/$50/$100) and higher.
   
9. 
   The summation test sums all the amounts with ________ (first/second/first-two/last-two) digits of 10, 11, 12,…,99.
   
10. 
    It is best to collect and analyze the data at the _______ (start/midpoint/end) of the investigation.
    

1. 
   The GAO is now known as the,
   

f.General Accountability Office

g.General Administration Office

h.Government Accounting Online

64.The use of cards is an efficient way of simplifying and speeding up the purchases of ______ transactions.

a.Foreign

b.High-value

c.Low-value

d.Cash

65.The National Association of Purchasing Card Professionals administers the _____ program.

b.Computer Forensics Education (CFE)

c.Certified Purchasing Card Professional (CPCP)

d.Computer Program Certification Panel (CPCP)

66.The first graph of the purchasing card dashboard in the chapter example was _______.

a.The data profile

b.Purchase amount by card type and by month

c.First-two digits of purchase amounts

d.Cardholders showing the largest month-on-month growth

67.The forensic analytic tests run on the purchasing card data would fit in well with a(n) ________ program.

a.Accounting

b.Rounding

c.Continuous monitoring

d.Mentoring

1. 
   Use Excel's pivot table capabilities to create a table of the population totals for the 50 states and the District of Columbia.
   
2. 
   Create a second smaller table showing just the total populations of CA, TX, NY, FL, IL, and Other. Use Excel's VLOOKUP function to get the populations of the five states, and use the fact that the Other total is the grand total (308,745,538) minus the totals for CA, TX, NY, FL, and IL. The example below has the numbers purposely blurred.
   

3. 
   Create an "Exploded pie in 3-D" pie chart from the data Columns D and E in (b) above. Make sure that the segments are labeled with the state abbreviations and "Other" as the case may be.
   
4. 
   Save your result as Case_18_16.xlsx.
   

1. 
   Create a table with the same headings as the first table in the Excel dashboard (Figure 18.1). This is the "total purchase trend across all cards for a given period." The table has the sum in dollars, the counts, and the average value for six months, together with YTD figures in the last row. Create a table with the same format but use the PageSoftware invoice data. Use Excel's functions to calculate the dashboard amounts. Use functions that can be easily updated for the next month's dashboard. Your answer will have dollar amounts or transaction counts where the xs are shown below.
   

2. 
   Save your file as Case_18_17.xlsx.