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Published byShana Burns Modified over 6 years ago
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Chapter 7: Computer Assisted Analytical Techniques
EECS
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The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency. – Bill Gates EECS
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General Analysis Software
High level language similar to Microsoft Access with many functions to retrieve and analyze data. Common packages are ACL and IDEA Can be learned in a day Excel and Microsoft Access can also be used effectively as GAS. EECS
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Integrated Test Facility
Can be used to set up a test unit in the client’s organization Run test transactions through the test unit and subject them to all controls EECS
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Typical Functions Available in a GAS package
Extracting Data from Files Verifying calculation Joining tables Reorganizing Data Statistical sampling Statistical analysis EECS
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ACL and IDEA Very similar in functions.
User friendly, can be learned in a day. Its power increases with the growth in hardware technology; e.g., computing power of hardware doubles annually EECS
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GAS Applications for Banks
Deposits, e.g., checking withdrawals from dormant account. Loans, e.g., verifying interest calculation. Credit cards, e.g., verifying service charges to merchants Non-interest revenue, e.g., verifying calculation. EECS
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GAS Applications - Revenue
Sales, e.g., selecting a sample to vouch Receivable, e.g., aging Cost of sales, e.g., cross-referencing to inventory relief Commissions, e.g, verifying calculation EECS
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GAS Applications - Expenditure
Purchases, e.g., checking to warehouse receipts indicated in data file Inventory, e.g., obsolescence Expenses, e.g, analytical review Payroll, e.g., verifying calculation EECS
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ACL and IDEA Features Common operators include arithmetic and comparisons Common functions available for field, character and digit manipulation; similar to Excel’s. EECS
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ACL and IDEA Features Join 2 files based on a common key to a new file that contains all or a subset of the fields from the source files. This enables better correlation and analysis. For example, the accounts receivable master file can be joined with the invoice file to check credit limit to sales. EECS
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ACL and IDEA Features Analyze a file to statistics like averages and media on selected fields Stratify Aging EECS
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ACL and IDEA Features Gap analysis Duplicate record check
Sampling and evaluation File import and export EECS
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ACL and IDEA Features Fraud analysis based on the Benford Law
Benford Law says that the first digit of a natural number like expense or population is mostly likely 1 and least likely 9. Formula for the probability of a number starting with the string “n” is Log10 (1 + 1/n); e.g., the probability of a number starting with 1 is Log10 (1+ 1/1), or 30.1%; the probability of a number starting with 314 is Log10(1 + 1/314), or .14%, this makes sense because 314 is so restrictive. You can use Excel to verify this. EECS
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Benford’s Law Benford's law, also called the first-digit law, states that in lists of numbers from many real-life sources of data (i.e., natural numbers like amounts, but not account number which is arbitrarily assigned), the probability of 1 being the leading digit is very high, 30%; and higher order digits occurring as the leading digit have successively less probability, to the point that 9 as the first digit has a probability of less than 5%. EECS
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Benford Law Distribution
EECS
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Benford Analysis Applying the Benford Law, an analyst can look for frequency of leading digits to compare to the Benford averages. A significant variance may indicate fraud, i.e., some numbers were plugged in as opposed to having arisen from natural transactions. The law about the first digit also applies to the second digits… in less magnitude. EECS
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Benford Law The longer a number, the more it obeys the Benford Law.
A one-digit number is not in reliable obedience. Any natural number with at least 3 digits fits the Benford Law quite well, and if a number exceeds 9 digits, the Benford precision will stay fairly constant afterwards, i.e., the law of large numbers. EECS
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MC Question Which of the following number values can be tested with the Benford Law? A. Social insurance number B. Student number C. Store marked down sales price D. Store inventory value for a product E. Class size EECS
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