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In session three we discussed

In session three we discussed. Evidence Gathering techniques Evidence Analysis Techniques. Session IV contents. IDEA is Specialised & support Audit techniques / software used for data importing, extraction and analysis. IDEA CAAT Development Auditing Using Idea Downloading Data

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In session three we discussed

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  1. In session three we discussed Evidence Gathering techniques Evidence Analysis Techniques

  2. Session IV contents • IDEA is Specialised & support Audit techniques / software used for data importing, extraction and analysis. • IDEA • CAAT • Development • Auditing Using Idea • Downloading Data • Function in IDEA • Internet • Report

  3. IDEA- Computer Assisted Auditing Technique • Interactive Data Extraction and Analysis • A comprehensive CAAT • Helpful for Auditors, Financial Managers, Investigators and Accountants • display, analyze, manipulate, sample or extract from data files from almost any source - mainframe to PC, including reports printed to a file • Lower audit cost, enhance the quality to work and take on new roles by putting the power of IDEA

  4. IDEA-Development • Developed by Auditor General of Canada- 1985. • Shown to CICA(Canadian Institute of Chartered Accountants) -as tool for CAAT. • CICA- realised potential and licensed from Canadian Government. • In 2001 CICA sold its interest in IDEA to CaseWare. • CaseWare launched Idea 2001.

  5. Auditing Using Idea • Advantages:- • Increased or wider scope of investigations (conducting tests which are otherwise not possible manually) • Increased coverage ( checking large number of items and potentially covering 100% of the transactions for a year or more) • Better information ( Extra Analysis or profiling of data ) • Saving time

  6. Auditing Using Idea • Advantages :- • Mechanical Accuracy- Totals to ensure accuracy and completeness of information. • Analytical Review :- Stratification to populate records ( debtors,loans, breakdown of transactions.) • Comparison of figures with previous year to determine trends. • Exception testing to identify unusual or strange items - deviation from procedure.

  7. Auditing Using Idea ……. • Duplicate testing- checking for two or more occurrences of same record • Manually not possible to view all records. • Completeness - Gap detection & Matches. • Inventory & Sales files- completeness of dispatch note numbers & purchase files for receiving numbers. • Gap detection - Cheque numbers.

  8. Auditing Using Idea • Completeness- check between master (maintenance contracts) file and transactions (invoices ) to see any item on master for which no transaction.

  9. Downloading the Data • 5 stages • Planning • Requesting the Data • Performing the Transfer • Importing the Data • Checking the Data

  10. Downloading the Data • Planning: discussion with user and IT staff • File formats of different types • Excel, Access, dBASE, Lotus etc • ODBC (Oracle, SQL etc) • ASCII files (American standard code for information interchange)

  11. Function that can be performed using IDEA • Import- Any files type-text. Excel, access,ASCII, ODBC • Extract –Extracting Records • History - audit trail or log of all operations carried out on a database • @Functions – Using functions to extract record enhances IDEA capabilities • Indexed Extraction -You can select and index for the search, rather than have IDEA search through the entire database. • Join - can be used to combine fields from two databases into a single database for testing or test for data which matches or does not match across files

  12. Function that can be performed using IDEA • Append:- you may append 12 monthly payroll files to produce a database of all payroll transactions for the year • Gaps :- You can search a file for gaps in numeric or date sequence, or alphanumeric sequences • Sort :- The Sort option is used to create a new database physically sorted in the specified order • Chart :- Chart Data option can be used to graph data files or test results, in bar, stacking bar, pie, plot or area charts • Stratification:- Numeric Stratification, Character Stratification and Date Stratification are powerful tools used to total the number and value of records within specified bands. • Summarization :- Used to accumulate the values of numeric fields for each unique key where there is a single field in the key

  13. Function that can be performed using IDEA • Aging:-The Aging function is used to age a file from a specified date for up to 6 user defined intervals.. For example, the outstanding accounts could be aged at the year-end in order to determine provisions required against bad debts • SamplingIDEA offers four sampling methods together with the ability to calculate sample sizes based on parameters entered and evaluate the results of sampling tests. The sampling methods available are systematic (e.g. every 1000th record), random (number of items chosen purely at random), stratified random (a specified number of items selected randomly from within range bands), and monetary unit (e.g. every 1000th Rs or other monetary unit). IDEA also provides an Attribute Planning and Evaluationoption which can be used to calculate sample sizes, confidence levels, error limits and number of sample errors. These calculations are used to plan and then evaluate the results of the samples.

  14. Function that can be performed using IDEA • Add fieldsData imported into IDEA is protected and cannot be modified. However, additional editable fields can be appended to the database for comments, for checking off items or for correcting data. In addition, you can add virtual (calculated) fields to prove calculations in a database, perform new calculations and ratios from fields within the database or to convert data from one type into another.

  15. Function that can be performed using IDEA • Management reports and analysis • Ratio calculation and analysis • Summarization and ranking (such as customers, products, sales force, and regions) • Performance measures (response times for order processing, for example) • Profiling • Inventory analysis • Cash flow analysis

  16. IDEA- Sampling Methods • Simple Random Sampling • Systematic Sampling • Stratified Random Sampling • Monetary Unit

  17. Simple Random Sampling • In this example we will come to know how Idea will go for selecting records at random based on the basis of following information. There are 335 records in the database but we are interested in selecting 50 records at random where starting point will be at record number 25 and random seed can be entered by user or default seed can be accepted . Random number seed is a number used by IDEA for internal programming.

  18. Idea will select 50 records at random in a separate database for previous details as shown below

  19. Systematic selection • In this the first item is randomly selected • After that the same random sample is systematically selected at the sampling interval. • For eg. If 5 items are selected first item is randomly selected, that is say 6. Then if the sampling interval is 300, then it will be 5, 305,605,905,1205 etc. in a group of 2000

  20. Systematic Sampling- Idea • Systematic Record Sampling is a method of extracting a number of records from a file at equal intervals. This method is often referred to as interval sampling. • There are two methods of determining the sample: • entering the Number of records in which case IDEA will compute the interval size; • entering the Selection Interval in which case IDEA will compute the number of records. • The above parameters are calculated on the number of records in the database and will default to the first to last records. However, the sample can be extracted from a range of records, if required. • Systematic sampling should be used for samples to evenly cover a population range.

  21. Systematic Sampling using IDEA

  22. Idea – Systematic Sampling Idea display following dialogue for systematic sampling stated in previous screen

  23. Idea – Systematic Sampling • In earlier slide when interval is one no. of records selected is 335 but when interval is changed to 50 it will select seven records from 335 records as under

  24. Idea will filter 7 records as under for above filtration by creating a separate database

  25. Going for stratified Random sampling in IDEA Objective is to select sample at random from the stratum

  26. Stratified Random Selection • If database is not stratified IDEA will prompt user to stratify it first

  27. Stratification Screen Mention increment, select field to stratify & fields to include. Change file name if you want.In this example increment is 15000 and 20000 respectively, field to stratify is Credit Limit

  28. Stratification – screen showing number of records per stratumUser has to mention Sample size Sampling will be according to sample size.

  29. Record selected according to Sample Size- Stratified Random Selection- Screen shows stratum number lowest value of stratum highest value of stratum record number from sample database

  30. Though we get randomly selected stratified records one can also go for viewing all the records within the stratum if needed. For doing so just click the numeric/character/date stratification tab in the sample database.

  31. Stratification - showing numeric stratification tab crated in database

  32. Stratification- for viewing particular records just double click the stratum

  33. Monitory Unit Sampling • Monetary Unit Compliance Testing is used to evaluate whether chosen attributes are present with greater weight given to higher value items. • Use MUS planning to compute a sampling interval and a sample size using a Monetary Unit Sampling approach. • MUS is generally appropriate for populations with low error rates. If you anticipate a high error rate, consider using classical sampling methods. • If you plan a sample for a low error rate, but you discover a high error rate in the population, IDEA provides you with a high-rate alternative evaluation technique based on classical sampling methods, appropriate for MUS sample selection techniques. • Ex. Tests of Assets such as Accounts Receivables (Debtors) or Inventories and where a coverage of value is required should use Monetary Unit Sampling.

  34. Monitory Unit sampling • Note :- Ensure you have all the details to hand such as the population value and the requires precision and materiality before selecting the MUS Planning options. • Monetary Unit Sampling are difficult to implement manually. Where ever tests need to refer to physical documentation or assets rather than computer records then an appropriate statistical sampling technique should be used.

  35. Monitory Unit sampling • should be used where a financial assessment of error is required with items that can be partially wrong

  36. Monitory Unit sampling • Brief description of Monetary Unit Sampling • A numeric amount field is the basis of the sample. It is the rupees, dollars, pounds etc or unit which is sampled. Having chosen the rupees, dollars, pounds etc or units to test on an interval (or random item within each interval) basis, the items which contain those rupees, dollars, pounds etc or units are identified. To do this it is necessary to calculate the cumulative value of the relevant field for each item.

  37. Monitory Unit sampling Record Ref Amount CUMULATIVE AMOUNT 1 A123 50 50 2 A124 75 125 3 A125 40 165 • With an interval of 100 starting at a random start point of 35, the first selection would be at 35, and the second at 135. It is the cumulative field that is used for the selection. • Obviously any items greater than the sampling interval are forced to be chosen. However these 'key' or 'High Value' items should be extracted from the population and subject to separate testing leaving just those items below a specified High Value Amount (which can, if desired, be set to a different limit to the interval) to be statistically evaluated.

  38. Monitory Unit sampling • IDEA offers options for determining the sample size for both compliance and substantive tests, based on confidence levels, population size, materiality and certain options on the weighting statistics used. • Whether or not the planning option is used, samples can be selected using the Monetary Unit Sampling techniques. • The output file contains an editable field called AUDIT_AMT. If desired, this can be updated from the results of audit testing using the Edit Field option and then a detailed evaluation of the results can be performed against Book Value

  39. Planning Monetary Unit sampling • To plan a sample, note the total value of the population to be tested. It is assumed that the required confidence level (often 90%) and the materiality amount for the audit will be known from the audit planning. • Ensure the file being tested (if a subsequent extract is to be performed) is the current selected database.

  40. Planning Monetary Unit SampleUse Monetary Unit Sample planning to compute a sampling interval and a sample size using a Monetary Unit Sampling approach.

  41. Monetary Unit sample planning • Two tests • Compliance Test • Substantive Test

  42. Monitory Unit Compliance Testing • Monetary Unit Compliance Testing is used to evaluate whether chosen attributes are present with greater weight given to higher value items. • Having selected the Compliance testing tab complete the dialog as follows: • Enter the MUS Confidence level Specify the confidence level (degree of assurance) required. The value must be between 1% and 99.99%. IDEA defaults to 90%. Confidence levels of below 70% are of dubious worth. The higher the value the greater the sample size.

  43. Monetary Unit Compliance Testing • Enter the total value of the sampled population: This can be determined from selecting statistics or control amount on the file in question. Leave as zero if unknown. Strictly, it should be net of any high value (key) items excluded from the sample.

  44. Monetary Unit Compliance Testing • Enter the Materiality amount: The materiality (i.e. the highest level of monetary error which is acceptable).

  45. Monitory Unit Compliance Testing • Enter the Multiplier ratio Enter a figure between 1 and 9 being an estimate of the ratio of items with critical compliance deviations to the number of errors. A compliance deviation (i.e. lack of control being performed) does not necessarily result in an error. This is an estimate of the number of compliance deviations to each error. The default is 3 (which gives the highest sample size) and should be used unless the ratio is thought to be different.

  46. Monitory Unit Sample Planning • Enter a number for the Tolerable number of Compliance deviations • Enter a figure between 0 and 3 being the acceptable number of deviations in the sample. The default is 1.

  47. Monetary Sampling showing computation of sample size & interval • Click on the Compute button to determine the sample size and interval. • At this stage a decision has to be taken as whether to go ahead and Extract the Sample or whether to change any of the parameters and recompute. Click on the Extract button to extract the sample. • If an extraction is not to be done at this time then click on the OK button

  48. Monetary Unit Extraction of records according to given interval Audit Amount field Sample field Cumulative Totals

  49. Monetary Unit Sampling-Substantive Testing • Monetary Unit Substantive Testing is used to evaluate financially the value of errors in the chosen Population

  50. Monetary Unit Sampling-Substantive Testing Enter the MUS Confidence level • Specify the confidence level (degree of assurance) required. • The value must be between 1% and 99.99%. • IDEA defaults to 90%. • Confidence levels of below 70% are of dubious worth. • The higher the value the greater the sample size.

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