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Quickly identify employees who are potentially violating payroll processes or controls with this suite of 14 tests that can be run in various combinations, including the ability drill down for greater detail. This complete suite contains a dialog box allowing users to select which tests to run, input additional information needed for specific parameters and control how scores are weighted.
To collect an overall risk rating by an employee, the user sets the risk level to high, medium or low for each test. Employees who fail the most individual tests are sorted in descending order from highest to lowest. The final scorecard database includes action links to drill down into the data to see more details. The App automatically creates a subfolder to store the database with the final results, which is flagged to make it easier to find.
You will need to tag individual fields in order to run the tests. This requires access to both HR Master Data and Payroll Transaction data. If these fields are not available in one database, a database can be created by performing a join of HR Master Data and Payroll Transaction Data in IDEA using common fields, such as employee ID. Instructions for tagging databases are provided in the User Guide, provided with the suite.
Need to search large databases for specific words or phrases, but don’t have time to perform individual searches? The Looping Search App conducts multiple searches at a time across single or multiple fields using keywords or wildcard fragments contained in a second file.
Results are ordered from highest to lowest based on hit rate to quickly identify potential fraud or infractions. The App automatically creates a subfolder to store the database with the final results, which is flagged to make it easier to find. The Looping Search offers the ability to tag data in a subfolder for easy access to analyze. This App is highly effective for P-card and T&E audits.
This App now includes a dialogue box providing users with the choice to perform flexible or exact keyword matches. For example, the user can decide whether to allow “spa” to bring in all words starting with those letters, such as “space,” or only search for the word “spa.” This new capability will help look for specific words or fragments for a more refined search when analyzing large data sets.
The Looping Search App identifies specified keywords in a table or large database to help identify potential red flags, such as the purchases made at unapproved merchants. The user tags fields for two databases. One contains a list of keywords, usually a table or Excel file with one field listing all words of interest, and the second table contains the data to be searched. Dialog boxes assist you in every step required for testing. Search terms are not case sensitive. You can search 1, 2 or 3 columns within a database. The App creates a folder within your Project with the results, which can be summarized and prepared for further investigation.
Want to see which keywords occur most often within a data set? This App creates a unique list of words found in a selected field including each occurrence within the database. Words are automatically converted to uppercase with special characters removed and the most frequently used words appear at the top to help you focus on keywords of interest.
Results are stored in a subfolder, separate from the input databases, making them easier to find. The Word List Maker App offers the ability to tag data in subfolders for easy access to analyze. This App pairs well with the Looping Search App for developing a list of keywords to search within large data sets.
The App now features a reference card within the result set, which allows the user to see the original data including the entire row where the match resided. Users can gain deeper insights by seeing the word list itself, plus a separate table that includes source data.
The Word List Maker App analyzes a tagged field, separated out by spaces, to create a unique list of words found in a field. The App helps “normalize” data by converting words to uppercase and removing special characters, keeping only alphanumeric characters. A summarization is performed on the data to keep only the unique list of words and count the number of occurrences found in the file for each word.
The final database is stored by the count and moved to a subfolder which is flagged for easy identification. The database contains the word and a count of how many times each word occurred. You can use IDEA’s search feature to extract specific words or records.
One can run Word List Maker with no option settings at all. By default, it will count all words two characters or greater in length, and it will convert any special characters to spaces. If these behaviors are undesired, or if the user wishes to submit a list of words to omit from the list produced, the Options Dialog can be utilized. Using this dialog, the user can enter words in the value textbox one at a time and click the green check button to form a list of words to omit. The user can then click the save button to save this list to a file if the user wishes. The file can then be loaded later using the open file button.
This can be useful when creating multiple lists across multiple databases to conveniently omit from any list common words such as “the”, “and”, and “for”, for example. In fact, Omit Words will accept any text files (.txt extension) that contain lists of words with one word per line, not just those it creates.