Popular Analytics Tests (Part 2 of 6 series)
Many Internal Audit team needs to prove ROI if they intend to invest on Analytics technology. The best way is to achieve quick implementation of analytics use cases, and start testing it out on their data. When it comes to analytics use cases, we always share with our customers on 2 things:
1) Analytics is only limited to your own creativity.
2) No Two Organizations are Identical, But there will be commonly use analytics which many will be using the same tests.
So to achieve quick ROI on your analytics, we have come up with 6 areas of the common and popular analytics tests that you can consider. They are:
1) Employee Spending
2) Vendor Management
4) GL JE Risk Scoring
5) Duplicate Payments
6) Counterparty Validation & Outliers
Do follow us on our LinkedIn or subscribe to our newsletters for updates. We have discussed about Employee Spending in Part 1 (url link) series. For part 2, we are going to discuss about Vendor Management.
The proliferation of complex supply chains has made vendor management a high-risk area for many organizations. Managing vendors now requires a multitude of tests to ensure that the associated risks are kept to a minimum. In addition to duplicate payments, vendor data quality, conflicts of interest, and watch-list comparisons are key areas for testing.
Vendor Data Quality:
Look for missing or incomplete critical data when input validation is weak or non-existent. Use the various Arbutus functions to test for completeness by deploying filters and the Count command to document the results.
IsBlank(<field name>) will tell you if a key character field such as the City field has no content.
Format(<field name>) will display the underling numeric/alpha content of a field. For example, to test the vendor telephone numbers for appropriate content, use the expected format of your supplier data to identify non-conforming numbers. In the US and Canada, telephone numbers consist of 10 digits. Your filter would look like this:
Format(Phone_No) <> "(999) 999-9999"
Conflict of Interest
Compare vendor and employee telephone numbers, addresses, bank accounts, and tax IDs to identify identical or similar entries. Use the SortNormalize function to standardize the data, then execute a many-to-many Join between the two files.
Watch List Comparisons
Download the GSA SAM file or the OFAC list and use the same process as the conflict of interest test to identify possible matching names or addresses.
A vendor account that has not been active leaves it open to fraud. To identify vendors who have not been active in the past year, download the payments data and the vendor master file. Then, run an unmatched Join between the two files on the vendor number with the vendor master as the primary file. The output will consist of all vendors who have not been active.
Do watch out for part 3 on analytics in the Technology area, or reach out to our team email@example.com for further discussion on your areas you will like to cover.