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  • Writer's pictureDerrick Wong (Managing Director)

Popular Analytics Tests (5 of 6 series)

Updated: May 16

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

3) Technology

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 Journal Entry Risk Scoring in Part 4 (url link) series. For part 5, we are going to discuss about Duplicate Payments.


Duplicate payments can be a significant source of financial leakage.

Although some systems possess basic built-in duplicate detection, it's not likely that they will detect near duplicates that can come in different configurations. The enhanced Duplicates command in Analyzer has helped users to identify different kinds of fuzzy duplicates. Here are some of the analytics in Duplicate Payments:


Same-Same-Same

Same-Same-Same | Connevate

Detecting payments where one or more values are identical, such as same vendor, same amount, same date, is straightforward. In the Duplicates command dialog, select those fields from the "Field(s) to test for Duplicates" list.


You can select additional fields in the "List fields" list to send to the output, such as product number, that may enhance your follow-up analysis. And, finally, the output can be directed to a file in the "Output options" section by selecting "DATA" and naming the output file.




Same-Same-Different

If you're trying to detect same vendor, same amount, different invoice, selecting the "Different" parameter will identify those transactions.

Same-same-Different | Connevate

Same-Same-Near

The "Near" parameter allows greater precision and focus. For example, you could search for same vendor, same month, within $10 for amounts that are very close in value. As well, you could identify same vendor, same product, same amount, date within 14 days to exclude recurring payments. The field being tested for the "Near" quality must be the final field selected in the "Fields to test for Duplicates" list.


Note that the results for Near and Similar places the matching records side-by-side. This facilitates more granular testing, such as calculating the actual number of days between the two transaction dates.

Same-Same-Near | Connevate

Same-Same-Similar

It frequently happens that vendors may re-issue the same invoice with a slightly different number, such as re-issuing invoice number "102" as "102a". Or input errors may replace one character so that it is entered as "I02".


The "Similar" parameter allows you to test for same vendor, same amount, invoice numbers within 1 character of each other.

To compare the invoice numbers, all blanks, leading zeros and punctuation are removed, data is made upper case and similar looking characters (e.g. 1 and I, or 0 and O) are matched.


Note how similar the two invoice numbers are for rows 4-6 with substitutions of "I" for "1".

same-same-similar | Connevate

Suppress Duplicates Parameter

This checkbox will exclude exact matches from the Near and Similar analytics. Exact duplicates are higher-risk, and the presumption is that those would have been already identified. This allows the analyst to focus on a different population without the risk of double-counting.


Do watch out for our part 6 and final series of Popular Analytics Tests on Counterparty Validation & Outliers, or reach out to our team info@connevate.com for further discussion on your areas you will like to cover.


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