Use this method to find suspicious vendors that have similar names to a high-volume vendor. Typically, a suspicious vendor makes little revenue but their name resembles the name of a high-volume vendor. For example, if there were a vendor called “Ziemens AG ” it might be considered suspicious because it is similar to “Siemens AG”.
This method determines the low- and high-volume vendors based on the revenue of the last 12 months. For each low-volume vendor, it tries to find matching high-volume vendors that have similar names. The matching is done with a freestyle fuzzy search on the four name columns of table LFA1
. You can restrict matching by specifying thresholds for the minimum turnover of valid vendors and the maximum turnover of vendors that may be suspicious.
Investigation object type: FRA_VEND
(Vendor
)
Detection object type: FRA_VEND
(Vendor Master Data
)
BKPF
: Accounting Document Header
BSEG
: Accounting Document Segment
LFA1
: Vendor Master (General Section)
LFB1
: Vendor Master (Company Code)
Procedure Category | Procedure Name | Procedure Type | Package |
---|---|---|---|
Selection |
| SQLScript Procedure |
|
Execution |
| SQLScript Procedure |
|
Additional Information |
| SQLScript Procedure |
|
The execution procedure uses two foundation procedures:
PR_VENDOR_SIMILAR_NAME_FUZZY_SEARCH
This procedure performs the fuzzy-logic search.
PR_CONVERT_AMOUNT_TO_GIVEN_CURRENCY
This procedure converts invoice amounts into the currency of the threshold amount.
Parameter | Use |
---|---|
| Minimum turnover of vendors who are considered as match candidates (valid vendors to match against suspicious vendors that have similar names). The turnover is aggregated over the last 12 months. |
| Maximum turnover of vendors who are considered as fraud candidates. |
| The currency in which the threshold parameters are denominated. |
| Specifies by how much a search term and a hit in the data being searched may differ. The parameter tells the SAP HANA database how much fuzziness – differences in spelling, differences in number of characters, and so on – to allow in doing a search. The error tolerance scale is a percentage, from 0 to 100, where 100% is an exact match. The lower the value of the fuzziness parameter, the higher the tolerance. That is, a lower fuzziness value may produce too many false positives. The recommended setting is in the range between 80 and 100. |
Message ID FRA_INTERNAL_AUDIT
, message number 121, Vendor &1 (&2) has a similar name as high-volume vendor &3 (&4)