Data Analysis
The Data Analysis module of Synaxion Urbidata is aimed to achieve the following objectives:
- Improve the data quality by the identifying master data and postings which are duplicate or incomplete.
- Identify actual breaches of segregation of duties as the document flows of an entire business cycle is analyzed.
- Identify potential fraud cases as suspicious transaction (flows) are identified.
- Improve the harmonization of business processes as differences in the actual use of the applications are identified.
Techniques
| Analyses techniques | Explanation |
| Pattern and frequency | Attempt to identify anomalies within the data. |
|
Circumvention strategies
|
The analysis searches for transactions that exhibit a pattern or frequency which suggests someone was processing transactions below the control threshold. |
| Duplicate analysis | The search routine searches for duplicate information within the postings. |
|
Changes
|
The analysis searches for changes in data that would be consistent with a fraud scenario. |
|
Illogical
|
The analysis searches for postings that do not fit the normal frequency or pattern that would be expected. |
|
Trends
|
The increasing or decreasing nature of the activity is not consistent with the established standard. |
|
Mistakes or an unsophisticated perpetrator |
In this phase the data interrogation is simply looking for errors which would be indicative of a fraud scenario. |
Using the data techniques all data can be clustered using catalogues. In these catalogues data in a functional area is combined. Using the catalogues, filters can be defined to interrogate the data per period and operating company. A number of examples of catalogues and filters is included in the table below.
Filter examples
| Catalogus | Filter |
|
Postings
|
Items posted subsequent to their effective date Journal entries made at unusual times Benford’s Law Analysis |
|
Sales orders
|
Discount per user, account, customer Return sales orders per user |
| Purchase orders |
Duplicate purchase orders |
|
Master Data
|
Duplicate vendors Incomplete vendors (VAT, PO Box, Street, bank account) Changed vendor Bank Accounts Changed customer Bank Accounts |