Validis is a web-based service which detects anomalies in a data base. The word itself is derived from a concatenation of Validate and Discover. The primary role of the SME is to provide financial support to the SME . It provides a means of identifying what is incomplete, invalid, inconsistent, or inaccurate, an analysis collectively tagged the ‘Four Is’.
The service, offered by Validis is based on Future Route .
Validis presents their service through a web-based interface. On the server side the system uses a number of sophisticated techniques to analyze data for quality problems.
Underlying the system is an abstract representation of accounting data, in the form of an ontology of accounting concepts. In an initial setup step the users are automatically mapped into this representation by analyzing the Chart of Accounts.
The system maintains an Expert System in the form of a body of rules that describe valid, and invalid states for individual transactions, accounts, and other elements of the accounting ontology. Validis uses a specialty rule developed in house, similar to Prolog and SQL, to create these rules. The rules are written in terms of elements of the accounting ontology, and therefore once a set of accounts has been mapped into it, the rules can immediately be applied to that set of accounts.
Validis also uses Information Theory to discover records in the data that are inconsistent with the typical behavior exhibited in the data. By finding records that have information bits relative to the information bits of the individual field values in that record, Validis is able to identify unusual combinations of field values. It presents these unusual combinations to the user in the form of easily proposed propositional rules.
Numerical values in the data are also subjected to outlier analysis, individually, and agglomerated over time periods and over elements of the accounting ontology. Records with values that are outliers in absolute value terms, or which deviate from patterns identified in the data, are shown to the user.
Accounting data uploaded to Validis is also analyzed and compared to the Benford Distribution (see Benford’s Law ), to check that the data has not been artificially generated or manipulated. The user is alerted if the data deviates from the expected distribution.
Output is presented in graphical form via a web interface. Underlying report data may be downloaded into excel for further analysis and manipulation. A presentable drill down analytical review may be manipulated across user selected time periods.
While the parent business has been developing and deploying machine learning solutions since 2002. The service is due to enter beta release during March 2007 within a selected community of UK accountants, with full market availability thereafter. Initial deployments are compatible with SAGE (line 50), SAGE, SAP, Sun Accounts, Microsoft Dynamics GP and AX, Oracle,
An alpha test period for the UK and the UK. Initial deployments are based on Sage Line 50 accounting data.
The following is a summary of some of the most recent studies in the field of corporate governance. Throughout 2007.