Abstract: In an on-line method of analyzing financial accounting data, uploaded financial accounting data is received at a server (2) from a client computer (3). The data is analyzed at the server (2) to identify anomalies in the data. A display is provided at the client computer (3) representing the anomalies that have been identified. Further, in a method of pre-processing financial accounting data prior to analyzis of the data, the financial accounting data is abstracted to correspond to a pre-stored accounting ontology. Further, in a method of analyzing financial accounting data, the method checks the data for violation of a particular state to identify inconsistent combinations of values in the data.

Abstract: In a method of identifying unusual combinations of values in data (1) that is arranged in rows and columns, the data is pre-processed to put it into a form (4, 5) suitable for application of a search method thereto. Using said search method, the pre-processed data is searched (8) to search the set of possible combinations of unique values from the columns to find any combinations that are unusual according to an evaluation metric.

Abstract: In an on-line method of analysing financial accounting data, uploaded financial accounting data is received at a server (2) from a client computer (3). The data is analysed at the server (2) to identify anomalies in the data. A display is provided at the client computer (3) representing the anomalies that have been identified. Further, in a method of pre-processing financial accounting data prior to analysis of the data, the financial accounting data is abstracted to correspond to a pre-stored accounting ontology. Further, in a method of analysing financial accounting data, the method checks the data for violation of a particular state to identify inconsistent combinations of values in the data.

Abstract: In a method of identifying unusual combinations of values in data (1) that is arranged in rows and columns, the data is pre-processed to put it into a form (4, 5) suitable for application of a search method thereto. Using said search method, the pre-processed data is searched (8) to search the set of possible combinations of unique values from the columns to find any combinations that are unusual according to an evaluation metric.

Abstract: Methods and computer apparatus are disclosed for deriving first order logic language rules for use in analysing new data to identify anomalies in the new data. Historical data is formatted to be in a form suitable for application of a machine-learning algorithm thereto. The machine-learning algorithm is applied to the formatted historical data to generate a set of first order logic language rules that cover the formatted historical data. The set of first order logic language rules are analysed to obtain a subset of said set of first order logic language rules which can be used as first order logic language rules in analysing new data.