Abstract
Much legal evidence is being generated by and stored in information systems. In this paper we look at evidence from an auditing point of view. Auditors rely on evidence of the party being audited, who may have a legitimate or illegitimate interest to manipulate it. To assess the quality of audit evidence, we argue for an approach called model-based auditing. It is based on a mathematically precise model of the expected relationships between the flow of money and the flow of goods or services. Such equations are used for cross verification. If the equations do not hold, either something is wrong (violation) or some underlying assumption is false (exception). To show the usefulness of the approach, we look in particular at a case study of a legal dispute about automated contract monitoring. A precise revenue model is instrumental in demonstrating that the data set does indeed constitute appropriate evidence to settle the case.
Original language | English |
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Title of host publication | Proceedings of the 15th International Conference on Artificial Intelligence and Law (ICAIL 2015) |
Publisher | Association for Computing Machinery |
Pages | 43-52 |
ISBN (Print) | 9781450335225 |
DOIs | |
Publication status | Published - Jun 2015 |