|Appears in Collections:||Computing Science and Mathematics Book Chapters and Sections|
|Peer Review Status:||Refereed|
|Title:||A review of artificial intelligence and biologically inspired computational approaches to solving issues in narrative financial disclosure|
|Citation:||Minhas S, Poria S, Hussain A & Hussainey K (2013) A review of artificial intelligence and biologically inspired computational approaches to solving issues in narrative financial disclosure, Liu D, Alippi C, Zhao D, Hussain A (ed.) Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings, 6th International Conference on Brain Inspired Cognitive Systems, BICS 2013, Beijing, China, 9.6.2013 - 11.6.2013, Berlin Heidelberg: Springer, pp. 317-327.|
|Keywords:||Narrative Financial Disclosure|
|Series/Report no.:||Lecture Notes in Computer Science, 7888|
|Abstract:||Indisputably, financial reporting has a key role to play in the efficient workings of capitalist economies. Problems related to agency and asymmetric information (Jensen and Meckling, 1976) would abound and cripple financial markets, as it has done when left unchecked (Enron, WorldCom and Tyco). However for too long, quantitative data has monopolised the assessment and prediction role within this arena and this has contributed to the failures, borne out by research (Kumar & Ravi, 2007). As qualitative data proliferates, containing value relevant information it needs to be factored into the analysis. This paper reviews work on financial narrative disclosures and looks at conventional artificial intelligence and more recent biologically inspired computational approaches to catapult the domain to more progressive methods of using linguistic data in evaluations.|
|Rights:||The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.|
|Affiliation:||Computing Science and Mathematics|
Computing Science - CSM Dept
Accounting and Finance
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