Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/29340
Title: Automated Assessment of Capital Allowances
Authors: Gholizadeh, J
Chun, K-S
Curd, C
Masters, N
Gibson, D
Li, Y
Keywords: capital allowance;tax relief;artificial intelligence;expert systems;natural language processing;automation
Issue Date: 25-Apr-2024
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: Gholizadeh, J. et al. (2024) 'Automated Assessment of Capital Allowances', IEEE Access, 12, pp. 60206 - 60221. doi: 10.1109/ACCESS.2024.3393830.
Abstract: Capital allowances play a crucial role in enabling businesses to claim tax relief on specific capital expenditures, reducing their taxable profits and overall tax burden. However, the current manual process for managing capital allowance claims is time-consuming and complex, particularly for small and medium enterprises (SMEs) that often lack access to expert consultation. Furthermore, the distinct nature of construction expenditure on buildings adds to the complexity, with unique costs and data for each property and project. These challenges underscore the necessity for the development of automated technologies and systems for capital allowance assessment. To address these challenges, we present the development of an automated capital allowance assessment system comprising three key components: a capital allowance expert system, a tax coding system, and an integrated web-based application. The capital allowance expert system covers the entire process of capital allowance assessment, leveraging rules and procedures extracted from standardised processes and expertise. The tax coding system automatically classifies textual costing items into corresponding tax codes, addressing the complexity of capital allowance rules and frequent legislative changes. The integrated web-based application offers an interactive experience for data gathering, analysis, coding, and report generation, providing a comprehensive solution for efficient and accurate capital allowance assessment. This automated system addresses the complexities and inefficiencies associated with manual capital allowance assessment. It potentially benefits tax authorities in standardising and streamlining allowance assessment processes while fostering economic growth through accessible services for SMEs and promoting environmental sustainability by encouraging energy-efficient practices.
URI: https://bura.brunel.ac.uk/handle/2438/29340
DOI: https://doi.org/10.1109/ACCESS.2024.3393830
Other Identifiers: ORCiD: Javad Gholizadeh https://orcid.org/0009-0009-0561-7089
ORCiD: Kwang-Sung Chun https://orcid.org/0009-0000-7560-0025
ORCiD: Clive Curd https://orcid.org/0009-0009-7507-3582
ORCiD: David Gibson https://orcid.org/0009-0002-7953-5368
ORCiD: Yongmin Li https://orcid.org/0000-0003-1668-2440
Appears in Collections:Dept of Computer Science Research Papers

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