Enhanced Audit Techniques Empowered by the Reinforcement Learning Pertaining to IFRS 16 Lease
This work addresses the problem of enhancing accounting audits for IFRS 16 Lease by leveraging reinforcement learning, which could benefit auditors and companies dealing with complex lease contracts. It is an incremental step towards digitalizing and improving audit processes.
This paper proposes using reinforcement learning to enhance accounting audit techniques for IFRS 16 Lease, specifically to improve the assessment of relevance, completeness, and accuracy of financial information. The study aims to demonstrate the possibility and utility of 'gamification' or 'numericalization interpreters' to translate domain knowledge into numerical systems.
The purpose of accounting audit is to have clear understanding on the financial activities of a company, which can be enhanced by machine learning or reinforcement learning as numeric analysis better than manual analysis can be made. For the purpose of assessment on the relevance, completeness and accuracy of the information produced by entity pertaining to the newly implemented International Financial Reporting Standard 16 Lease (IFRS 16) is one of such candidates as its characteristic of requiring the understanding on the nature of contracts and its complete analysis from listing up without omission, which can be enhanced by the digitalization of contracts for the purpose of creating the lists, still leaving the need of auditing cash flows of companies for the possible omission due to the potential error at the stage of data collection, especially for entities with various short or middle term business sites and related leases, such as construction entities. The implementation of the reinforcement learning and its well-known code is to be made for the purpose of drawing the possibility and utilizability of interpreters from domain knowledge to numerical system, also can be called 'gamification interpreter' or 'numericalization interpreter' which can be referred or compared to the extrapolation with nondimensional numbers, such as Froude Number, in physics, which was a source of inspiration at this study. Studies on the interpreters can be able to empower the utilizability of artificial general intelligence in domain and commercial area.