Automating ERP Applications for Taxation Compliance using Machine Learning at SAP Labs

  • Choppadandi A
  • Kaur J
  • Chenchala P
  • et al.
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Abstract

Aim: The inspiration driving this study is to examine the feasibility benefits and challenges of automating ERP applications for charge consistence and to sort out the usage of gadgets in SAP research offices. Methods: Abstract discretionary investigation techniques, for instance, productive composing review content assessment effective examination and master conversation were used. Materials used consolidate educational records institutional disseminations context-oriented examinations and reports. Results: Key results recollect basic declines for work and taking care of time extended certain accuracy and consistency ordinary yearly money hold assets of $500000 and further created charge procedure consistence. Acknowledged issues integrate the complexity of merging quantifiable heterogeneity and stresses over algorithmic tendency. Conclusion: Planning gear fitness into ERP applications offers phenomenal potential for charge consistence by enabling relationship to achieve more essential adequacy accuracy and financial cost speculation reserves. Overseeing testing conditions requires strong legitimate plans and multidisciplinary joint effort. Future assessment should focus in on the flexibility and straightforwardness of electronic charge reporting courses of action.

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APA

Choppadandi, A., Kaur, J., Chenchala, P. K., Nakra, V., & Pandian, P. K. K. G. (2020). Automating ERP Applications for Taxation Compliance using Machine Learning at SAP Labs. International Journal of Computer Science and Mobile Computing, 9(12), 103–112. https://doi.org/10.47760/ijcsmc.2020.v09i12.014

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