Abstract
Deductions are predominantly the short payments done for a generated invoice usually by the customer as a compensation or for the lack of products or services. Possible reasons for deductions to happen include shortage, damage, late delivery, and other-related factors. The machine learning approach has a huge impact on the deduction domain as eliminates the manual effort of a deduction analyst without compromising much on the accuracy. A deduction analyst can save so much on time as now he/she does not have to go through the complex procedure of deduction validity or invalidity. Also this solution will help in speeding up the business process which will lead to customer satisfaction due to on-time delivery. In this research, various machine learning techniques like LGBM and random forest are used for the analysis. It was observed that LGBM model provided optimum result thereby helping business analysts to take decision with respect to invoice payments.
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Tutica, L., Vineel, K., Mishra, S., Mishra, M.K., Suman, S. (2021). Invoice Deduction Classification Using LGBM Prediction Model. In: Mallick, P.K., Bhoi, A.K., Chae, GS., Kalita, K. (eds) Advances in Electronics, Communication and Computing. ETAEERE 2020. Lecture Notes in Electrical Engineering, vol 709. Springer, Singapore. https://doi.org/10.1007/978-981-15-8752-8_13
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DOI: https://doi.org/10.1007/978-981-15-8752-8_13
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