Opportunities of Machine Learning Algorithms in the Tax Default Prediction - A Survey

To develop the countrywide revenue plans, the tax prediction activities should be monitored and activated efficiently. This research study concentrates on the survey of various Machine Learning (ML) algorithms to find better solutions. Financial profit ratios and revenue flow statements have been used to find similar occurrences like income manipulations, false cash flows, and the relationship between tax risk and profitability ratio. Also, this research study addresses the financial suggestions of unpaid taxes by practicing an automated technique to anticipate tax default. In the previous analyses, tax default prediction has attained very small consideration. Findings suggested that the existing analyses were unable to predict the information on tax default in the real-world economic data because it fails to report for appropriate data exchanges as well as non-linear relations among tax default behaviours and prior-warning financial indicators. This study aims to predict the best solution for forecasting tax default using cutting-edge ML techniques.