Use of Artificial Neural Network (ANN) in Predicting Financial Distress: A Case of Emerging Economy.

  • Rakesh Parkash and Agha Amad Nabi


The objective of the study is to use Artificial Neural Network (ANN) algorithm to identify the important factors those can accurately predict financial distress (FD) of non-manufacturing firms of Pakistan using a panel data of 271 companies from 2013 to 2016.  The results of the study based on Artificial Neural Network established that firm-specific variables (profitability, liquidity and leverage) are very important variable in predicting financial distress. Further the results concluded that sustainable growth rate, going concern (TATA and FCF), earning manipulation and size of the firm play moderately important role in financial distress prediction. On the other hand, macroeconomic indicators (GDP growth and Inflation) contribute least in forecasting financial distress of a firm. This study can assist probable financers, investors and regulators to tell if the firm is viable to an extent that they can invest in it or it might go into FD in the future.