Efficacy of artificial neural network for financial literacy prediction
Sood Meenakshi1, Bhushan Puneet2
1Assistant Professor, Department of Electronics and Communication Engineering, Jaypee University of Information Technology Waknaghat, Solan, Himachal Pradesh
2Assistant Professor, University Business School Himachal Pradesh University, H.P
Online published on 5 December, 2018.
Financial forecasting is becoming more and more dependent on advanced computer techniques due to high non-linearity and high volatility nature of finance domains. An Artificial Neural Network (ANN) is the current technique being used that can model flexible linear or non-linear relationship among variables and predict financial data more accurately. Financial Literacy (FL) is a combination of attitude, knowledge, skill and behavior to achieve desired financial goals. FL shows non linear dependencies on various socio demographic attributes which are in turn responsible for FL level of an individual. This paper brings neural networks applications in the financial domain. An attempt has been made in this research work to analyze the usefulness of artificial neural network for predicting FL level of individuals. The classification accuracy of 75% has been achieved through MLPNN that can help in knowing the efficacy of demographic determinants. The studies done in this work show that neural network have great promise for financial applications.
Financial Literacy, Artificial Neural network, Sensitivity, ROC.