On the Use of Intelligent Systems for the Modelling of Financial Literacy Parameters

On the Use of Intelligent Systems for the Modelling of Financial Literacy Parameters

H. Tawfik, R. Huang, M. Samy, A.K. Nagar
Copyright: © 2009 |Pages: 19
DOI: 10.4018/jitr.2009062902
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Abstract

Research has shown that more young people lack good financial literacy and make poor financial decisions. Financial literacy is not only important for individuals, but also for families, financial institutions, and the entire economy. In this paper, artificial neural networks (ANNs) and support vector machines (SVMs) are used as tools to model the financial literacy levels of young university students across Australia and three Western European countries. The goal was to ascertain the students’ level of financial knowledge in relation to the use of credit card and loan facilities based on a number of input parameters such as age, gender and educational level. Sensitivity analysis is applied to determine the relative contribution of each input parameter to the overall financial literacy model. The experiments show that ANNs and SVMs exhibit promising results and capabilities for effectively modeling financial literacy. Our findings indicate that the main determinants of young people’s level of financial literacy include educational level, length of employment, age, and credit card status – in terms of the use of credit card facilities, and gender, living status and credit card status – in terms of the use of loan facilities.
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1. Introduction

Literature has shown that financial literacy is an important issue in many countries including developed and Western societies. The substantial cost of low level of financial literacy for the society has been identified in (Joo & Garman, 1998; Cutler & Devlin, 2000) and has been clearly substantiated by the current global financial meltdown. Organizations including banks, government agencies, and interested groups are concerned about their customers not having the ability to make informed judgments and to take effective decisions regarding the use and management of money (Schagen & Lines, 1996). The lack of financial skill does not only affect an individual’s or a family’s day-to-day use of money, but also the ability to plan for long term goals such as buying a house or retirement. Poor financial literacy can, over a long period, lead to severe regional or even global financial crises.

Financial literacy is defined as the ‘ability of an individual to make informed judgments and to take effective decisions regarding the use and management of money’ (ASIC, 2003; Noctor et al., 1992). Anthes and Bruce (2000) states that it includes the ability to read, analyze, manage and communicate about the personal financial conditions that affect an individual’s well being. As a result, this study has considered a number of important issues, namely the individual, level of financial knowledge and informed judgments. In terms of the individual, one has to consider that everybody does not require the same level of financial knowledge. With respect to the level of knowledge and informed judgments, it is important to be aware that developed societies such as Australia, the UK and the USA tend to have complex financial services aimed at addressing diverse financial needs. However, some of these services, more often than not, appear too complex to be useful to the average user.

The issues surrounding the financial literacy measurement are of a complex nature due to factors such as demographics, language, income levels, culture, age, and sex. Extensive research in the US (Chen & Volpe, 1998), the UK (Schagen & Lines, 1996), and Australia (Roy Morgan Research, 2003) has revealed a number of social factors that affect the level of financial literacy of single parents, students and low level of income earners.

This paper presents a model of the financial literacy levels of young university students with the aim of highlighting the growing importance of financial literacy as indicated in a number of related studies. The project extends researches initially carried out in Australia with a focus on the Australian society’s knowledge of financial issues by extending the sample study to include three Western European countries namely UK, Spain, and Portugal. The perimeters of financial literacy in this study focus on understanding the literacy of youths in different societies with respect to prudent use of credit card and loan facilities.

Our approach is to use two intelligent systems techniques – ANNs, and SVMs as tools to model the financial literacy levels of young university students from four different countries in order to better understand the relationship between financial literacy determinants and overall financial literacy output in relation to knowledge about credit card and loan facilities. Sensitivity analysis is applied to determine the relative contribution of each determinant to the overall financial literacy output.

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