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Samy, Martin
Tawfik, H.
Huang, R.
Nagar, A. K.
Year of Publication: 
[Journal:] International Journal of Economic Sciences and Applied Research [ISSN:] 1791-3373 [Volume:] 1 [Year:] 2008 [Issue:] 1 [Pages:] 55-70
This paper reports on the potential use of Neural Network as a sensitivity modeling tool for the determinants of financial literacy. The financial literacy modeling in this research has been attempted to measure the literacy of youth in the Australian society with respect to their financial knowledge of Credit Cards, Loans and Superannuation (Pensions scheme in Australia that allows for choice of funds and investment decisions by the member). Based on the financial literacy related parameters, Neural Networks results showed good promise and capability for efficient financial literacy determinants, and represent a potentially robust and fault tolerant approach. The findings indicate that the determinants of credit card are significantly dependent on a student's year of study, credit card status and daily routine, which has a strong relevance to respondents' knowledge of credit cards. (n=1070; 9.0070 and 10.5898 respectively). This study did not have the intention to explore the skills of youth in order to measure the level of financial literacy but the objective was to test the basic financial knowledge of key products that is common to youth in Australian society. In so doing, the researchers were keen to identify the determinants of financial knowledge.
Financial literacy and/or knowledge
youth finance
credit cards
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