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

2009 ◽  
Vol 2 (4) ◽  
pp. 17-35
Author(s):  
H. Tawfik ◽  
R. Huang ◽  
M. Samy ◽  
A.K. Nagar
Keyword(s):  
Financial Literacy ◽  
Educational Level ◽  
Credit Card ◽  
Intelligent Systems ◽  
Input Parameter ◽  
Support Vector ◽  
Financial Decisions ◽  
Relative Contribution ◽  
Main Determinants ◽  
And Gender

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.

scholarly journals MILLENNIALS: THEIR FINANCIAL LITERACY AND DECISION MAKING

2020 ◽  
Vol 1 (3) ◽  
pp. 326-340
Author(s):  
Arie Widyastuti ◽  
Ratna Komara ◽  
Layyinaturrobaniyah Layyinaturrobaniyah
Keyword(s):  
Decision Making ◽  
Financial Literacy ◽  
Credit Card ◽  
Significance Level ◽  
Financial Decisions ◽  
Financial Decision Making ◽  
Demographic Profiles ◽  
Gender Education ◽  
Financial Decision ◽  
Mother Education

Millennials are now the largest population groupings in Indonesia, therefore their decisions in financial matters have significant implications for themselves as well as the country’s economy. This paper is aimed to evaluate the level of financial literacy possessed by the Millennials and their attitudes towards making key financial decisions. Data were collected through questionnaire of 30 questions with 15 questions regarding financial literacy and 15 questions related to financial decision making, with the participants in the study consists of 446 individuals who were born from 1980s to 2000s. The result reveals that better financial literacy leads to better financial decision at 1% significance level. This study also indicates that, although demographic profiles such as gender, education, length of working experience, income, number of credit card ownership and mother education have positive correlation with the level of financial literacy, they do not have moderating effect to the financial literacy and financial decision making of the millennials

scholarly journals FINANCIAL LITERACY AND RISK PROFILE: AN EXTENSIVE OBSERVATION ON BANK EMPLOYEES

2021 ◽  
Vol 19 (1) ◽  
pp. 175-186
Author(s):  
Sylviana Maya Damayanti ◽  
◽  
Pramudya Wicaksana ◽  
Keyword(s):  
Financial Literacy ◽  
Financial Management ◽  
Demographic Factors ◽  
Sampling Technique ◽  
Well Being ◽  
Risk Profile ◽  
Financial Decisions ◽  
Bank Employees ◽  
And Gender ◽  
High Level

People with a high level of financial literacy tend to have better financial management skills to realize their financial well-being through effective financial decisions including investing according to their risk profile. The banking industry is an industry that has the highest inclusive level selected because it can represent financial literacy conditions. On the other hand, the gap between financial inclusion and financial literacy leads to a large number of investment (illegal) cases and complaints to regulators. The purpose of this research is to find out the level of financial literacy and type of risk profile, factors that affect it with bank employees in Bandung as research objects. The sampling technique used is a non-probability sampling technique that is purposive sampling with a total of 408 respondents. Data collection is through online questionnaires. There are three sections questionnaire, demographic factors, financial literacy, and risk profile. The data processing techniques used are descriptive statistical analysis and multiple regressions. The results showed that bank employees in Bandung had financial literacy indexes categorized as “medium” or “sufficient” (66.7%) with a risk profile index of “moderate” type (60%). Demographic factors that affect financial literacy are age, education level, and organizational position. While the factor that affects the risk profile is age and gender. Research has also revealed a strong correlation between financial literacy and risk profile.

scholarly journals Determinants and Impacts of Financial Literacy in Cambodia and Viet Nam

2019 ◽  
Vol 12 (1) ◽  
pp. 19 ◽  
Author(s):  
Peter Morgan ◽  
Long Trinh
Keyword(s):  
General Education ◽  
Low Income ◽  
Financial Literacy ◽  
Educational Level ◽  
Occupational Status ◽  
Financial Inclusion ◽  
Viet Nam ◽  
Savings Behavior ◽  
Education Levels ◽  
Main Determinants

Our paper extends the literature on the determinants and impacts of financial literacy by conducting the OECD/INFE survey in two relatively low-income Asian economies—Cambodia and Viet Nam—and analyzing the determinants of financial literacy and the effects of financial literacy on savings and financial inclusion. Generally, our study corroborates the findings of studies of other countries, but uncovers some differences as well. The main determinants of financial literacy are found to be educational level, income, age, and occupational status. Both financial literacy and general education levels are found to be positively and significantly related to savings behavior and financial inclusion, and these results generally hold even when correcting for possible endogeneity of financial literacy.

scholarly journals DETERMINATION of FINANCIAL LITERACY LEVEL: A STUDY on HITIT UNIVERSITY FACULTY of ECONOMICS and ADMINISTRATIVE SCIENCES STUDENTS

2021 ◽  
Vol 10 (4) ◽  
pp. 29-41
Author(s):  
Selcuk Kendirli ◽  
◽  
Muhammet Selcuk Kaya ◽  
Aykut Isleyen ◽  
◽  
...  
Keyword(s):  
Financial Markets ◽  
Financial Literacy ◽  
Credit Card ◽  
Internet Banking ◽  
University Faculty ◽  
Price Bubbles ◽  
Significant Relationships ◽  
Literacy Level ◽  
The Difference ◽  
And Gender

Financial literacy is the level of financial knowledge, attitude and behavior that enables individuals to manage their income, expenses and assets in a way that does not cause financial problems both today and in the future. As individuals' financial literacy levels increase, unnecessary consumption and waste of resources will decrease and the efficiency of investments will increase. Increasing the level of financial literacy will ensure a more balanced formation of asset prices in financial markets and prevent the formation of price bubbles in the markets. Today, financial markets around the world are almost integrated, financial transactions have become possible quickly through portable electronic devices. In this environment, the difference in welfare between individuals and societies with financial literacy and individuals and societies without financial literacy has increased more than in any other period in history. This study, it is aimed to measure the financial literacy level of the students of Hitit University Faculty of Economics and Administrative Sciences located in the province of Çorum. The data of the study were obtained from a questionnaire with the participation of 400 students studying in 5 different departments. By using the percentages of the correct answers given to the questions, success scores were created based on departments. With the help of the T-test and ANOVA tests, the relationship between students' financial literacy and whether they use department, gender, class, and credit card was determined. As a result of the study, it was determined that there are significant relationships between the departments and classes in which students study and their financial literacy, and no significant relationships were found between their credit card and internet banking usage and gender and financial literacy.

scholarly journals AWARENESS ON PENSION PLANS-A STUDY OF INVESTORS’ IN BENGALURU CITY

2021 ◽  
Vol 9 (2) ◽  
pp. 1017-1021
Author(s):  
Pushpa B.V.
Keyword(s):  
Financial Literacy ◽  
Economic Status ◽  
Pension Plans ◽  
Willingness To Participate ◽  
Defined Contribution ◽  
Financial Decisions ◽  
Defined Contribution Plans ◽  
Income Adequacy ◽  
To Come ◽  
And Gender

Individuals make inconsistent, irrational financial decisions mainly due to disproportionate time preferences. Bias and procrastination prevail. Along with a default option, there is a need for a customized plan with individuals' socio-cultural and economic status.  Low participation rates are mainly due to a lack of awareness of pension literacy and behavioral aspects. Individuals have failed to create a corpus to protect themselves for retirement as there is a lack of awareness to suitability of a plan to one’s situation, failure to measure income adequacy at retirement, not able to identify the link between contributions made and pension drawdown, etc. Age and gender differences prevail strongly. Defined contribution plans are likely to dominate in global pension model in the years to come. Individuals are ready to own their risk but have little control and knowledge to cover themselves. Frequent timely and prompt advice or counseling from investment advisors will enable participants to understand the need, identify suitable options and schemes, and provide themselves with sustainable long-term savings. This should convert willingness to participate to real participation. Keywords: Financial literacy, Pension knowledge, Defined contribution pension plans (DCP), irrational decision making, demographics.

Factors Affecting Financial Literacy of Vietnamese Adults: A Case Study for Hanoi and Nghe An

2017 ◽  
Vol 33 (2) ◽  
Author(s):  
Tue Nguyen Dang
Keyword(s):  
Higher Education ◽  
Multiple Regression ◽  
Financial Literacy ◽  
Urban Areas ◽  
Logistic Models ◽  
Factors Affecting ◽  
Financial Behaviors ◽  
Financial Decisions ◽  
Literacy Level

This research examines the factors affecting the financial literacy of Vietnamese adults. Using a sample of 266 observations of adults in 2 big cities in Vietnam (Hanoi and Vinh in Nghe An Province), the author evaluates the literacy level of adults in these urban areas. The financial literacy of the interviewed people is low. The multiple regression results show that lower financial literacy levels associate with higher age and married status and higher financial literacy levels associate with higher education, more family members, the person making financial decisions and the person attending a useful financial course. This research also explores the association between financial literacy and financial behaviors of individuals employing logistic models. It is found that higher financial literacy associates with less probability of overspending and higher probability of saving money and careful spending. Higher financial literacy is also found to associate with higher probability of opening a savings account and making various investments. 

Financial Literacy among Rural Women in Darbhanga District:An Empirical Evidence.

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Prof. F.B. SINGH ◽  
POOJA JHA
Keyword(s):  
Empirical Evidence ◽  
Rural Women ◽  
Financial Literacy ◽  
Rural Population ◽  
Current Status ◽  
Financial Decisions ◽  
The World ◽  
Current Scenario

Financial Literacy is defined as the possession of knowledge and understanding of elementary financial concepts which results in developing the ability to make conversant, poised and effective financial decisions. In current scenario, the concern to increase the level of financial literacy among common masses has been witnessed by many countries of the world through various Financial Literacy center, programme and initiatives but all these programmes and policies are crafted and implemented taking into consideration the male as ultimate receiver and so women who constitute half of the rural population are lagging behind in terms of a making informed financial decisions and financial wellbeing. Hence Strategies should be formulated taking into consideration the women as the main spectators. This paper is an attempt to analyze the current status of the financial literacy among the rural women of the Darbhanga district.

scholarly journals Exploring Impact of Age and Gender on Sentiment Analysis Using Machine Learning

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 374 ◽  
Author(s):  
Sudhanshu Kumar ◽  
Monika Gahalawat ◽  
Partha Pratim Roy ◽  
Debi Prosad Dogra ◽  
Byung-Gyu Kim
Keyword(s):  
Machine Learning ◽  
Sentiment Analysis ◽  
Short Term Memory ◽  
Age Groups ◽  
Modern World ◽  
Support Vector ◽  
Digital Information ◽  
Age And Gender ◽  
And Gender ◽  
The Impact

Sentiment analysis is a rapidly growing field of research due to the explosive growth in digital information. In the modern world of artificial intelligence, sentiment analysis is one of the essential tools to extract emotion information from massive data. Sentiment analysis is applied to a variety of user data from customer reviews to social network posts. To the best of our knowledge, there is less work on sentiment analysis based on the categorization of users by demographics. Demographics play an important role in deciding the marketing strategies for different products. In this study, we explore the impact of age and gender in sentiment analysis, as this can help e-commerce retailers to market their products based on specific demographics. The dataset is created by collecting reviews on books from Facebook users by asking them to answer a questionnaire containing questions about their preferences in books, along with their age groups and gender information. Next, the paper analyzes the segmented data for sentiments based on each age group and gender. Finally, sentiment analysis is done using different Machine Learning (ML) approaches including maximum entropy, support vector machine, convolutional neural network, and long short term memory to study the impact of age and gender on user reviews. Experiments have been conducted to identify new insights into the effect of age and gender for sentiment analysis.

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