Financial Literacy and Its Impact on Fraud Detection of Indonesia's Generation Z
Daffa Rialdo Davis1*
1 School of Business and Management, Bandung Institute of Technology, Bandung, Indonesia
*Corresponding Author: [email protected] Accepted: 15 September 2022 | Published: 1 October 2022
DOI:https://doi.org/10.55057/ajafin.2022.4.3.5
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Abstract: Everyone in the world had to adjust their way of life during the Covid-19 epidemic, since lockdown and quarantine measures were enacted in the majority of countries. As a result, social engagement and communication were forced to take place through the internet.
Consequently, as in the case of Indonesia, the number of internet users expanded dramatically over this time period. With an increase in internet users and activity comes an increase in financial fraud. According to this study, Financial literacy has an effect on someone's capacity to spot fraud. From investigating through various literature and conducting surveys, Individuals with a high score in both financial knowledge and behavior have a better capacity to identify fraud. It might also be claimed that Indonesia's youth generation have financial literacy knowledge and skills. As technology advances, more research with the inclusion of digital literacy may be conducted. This will help people to get understanding of the digital world as well as financial expertise.
Keywords: financial literacy, financial fraud, financial knowledge, Indonesia
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1. Introduction
During the Covid-19 pandemic, everyone in the world had to change their form of life as lockdown and quarantine rules were imposed in the majority country in the world. Countries had these rules implied as a way to reduce physical interaction in the effort to decrease infections and the spread of the Covid-19 virus. As a consequence, social interaction and communication had to be done through the internet. Remote working or work-from-home, online school, online shopping, and social networking are examples of the effect of this transition.
“In 2019, 4.1 billion people (or 54 percent of the world’s population) were using the Internet. Since then the number of users has surged by 782 million to reach 4.9 billion people in 2021, or 63 per cent of the population. In 2020, the first year of the pandemic, the number of Internet users grew by 10.2 per cent, the largest increase in a decade, driven by developing countries where Internet use went up 13.3 per cent. In 2021, growth has returned to a more modest 5.8 per cent, in line with pre-crisis rates. Between 2019 and 2021, Internet use in Africa and the Asia-Pacific region jumped by 23 per cent and 24 per cent, respectively. Over the same period, the number of Internet users in the least developed countries (LDCs) increased by 20 per cent and now accounts for 27 per cent of the population.” (ITU, 2021)
Ultimately, the number of internet users increased tremendously during this period of time, like in the case found in Indonesia. The number of internet users in Indonesia has skyrocketed during the time of lockdown that was imposed amidst the Covid-19 pandemic. The Indonesia Internet Service Providers Association, or APJII, conducted a survey on the number of people using the internet. The result stated that 196 million or nearly 73.7 percent of the Indonesian population have used the internet in 2020. Which is approximately 8.9 percent of an increase from the year 2018. From this figure there are 23 percent of users are Generation Z which are within the age range of 15 and 24 (APJII, 2020).
“The enforcement of social distancing, lockdowns and other measures in response to the COVID-19 pandemic has led consumers to ramp up online shopping and use of social media and of other means of digital communication. Online e-commerce platforms have registered significant growth since the start of the pandemic. Amazon, a US-based e- 3 commerce company, announced revenues of US$ 75 billion in the first three months of the year, averaging US$ 33 million an hour. MercadoLibre, Latin America’s leading ecommerce technology company, reported a 70.5 per cent year-over- year increase in net revenue in the first quarter of 2020. The Chinese e-commerce giant Alibaba reported that its sales grew by 22 per cent in the first three months of 2020, despite virus-related restrictions denting activity.” (World Trade Organization. 2020) The utilization of financial technology applications in Indonesia also went on an upward trend.
Bank Indonesia has reported that, Digital transactions have increased 37.8 percent on a yearon- year basis, this includes bank transfer and digital banking. (Kompas, 2020). E-commerce accounts for 72.73 percent of all digital economy transactions in Indonesia. According to Indonesia's Coordinating Minister for Economic Affairs, Airlangga Hartarto, e-commerce is a big contribution to the country's rapid digital economy growth. (Jakarta Globe, 2021). With the growing number of internet users and activity comes also an increasing number of financial fraud activities. During the Covid-19 pandemic, one out of three people experiences online fraud in Southeast Asia. Between January and September 2020, the second most common kind of case reported in police reports was internet fraud, In Indonesia. (Jakarta Post, 2021).
Figure 1: Cyber Crime trend in Indonesia
The Indonesian National Police's Criminal Investigation Agency has seen an upsurge in cybercrime reports. From 2015 to 2019, there was an increase in cybercrime in Indonesia. In the previous six years, the Patrolisiber portal has received 25,759 public complaints, resulting in a total loss of IDR 5.05 trillion. Internet fraud is the most prevalent sort of crime. There were a total of 8,541 reports of internet fraud. (Christianingrum and Aida. 2021). The number of fraudulent acts could be very harmful to the Indonesian market, not only in terms of actual loss but also in terms of consumer trust and willingness to use financial products and services.
According to CNN Indonesia (2021), the Ministry of Communications and Informatics, or KOMINFO, is now implementing Digital Literacy efforts to educate the public on the safety of utilizing digital media. This Digital Literacy exercise is conducted by the Ministry of Communications and Informatics' National Digital Literacy Movement to educate the public
about digital media safety, digital media ethics, digital media culture, and being skilled in digital media. This paper is intended to study the impact and importance of Financial literacy to a person's ability to detect fraud. Fraud detection in this case would be measured by an aspect of financial literacy which is financial knowledge. Financial knowledge may help an individual distinguish between legitimate and fraudulent information, making them more alert to fraud risk, minimize their relative ignorance to frauds, and foster more efficacy in detecting fraud.
Prudent financial activity can lessen an individual's vulnerability to being a victim of fraud.
Financial knowledge may equip individuals with the skills needed to raise their awareness of fraudulent behaviors, strengthen their detection performance, and enable them to resist fraud.
(Engels, Kumar and Philip. 2019).
Research Question
Based on the background that has been stated previously in the beginning of this paper, these are the research question that are going to be answered in this research:
1) Does Financial literacy have an effect on fraud detection?
2) How does financial literacy affect Indonesia’s Generation Z?
Based on the research question and background that has been stated previously in this paper, the main research objective is to analyze the impact of financial literacy on fraud detection, which focuses on the subject of Generation Z of Indonesia. The research aims to find how and in what ways does financial literacy have the ability to influence an act of fraud prevention.
2. Literature Review
2.1 Financial Literacy
According to Abdeldayem (2016), financial literacy is the capacity to understand how money works in today's society, as well as how a person manages and invests their money. Financial literacy is described as the capacity to comprehend and apply basic economic and financial ideas, as well as the ability to manage financial resources using that knowledge. While PACFL (2008) describe that financial literacy is the capacity to efficiently manage financial resources using knowledge and skills for a lifetime of financial well-being. There also stated that financial education is the process by which individuals develop their knowledge of financial goods, services, and ideas so that they can make educated decisions, prevent hazards, understand where to get assistance, and take additional measures to enhance their current and long-term financial health.
Engels, Kumar, and Philip (2019) investigate whether financially literate individuals are better able to estimate fraud risk and detect fraud incidents due to increased financial knowledge and cautious financial conduct. They discover substantial evidence in the case of financial knowledge but not in the case of financial behaviors linked to fundamental money management.
More particular, the findings show that the stronger an individual's financial expertise, the better his or her ability to spot fraud. This supports the theory that as people gain financial expertise, they get better at spotting fraud when it occurs. The financial expertise required to identify fraud is provided by financial knowledge. Anderson (2016) conducted an experiment in which they observed the relation of consumer literacy to their understanding at multiple financial marketplaces, they found that literacy significantly affects people's tendency to identify fraudulent advertisements. Furthermore, Andreou and Philip (2018) discover that the financially literate among the younger population have a considerably higher inclination than their peers to decline an offer to participate in a Ponzi or fraudulent scheme after being approached.
2.2 Fraud
Fraud is defined as the act, process, or method of misleading, deceiving, or deceiving objects.
Fraud may be defined as an act or words committed by someone who is dishonest or lying with the purpose to mislead or outwit another person for the profit of himself or a group. (Aryyaguna, 2017). Furthermore, Fraud is an act of deceit, a sequence of lies, a false name, and a false scenario committed with the goal of enriching oneself with no rights. Suite a lie is an arrangement of lies made up of phrases that tell the tale of something as if it were true. Fraud inside organizations is defined as the deliberate concealment or misrepresentation of facts that affects the financial interests of another person(s) while benefiting the perpetrator's financial interests. (Rossouw, Mulder and Barkhuysen, 2000). They also stated that there are three dimensions of fraud, the first one is motive, opportunity, and lack of feelings of guilt. The act of fraud is indefinitely an illegal act that would eventually lead to some sort of penalties like fines and imprisonment. In order to execute fraud, a person must have a strong motivation to carry out the act. Therefore, motive plays a huge role in someone in the act of fraud, despite the known fact that such an act would lead them being punished. The second one is opportunity.
There are three combinations of factors that could create opportunity for someone committing fraudulent activities. To begin, the individual must be in a position of trust or have access to people in positions of trust. Second, in order to defeat the company's control systems, the individual must be familiar with them. Third, the individual should have access to the company's assets. The third dimension of fraud is that the perpetrator's activities should not be impaired by emotions of guilt. It is obvious that a common component of fraud is the lack of emotions of guilt or remorse, which explain why most offenders repeatedly commit fraud. To relieve themselves of such feelings of guilt, perpetrators of fraud should create some type of justification or rationalization to relieve themselves of emotions of guilt that may follow from intentionally engaging in criminal acts of deception.
2.2.1 Financial Fraud
Financial Fraud as defined by Reurink (2018) is an action through which users of the financial market intentionally or recklessly misinform or mislead other market participants with imperfect, false information, or manipulative information. These acts are related to financial products, service or opportunity in investment in a way that is discriminatory. Fligstein and Roehrkasse (2013) stated that financial fraud is best described as illegal deception or manipulation of financial information that happens in financial market activities. Fraud would most likely become more prominent in the next couple of years, this is due to the Covid-19 pandemic and the shutdown of the economy which creates a perfect environment of fraud.
2.2.2 Financial Identity Scams
Financial identity frauds and identity misuse in general are widely acknowledged in the literature to be a substantial and rising hazard to financial systems today. Identity theft is claimed to be the most common and fastest increasing economic crime in a lot of nations.
According to the analysis by Reurink (2018), three types of victims bear the negative repercussions of financial identity frauds. The first are the customers and businesses whose financial identities have been hijacked and misused by fraudsters. This type of victims may have the possibility to bear various negative effects, such as losing money and time investigating the fraud, losing access to credit due to their credit score being disrupted, and psychological and emotional implications. A second category includes merchants and credit issuers who have been deceived into sending money or items in exchange for fake payments.
These organizations typically suffer the expenses of investing in fraud detection systems and may forego potential income as a result of their unwillingness to accept lawful transactions that appear suspicious or as a result of increased customer reluctance to engage in e-commerce. The
final set of victims are banks, credit card firms, and e-commerce sites whose brand identities have been ruined by phishing tactics. Costs connected with greater surveillance and prevention, as well as negative impacts on stock prices and trading volume, may be borne by these corporations.
2.3 Generations Z
According to Mckinsey (2018), Generation Z are the people who are born from 1995 to 2010, on which they are true digital natives. They have been exposed and experiencing the internet, utilizing social networks and have adapted to the mobile system from the moment they come to the world. They did a survey where it was revealed that there are four core behaviors that made up Gen Z, and it all comes to one specific aspect, that is they search for truth. Individual expression and dismissing labels are what they valued. They get together to support a range of issues. They are firm believers in the power of communication to resolve disputes and improve the world. Weinswig (2016) identified three defining attributes of Gen Z, which essentially come from their behavior in adapting to the new technologies. The first one is that this generation places a 14 high value on personal appearance since they are the first generation to grow up "in public" online, i.e., through chronicling their life on social media. Evidence shows that this is causing even young children to use cosmetic products and that it is promoting body consciousness among young people. The second is that social media pressures are also driving Gen Z to spend money on leisure activities such as trips, dining out, and going out. The need to be regarded on social media as living a pleasant, fascinating, experience-rich life which is referred to as "the Instagram effect." The last attribute is, the on-demand economy, which includes everything from video-on-demand services like Netflix to date-on-demand applications like Tinder, is making Gen Z the most demanding, least-patient age ever.
Furthermore, Weinswig (2016) mentioned that in 2015, Gen Z accounted for an estimated 26 percent of the total world population, with that figure predicted to rise to 33 percent by 2020.
According to our research of demographic estimates from statistics offices, the percentage of Gen Z in Western nations is lower: in the US, it was 19 percent in 2015 and is predicted to climb to 25 percent in 2020, while in the EU, it was 16 percent in 2015 and is likely to rise to 21 percent in 2020.
3. Research Design and Methodology
3.1 Research Approach
This study employs quantitative research using a descriptive method. Quantitative research methods are one sort of research in which the specifications are methodical, planned, and explicitly structured from the beginning of the research design to the end. Quantitative research methods, as defined by Sugiyono (2013), are research techniques that are grounded in the positivist philosophy and used to study a specific population or sample. Sampling techniques are typically performed at random, data are collected using research instruments, and data analysis is quantitative or statistical in nature with the goal of testing the established hypothesis.
The analysis here is used to find the effect of financial literacy on the awareness of financial fraud. In order to describe the subject of the study or its findings, this research employs a descriptive methodology. According to Sugiyono (2013), the concept of a descriptive approach is one that uses data or samples that have been acquired in their natural state, without further analysis or drawing generalizations, to describe or provide a description of the thing under study.
3.2 Data Collection
In this research the respondents are consist of Generation Z that live in Indonesia. The survey conducted in online questionnaire form, due to the characteristic of this sample which use often use the internet. Based on the research objective, the respondent criteria need to be determined.
The respondent criteria needed in this questionnaire therefore are:
1) Indonesian Citizen 2) 18-25 Years Old
This research measures how significant one’s financial literacy is to detect fraud, but in order to access a comprehensive data other attributes must be retrieved. Individual characteristics, such as age and gender, as well as socio-economic characteristics, such as education and income, are collected in the first section of the questionnaire. The second part of the survey would be around financial literacy and fraud detection. For the Financial literacy, level of financial knowledge and skill, as well as respondent’s financial attitudes and behavioral traits are also being collected in the survey. Wordings of financial literacy questions are listed in the table 1.
Table 1: List of Questions
Variable Dimensions Items Reference
Financial Literacy
Financial Knowledge
and Skills
I know how to use financial goods and services.
Utami and Sitanggang (2021) I know how to invest
I am capable of calculating financial transaction gains and losses.
I am capable of calculating return on investment
Financial Behaviors and
Attitude
I spend money based on my financial budget that I made
I consider the steps that I need to do to stay on track with my budget.
I set financial goals for myself in terms of what I want to accomplish with my money.
To reach my financial goals, I create a clear plan of action with specific stages.
Financial Fraud
Has someone used or attempted to use an existing account of yours, such as a credit or debit card, bank or savings account,
telephone, internet, or insurance account, without your consent in the last 5 years?
Engels, Kumar, and Philip (2019)
In the question that was used by Engels, Kumar, and Philip (2019) with the intention to evaluate respondent’s detection of fraud, Respondents were given three options for answers: "Yes,"
"No," and "I don't know." The survey answer is unable to clearly identify the circumstance where the respondent is experiencing more or less fraud since additional follow-up questions on the detail and frequency of the fraud were not asked. To obtain a better idea of an individual's fraud detection skill, look at the conditional outcome space, which shows whether or not the person is able to identify fraud if he or she is targeted for it. That is, the research necessitates the observation of attempted deception. However, whether or whether an individual has been targeted for fraud is unobservable in non-experimental data such as surveys. As a result, this study makes the implicit assumption that everyone has a same chance of being targeted for fraud and then investigates whether they can identify fraud if they are targeted. This presumption is logical, given the huge rise in fraud victimization in recent years, with fraudsters seeking for susceptible people at random to catch those who fall prey to their schemes.
Furthermore, large-scale data breaches of corporations holding sensitive customer data have made individuals across the population vulnerable to fraud. Thus, it is likely that the respondents in our representative sample of households have all been subject to fraudulent attempts in the previous five years. Therefore, interpret the responses to the survey question above as capturing fraud detection.
3.3 Data Analysis
The participants in this study were members of Generation Z in Indonesia. Data was collected, translated, and coded before being entered into Microsoft Excel. After data has been transferred to Excel, the data then could be examine using IBM SPSS. To understand the characteristics of the respondents, descriptive statistics were used to identify the sample profile. Then each variable is analyze using the frequencies analysis. Frequencies analysis is used as a way to shows the number of occurrences of each response chosen by the respondents. In this part multiple variables are presented as the number of responses chosen by the respondents.
3.4 Validity and Reliability Test
The validity test was conducted with the aim of measuring the validity or invalidity of a questionnaire. According to Sugiharto and Sitinjak (2006), validity relates to a variable that measures what it is supposed to measure. Validity in research states the degree of accuracy of research measuring instruments to the actual content being measured. A questionnaire is said to be valid if the questions or statements on the questionnaire are able to reveal something that will be measured by the questionnaire (Ghozali, 2016). Each measurement variable is put to the test to see if it complies with the theory. If an indicator has a corrected item total correlation value ≥ 0.30, it is considered to be valid (Sekaran, 2000). The reliability test, according to Ghozali (2016), is a method to assess a questionnaire that serves as an indicator of a variable.
When a respondent's response to a question is consistent or stable throughout time, a questionnaire is said to be dependable or reliable. To determine how well the questionnaire items were connected to one another in this study, the internal consistency reliability technique using the Cronbach Alpha test was utilized. If a construct or variable has a Cronbach Alpha value greater than 0.70, it is considered dependable (Ghozali, 2016)
4. Findings
4.1 Validity and Reliability test result
Each question on the questionnaire has been determined valid since it falls within the range of 0.429 and 0.560, as shown in more detail in the table 2.
Table 2: Validity test
Item/Question
Corrected Item-Total Correlation
Conclusion
I know how to use financial goods and services 0.530 Valid
I know how to invest 0.537 Valid
I am capable of calculating financial transaction gains and losses 0.517 Valid
I am capable of calculating return on investment 0.559 Valid
I spend money based on my financial budget that I made 0.429 Valid I consider the steps that I need to do to stay on track with my budget 0.430 Valid I set financial goals for myself in terms of what I want to accomplish
with my money 0.480 Valid
To reach my financial goals, I create a clear plan of action with
specific stages 0.560 Valid
The value of Cronbach’s Alpha in this test is 0.795, this indicates that it is reliable, as shown in more detail in the table 3.
Table 3: Reliability test
Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on
Standardized Items N of Items
0.795 0.797 8
4.1 Descriptive analysis
Based on the table 4, the percentage of male respondents is 47.1 percent, on the other hand the female respondent’s is 52.9 percent. There are not any abnormality figures regarding these categories. For defining the age of the respondent, it is divided into three range, 14 - 17 years old, 18 - 21 years old, and 22 - 25 years old. In this category, there is a significant number in the range age of 18 - 21 years old, which at a percentage of 84.7 percent. Follow with the age range of 22 - 25 years old with 11.8 percent, and 14 - 17 years old range with 3.5 percent. This similarity in figures also could be seen in the next attributes which is the respondent’s category.
This attribute is divided into three categories, student, university student, and employee. The result show that, the majority of respondent are currently a university student with a percentage of 83.5 percent. The second category is student with 12.9 percent and the last with 3.5 percent is employee. Moving on to the respondent current education background, the most prominent figures could be seen in the percentage of respondent who are currently studying for undergraduate degree. It is sum up to 74.1 percent. Respondent who are currently pursuing senior high school come in second with 17.6 percent, follow by master degree with 4.7 and junior high school degree with 3.5 percent. The last demographic attributes for the sample profile are regarding respondent monthly income. The result for this attribute is fairly spread out throughout the categories. The categories are range of the monthly income that respondents gain. There are four categories, the first one is less than Rp 1 million, the second one between Rp 1 million and Rp 2.5 million, the third one between Rp 2.5 million and Rp 5 million, and
the last is more than Rp 5 million. From these attributes the highest percentage is the monthly income of less than Rp 1 million with the percentage of 32.9 percent.
Table 4: Respondent’s Demographic
Demographic attribute Categories Count Percentage
Gender
male 40 47.1
female 45 52.9
Age
<17 years old 3 3.5
18 - 21 years old 72 84.7
22 - 25 years old 10 11.8
Occupation
Student 11 12.9
University Student 71 83.5
Employee 3 3.5
Current Education Background
Junior High School 3 3.5
Senior High School 15 17.6
Undergraduate 63 74.1
Master 4 4.7
Monthly Income
< Rp 1,000,000 28 32.9
Rp 1,000,000 - Rp 2,500,000 23 27.1
Rp 2,500,000 - Rp 5,000,000 21 24.7
> Rp 5,000,000 13 15.3
The second analysis that are conducted is the level of financial literacy. In this part there are 8 questions that measure the financial literacy, these questions are divided into two categories, financial knowledge and abilities, and financial behavior and attitudes. Each of the categories has 4 questions. The first four questions are for the financial knowledge and the rest are for financial behavior. According to table 5, The first question asks for respondent knowledge on usage of financial goods and services, and the highest result among the respondents are 44.7 percent for the scale of agree. For the second question, mentioning the knowledge of investing, the result is fairly distributed along the scale of disagree, neutral, and agree. With the correspondent percentage of 29.4, 25.9, and 28.2 percent. The third question, the highest data is on the agree categories with 38.8 percent. Moving on to the fourth question, the highest
categories is neutral with 31.8 percent followed by disagree at 28.2 percent. The last four question is surrounding the financial behavior of the respondents. For the question, I spend money based on my financial budget that I made, 38.8 percent said that they agree with the statement. The next two question, question 6 and 7, the amount of respondent who response with the statement agree are high in both cases with 48.2 and 36.5 percent respectively. The final question state on the level of creating plan on financial goals, with the highest percentage of 37.6 stating that they were neutral on the statement.
Table 5: Financial literacy scale
Financial Literacy Scale Count %
I know how to use financial goods and services
Strongly disagree 0 0
Disagree 4 4.7
Neutral 16 18.8
Agree 38 44.7
Strongly agree 27 31.8
I know how to invest
Strongly disagree 5 5.9
Disagree 25 29.4
Neutral 22 25.9
Agree 24 28.2
Strongly agree 9 10.6
I am capable of calculating financial transaction gains and losses
Strongly disagree 1 1.2
Disagree 13 15.3
Neutral 23 27.1
Agree 33 38.8
Strongly agree 15 17.6
I am capable of calculating return on investment
Strongly disagree 7 8.2
Disagree 24 28.2
Neutral 27 31.8
Agree 15 17.6
Strongly agree 12 14.1
I spend money based on my financial budget that I made
Strongly disagree 1 1.2
Disagree 11 12.9
Neutral 22 25.9
Agree 33 38.8 Strongly agree 18 21.2
I consider the steps that I need to do to stay on track with my budget
Strongly disagree 0 0
Disagree 5 5.9
Neutral 19 22.4
Agree 41 48.2
Strongly agree 20 23.5
I set financial goals for myself in terms of what I want to accomplish with my money
Strongly disagree 0 0
Disagree 5 5.9
Neutral 20 23.5
Agree 31 36.5
Strongly agree 29 34.1
To reach my financial goals, I create a clear plan of action with specific stages
Strongly disagree 2 2.4
Disagree 15 17.6
Neutral 32 37.6
Agree 22 25.9
Strongly agree 14 16.5 Based on the result that could be found in table 6, the statement on the knowledge on usage of financial goods and service receive the highest score from all the question that been asked. With the score mean score of 4.04. The second highest level on the survey statement is the statement
“I set financial goals for myself in terms of what I want to accomplish with my money”. The mean score is 3.99 on this statement. The statement with the least amount of mean score is the capability in calculating return on investment. The mean score is at 3.01.
Table 6: Item’s statistic
Question Mean Std. Deviation Max Score
I know how to use financial goods and services 4.04 0.837 5
I know how to invest 3.08 1.115 5
I am capable of calculating financial transaction
gains and losses 3.56 0.993 5
I am capable of calculating return on investment 3.01 1.17 5
I spend money based on my financial budget that I
made 3.66 0.995 5
I consider the steps that I need to do to stay on
track with my budget 3.89 0.831 5
I set financial goals for myself in terms of what I
want to accomplish with my money 3.99 0.906 5
To reach my financial goals, I create a clear plan
of action with specific stages 3.36 1.033 5
The last analysis that would be conducted is a cross tabulation between variable of financial literacy and fraud detection. For this part, Financial literacy aspect were divided by financial knowledge and financial behavior. For this first part, 65 respondents out of 85 mentioned that nobody has attempted to do any fraud to them. While 14 out of 85 respondents said that they do not know if there are anyone who had attempted to commit fraud to them. On the other hand, there are 6 person said that they know if there are someone attempted to do fraudulent activity to them. From the survey, the people that appear to be aware that someone has attempted to do fraud to them are among the highest scoring respondent in the financial knowledge score, all 6 have their score higher than 3.00. From the 65 respondent that say no one has attempted to do fraud activities to them, most of them are in the middle of the score, from 2.75 to 3.75. The data is shown in more detail in the table 7.
Table 7: Financial Knowledge and skills cross tabulation with financial fraud
Has someone used or attempted to use an existing account of yours, such as a credit or debit card, bank or savings account, telephone, internet, or insurance account, without
your consent in the last 5 years? Total
Yes No I don't know
Financial Knowledge
and skills
1.5 0 1 0 1
1.75 0 1 0 1
2 0 2 0 2
2.25 0 4 0 4
2.5 0 3 1 4
2.75 0 7 3 10
3 1 9 1 11
3.25 0 9 2 11
3.5 1 8 1 10
3.75 0 8 0 8
4 0 4 2 6
4.25 0 3 1 4
4.5 1 1 1 3
4.75 2 2 0 4
5 1 3 2 6
Total 6 65 14 85
On this part, the financial behavior is calculated using the same techniques from the previous analysis. The score of financial behavior from the respondents could be see relatively high. For example, with the score of 4, there are 15 out of 65 respondents. From the result it could also be seen that the majority of the respondent scoring above 3.00, This is accounted for the person that said that they did not have anyone trying to fraudulent activities to them.
Table 8: Financial behaviour and attitude cross tabulation with financial fraud
Has someone used or attempted to use an existing account of yours, such as a credit or debit card, bank or savings account, telephone, internet, or insurance account, without
your consent in the last 5 years? Total
Yes No I don't know
Financial Behavior and
Attitudes
1.75 0 1 0 1
2.5 0 3 0 3
2.75 1 2 2 5
3 0 10 1 11
3.25 1 8 2 11
3.5 0 7 2 9
3.75 1 3 1 5
4 1 15 1 17
4.25 2 4 2 8
4.5 0 2 1 3
4.75 0 3 0 3
5 0 7 2 9
Total 6 65 14 85
4.2 Discussion
From the survey that been conducted, there are several figures that could be evaluate. Firstly, from the sample profile that have been analyze. From the survey, the dominating age range is between the age range of 18 to 21 years old. The respondents in this category also translate in the amount of sample that are university student on which the two categories are equal. There is also financial literacy level and its relationship with respondent’s ability to detect fraud. The aspect of financial literacy is being divided between aspect of knowledge and aspect of behavior. In the data, financial behavior overall has the higher score for all respondents, despite the respondents scoring higher on the first statement of the survey, which is in the aspect of financial knowledge. Summing up from the total respondents who are able to detect fraud, its significantly higher than the one who are not aware that someone has attempted to act fraudulently.
5. Conclusion
This study is about the role of financial literacy, that are evaluated within the segmentation of financial knowledge and financial behavior, for the ability to detect fraud. As the trend on fraud keep increasing in the upcoming year, the level of complexity also increases, this mean consumer would have to be more informed regarding their ability to detect fraud. The level of complexity in here could be related to the level of technology and system that these perpetrator use.The study is aiming to discover are there a correlation between one’s financial literacy level to their ability to asses’ fraud and recognize fraudulent activities. Using 85 respondents sample of Indonesia’s Generation Z, this study examines the correlation between these variables.
Generation Z is use as it is one of the most prominent generation in Indonesia, and in the way they utilize the internet on the daily basis. The result of this study indicates that there is strong indication that both financial behavior and financial knowledge indeed makes people more aware of detecting fraud. It also could be said that Indonesia’s young generation possess the knowledge and the ability in financial literacy. This research proposes that there is correlation between financial literacy and fraud detection, further research could be conducted as there are more variables that could be discussed more deeply. As fraudulent become more complex with the advancement of the internet technology, variable like people understanding of digital literacy could be made. This will allow not only the knowledge in financial term but also, people’s knowledge of the digital world.
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