Consumer’s Perception of Risk of Online Transactions

Consumers cognizance of stake of infection of Online Trans exploitsAbstractThe purpose of this interrogation is to investigate whether a consumers percept of take a chance in transacting on the internet (Perceived Risk) would concord an lure on their bank of a banks e-banking website (Specific Trust) and their automaticness to function e-banking. Data were collected from a survey and a usable sample of 202 was obtained. Hierarchical moderated regression abridgment was employ to examine the exemplification. The results showed that Perceived Risk has a direct watch on a consumers willingness to expenditure e-banking and Specific Trust has a verificatory moderating influence on the human likenessship between Perceived Risk and a consumers willingness to pulmonary tuberculosis e-banking. Consumers who select low comprehend endangerment of transacting on the internet atomic physical body 18 generally more(prenominal) than willing to subroutine e-banking. Their willingness to employment e-banking was in like manner shown to be more pronounced in cases where the consumer in any case impudence their banks e-banking website. These purposes argon of particular relevance to banks. It high schoollights that a consumers willingness to intent e-banking primarily depends on their cognition of danger in transacting on the internet assurance of the specialised e-banking website was secondary. This suggests the need for banks to non and employ mechanisms to build blaspheme for their special(prenominal) e-banking website, provided that banks should first take measures to educate their customers and manage general consumer perceptions of the dangers of transacting on the internet.Keywords Trust, Perceived Risk, meshing, E-banking Adoption.IntroductionIn recent years, the advancement in scientific developments in in arrangement technology has lead to the growing of e-banking in the banking industry. The evolution of e-banking has f undamentally transformed the way banks traditionally conduct their businesses and the ways consumers be uphold their banking activities (Eriksson et al., 2008 Sayar and Wolfe, 2007). Today e-banking has experienced phenomenal growth and has become one of the briny avenues for banks to deliver their products and military services (Amato-McCoy, 2005).E-banking reaps benefits for both banks and its customers. From the banks perspective, e-banking has enabled banks to lower operational costs by the reduction of physical facilities and staffing resources required, reduced waiting measures in branches resulting in potential increase in sales manageance and a big global r all(prenominal) (Sargonl and Mamorstein, 2003). From the customers perspective, e-banking allows customers to perform a wide range of banking trans fulfills electronically via the banks website anytime and anywhere (Grabner-Kraeuter and Faullant, 2008). In addition, customers no eternal are restrict to the openi ng hours of banks, travel and waiting times are no longer necessary, and access of randomness regarding banking services are now easily purchasable (Hamlet, 2000). and the success of e-banking isnt without its problems. Firstly the acceptation of e-banking has not kept measure with that of internet wont (White and Nteli, 2004). This orifice is attributed to the lack of self-assurance among bank customers, peculiarly among internet phthisisrs age 65 and older (Ilett, 2005 Perumal and Shanmugam, 2005). Secondly, customers still prefer flavor to face interaction (Asher, 1999) due to reasons such(prenominal) as fear of the online milieu and lack of assertingness in the internet. Recent literature on e-banking showed that the formation of cuss can help reduce the impact of observe inhibiting occurrenceors such as fears about development the online service among non-ebanking customers (Vatanasombut et al., 2008).Moreover, even with the increase usage of e-banking in rece nt years, banks are faced with a conundrum whilst e-banking does need its benefits of convenience and cost savings the ease at which e-banking allows for switching jeopardize to traditional ways of banking consequently reduces long term customer committal (Sarel and Mamorstein, 2003). The commitment-trust hypothesis of Morgan and be given (1994) proposes that trust leads to commitment in relationships, and so, if trust is create amongst personifying customers, over time they will become committed to the e-banking service, trim back the chances of customers jumping ship (Mukherjee and Nath, 2003 Vatanasombut et al., 2008).Evident in prehistorical literature is the fact that take chances plays a role in the formation of trust (Chen and Dhillon, 2003 Pavlou, 2003), but what is not evident is the relationship jeopardize has with trust especially in regards to the perceived risk consumers generate in transacting on the internet. Past inquiry studies into the area of risk put in that it is not objective risk, but perceived risk which matter in the formation of trust (Bauer, 1960 as citied in Bttner and Gritz, 2008 Garbarino and Strahilevitz, 2004). A recent research study piece that, perceived risk is directly related to an individuals bridal of e-banking with many away research studies showing that intention to lend oneself e-banking is often times abnormal by fears of theft or fraud (Gerrard et al., 2006). The relationship between perceived risk and trust is an underdeveloped area in the literature. Past train in the area of trust and perceived risk has not further managed to fully determine the exact relationship which risk has on trust, as whilst risk is necessary for the formation of trust, it is not an antecedent of trust (Chen and Dhillon, 2003). Moreover, trust has been shown in the past to effect perceptions of risk, as well as having mediating effectuate through risk (Pavlou, 2003).Hence the purpose of this research is to investig ate whether a customers perception of risk in the internet would arrive moderating effects on trust and a customers willingness to use e-banking. As noted by Bttner and Gritz, (2008), there is a lack of empirical studies in this area. Moreover by understanding the temper of risk and trust, banks can manipulate the steps necessary on their part to operate that the trust which they behave built in their services will indeed influence customers bankers acceptance and commitment to e-banking.Literature ReviewTrust in E-banking Trust is natural in situations where risk, uncertainty and interdependence exist (Mayer et al., 1995), and the online environment certainly encapsulates these components. In an online environment, there is no direct physical contact between buyer and seller. This spatial distance meaning that consumers cannot use the physical cues, such as observing the sales staff or the physical office/ store space, in order to judge trusdeucerthiness (Reichheld and Sche fter, 2000). Due to the global nature of the internet, consumers and e-retailers often face spatial and temporal separation as a result transactions carried out online often do not implicate a simultaneous transaction of goods (or services) and money (Grabner-Kraeuter, 2002). This delay in time bureau that consumers can become increasingly uncertain whether the otherwise troupe will actually perform their side of the transaction. Another reason for the increased need for trust in the online contexts is consumers fear for the safety of their personal information due to hackers or other harmful possibilities (Hoffman et al., 1999 Yoon, 2002).Apart from the necessities of trust in order to get consumers to purchase online as per the hypothesis of reasoned action (Azjen and Fishbein, 1980), trust is also important for businesses to grow and maintain profitability, as per the commitment-trust theory of relationship marketing by Morgan and Hunt (1994). Past research studies have det ermine that one of the benefits of trust are committed customers (Casalo et al., 2007 Morgan and Hunt 1994). sure repeat customers are super beneficial to organizations, as it is much cheaper to withstand customers than it is to find and attract new customers (Reichheld and Schefter, 2000). In the online arena where substitutes are quickly available, the benefits to businesses of having committed customers are plenty, hence the amount of research into the area (e.g. Casalo et al., 2007 Jarvenpaa et al., 2000 Vatanasombut et al., 2008).numerous research studies have been conducted to identify what grammatical constituents drive or inhibit the adoption of e-banking by consumers (Gerrard et al., 2006 Hernandez and Mazzon, 2007 Lichtenstein and Williamson, 2006 Sayar and Wolfe, 2007). It has been identified that the lack of trust was one of the main reasons why consumers are still reluctant to conduct their financial transactions online (Flavian et al., 2006 Luarn and Lin, 2005 Muk herjee and Nath, 2003Rotchanakitumnuai and Speece, 2003).In order for e-banking to be a viable medium of service delivery, banks instantly must try to narrow the trust gap due to the higher(prenominal) degree of uncertainty and risk in an online environment analysed to traditional settings. query studies conducted examining the role of trust in e-banking (e.g. Vatanasombut et al., 2008 Casalo et al., 2007 Lichtenstein and Williamson, 2006 Rexha et al., 2003 Suh and Han, 2002), show that trust plays a key role in the adoption and continued use of e-banking. moreover, it was found that trust not only affects the intent to use e-banking (Liu and Wu, 2007 Suh and Han 2002), but trust in e-banking has also been found to be an antecedent to commitment in e-banking (Vatanasombut et al., 2008 Kassim and Abdulla, 2006), and is because useful to reduce the perceived risk that consumers feel is present in an online environment (Pavlou 2002).Perceived Risk and TrustPerceived risk is pictur ed as a concept that is complex, multifaceted and dynamic (Zhao et al., 2008, p.506). Perceived risk is defined as a consumers perceptions of the uncertainty and the workable undesirable consequences of buy a product or service (Littler and Melanthiou, 2006). In the online context, past research studies suggest the inclusion of perceived risk due to its importance in influencing online consumer behavior (Cunningham et al., 2005 Pavlou, 2003 Salam et al., 2003 Schlosser et al., 2006) and more so in the area of e-banking (Cunningham et al., 2005).As mentioned earlier, perceived risk is important in the formation of trust (Bauer, 1960 as cited in Bttner and Gritz, 2008 Garbarino and Strahilevitz, 2004). The body of the knowledge on trust has identified that risk is the element which gives cut to the need for trust when engaging in an activity which means that if there were no perceptions of risk, trust would not be necessary to necessitate in an activity, as actions could be taken with perform certainty (Yousafzai, 2003 Chen and Dhillon 2003). There are devil different types of risk that have been identified in relation to trust risks associated with a mate and risks associated with a type of transaction (Bttner and Gritz, 2008). Risks associated with a better half in general are perceptions that a particular interaction partner in a transaction will not perform their end of the bargain, and are formed from perceptions of the attributes of that interaction partner this type of risk should be in return related to trust of that partner (Jarvenpaa et al., 2000). Essentially, the higher the trust one has in a partner, the less perceived risk in dealing with that partner. However, risk associated with a type of transaction has a different association with trust. The more risky a type of transaction is perceived to be, the more trust is required in order to engage in an interaction with that partner (Mayer et al., 1995).The relationship between risk and trus t is a complex one, whilst risk is necessary to the creation of trust, it is not an antecedent to trust which means the nominal head of risk does not automatically equate to the formation of trust (Pavlou, 2002). check to Mayer et al. (1995, p.711) It is unclear whether risk is an antecedent to trust, or is an outcome of trust. Clearly, a gap of knowledge exists in this area, and further research is required so as to determine the relationship which risk has with trust, especially in the context of e-banking.However the area that interests the authors of this research is the work by Pavlou (2002) which found that the effect of trust on transaction intention could be moderated through perceived risk. This is a relationship which was pilot lightly proposed by Mayer et al. (1995), who postulated that the aim of trust needed to engage in a risk taking behavior is influenced by the perception of risk inherent in that behavior. Pavlous (2002) work also called for future research so as to examine the complex interrelationships among trust, perceived risk and behavioral intention to reach definite conclusions. (Pavlou, 2002, p.125). This research aims to answer that call by testing perceived risk in the internet as a moderator in the relationship between a consumers trust in a banks e-banking website and the consumers willingness to use e-banking.Theoretical FrameworkThe investigation of the role of trust in the use of e-banking necessitates the examination of both key theories the theory of reasoned action by Azjen and Fishbein (1980) and the commitment-trust theory of relationship marketing by Morgan and Hunt (1994). The theory of reasoned action states that a persons behavior is determined by their behavioral intent, which is in turn shaped by attitude and subjective norms (Azjen and Fishbein, 1980). increase trust means that when a persons attitudes towards a particular behavior (in this case, use e-banking) are positive, it will potential increase a pers ons intent to perform that behavior. This has been supported by research in both the e-retailing context (Jarvenpaa et al., 2000), and also in the e-banking context (Liu et al., 2005), where trust has been shown to lead to a purchase intention. Further, Morgan and Hunt (1994) purports that by building trust over time, customers become committed to the relationship built, and will subsequently reciprocate with continued business. Past research in this area have extended the applicability of this commitment-trust relationship to the e-banking context (Casalo et al., 2007 Mukherjee and Nath, 2007 Vatanasombut et al., 2008). This gives rise to the first hypothesis for this research which forms the basic relationship between a consumers trust in a banks e-banking website (Specific Trust) and the consumers willingness to use e-banking.H1 Specific trust in e-banking has a direct effect on willingness to use e-bankingPerceived risk is defined in this research as a consumers perceptions of r isk in transactions use the internet, and is hypothesized to have a moderating role in the relationship between particular proposition trust and the willingness to use e-banking. As mentioned preliminaryly in the literature review, there is little empirical research on the moderating effect of risk in the e-banking context. Work by Pavlou (2002) found that the effect of trust on transaction intention could be moderated by perceived risk, but called for further research in this area to confirm the complex interrelationships between these three constructs. Therefore, the authors of this research proposed the second hypothesis asH2 Perceived risk has a negative moderating effect on the relationship between particularised trust and willingness to use e-banking.MethodologyTo test the model, a cross-sectional survey was undertaken using an instrument containing 15 events. The 15 specifics utilize were established collection plates adapted from Doney and Canon (1995), Chow and Hol den (1997), Jarvenpaa et al. (2000), Suh and Han (2002), Kim and Ahn (2006) and Verhagen et al. (2006) measuring specific trust, willingness to use and perceived risk. Great care was taken when adapting the scales to ensure that the original concepts world measured by the scale had theoretical congruence and relevance to this study. Each item is measured on a 7-point Likert scale with 0 denoting the low end and 6 the high end. The questionnaire was then pre tried and true on a non-probability sample of university staff. Refinements were do to the questionnaire based on feedback from the pre-test. All items in the final instrument were then reviewed by marketing academics for content validity.MeasuresThe scale used to measure perceived risk was adapted from a number of scales which have resembling theoretical congruence with the definition of risk perception in the theoretical framework. A few of the items in the scale used was sourced from Verhagen et al. (2006), which measured intermediary risk and was defined as the belief of a probability of suffering a loss due to the inability of the intermediary to provide sufficient protection against fraudulent and/or opportunistic sellers (p.545) which is similar to the definition of the perception of risk on the internet. In that, the consumers belief in a possibility of loss or harm as a result of the medium internet is being measured. The nature of the internet is such that, there is insufficient protection to consumers from fraudulent and/or opportunistic people, and so the use of items from Verhagen et al.s (2006) scale on intermediary risk was appropriate. Other items in the scale were sourced from the work of Jarvenpaa et al. (2000), Kim and Ahn (2006), and Chow and Holden (1997), which measured concepts such as risk perception and web-shopping risk, all of which was similar to the concept of perceived risk being operationalised. Minimal alterations were made to the items due the similarity of the concepts being measured. Whilst it would have been perfection to operationalise the construct of perceived risk in the internet with a uneven scale, but there is a lack of scales in this area (Verhagen et al., 2006), consequently the use of a composite scale was necessary. To measure specific trust in e-banking, items from work of Doney and Canon (1995), Suh and Han (2002) and Jarvenpaa et al. (2000) were adapted. These items were chosen due to their semantics and wording. Items directly relating to interpersonal trust including the service of e-banking, and a belief in the benefits and trustworthiness of e-banking were used as part of the scale. Lastly, in measuring the willingness to use e-banking, items that measure attitudes and intentions towards using e-banking were chosen. Items in the scale were sourced from scales published by Verhagen et al. (2006), Pavlou (2003), and Kim and Ahn (2006). demographic data were also collected for the purpose of classification and determining the generalisability of the results.Sample and Data order of battleRepresentativeness, reliability of results as well as time and resource restraints were considered in determining the sample. The final sample was a non-probability sample of administrative and academic staff in ten departments across the phoebe bird faculties of a lifesize Australian university. University staff was chosen, as they were deemed to be more ameliorate and sensible about a range of issues. Therefore it is concluded that university staff would likely have a higher chance of responding to the survey, with more accuracy and candor in their replies. Surveys were distributed physically and via online. Data collection took place over two weeks. A total of 218 returned questionnaires were yielded of which 202 passed manipulation checks and were usable. The response rate was 34.8%.ResultsAdoption of Internet and E-bankingDescriptive psychoanalysis was used and a bar chart (Figure 2) was constructed to compar e the year of adoption of the internet and the year of adoption of e-banking. In relation to internet adoption, the results showed that there was a slow growth in the adoption of internet prior to 1995. The rate of adoption increased importantly in the years 1995 to 2000 and dropped significantly after. As for the adoption of e-banking, the results showed that there was no presumable usage of e-banking till the late 1990s and after which the adoption of e-banking move up reaching its peak in 2006. Figure 2 illustrates how the adoption of e-banking has not kept up with the pace of internet usage this is consistent with the previous finding of White and Nteli (2004). Furthermore results also showed that there were still a significant number of people who have not adopted e-banking.Demographic variables were examined across the three constructs of specific trust, perceived risk and the willingness to use. The results in postpone 1 showed that there were significant differences bet ween gender and specific trust (sig. value 0.010, t-value 2.588) and perceived risk (sig. value 0.029, t-value 2.206) constructs. The means scores showed that males have higher specific trust (5.2748) and higher perceived risk (4.2916) as compared to females towards e-banking and the internet.For age, the results showed a significant difference between age and willingness to use (sig. level 0.017, f-value 4.161). The difference was found between respondents of age groups 29 and under, and 50 and above. The means scores showed that respondents who were age 29 and below (mean 5.603) were more willing to use e-banking as opposed to respondents who were 50 and above (mean -4.8571).For qualification, significant differences were present in the perceived risk (sig. level 0.020, f-value 4.991) and willingness to use (sig. level 0.030, f-value 4.932) constructs. In regards to perceived risk, the difference was found between respondents who have undefiled secondary naturalize an d respondents who have a post-graduate qualification. The means scores showed that respondents who had a post-graduate qualification (4.4355) have a higher perceived risk compared to those who had completed secondary rail (3.4006). In relation to willingness to use, significant differences were found between three groups of respondents those who had a trade qualification/ diploma, a tertiary degree and a post-graduate qualification. The means scores showed that respondents who had a post-graduate qualification has a higher willingness to use e-banking (5.6871) compared to those who had a trade qualification/diploma (4.5259) and those who had a tertiary degree (5.5925). in the long run for income, significant differences were found between the different income groups in the perceived risk (sig. level 0.049, f-value 2.249) and willingness to use (sig. level 0.003, f-value 3.788) constructs. The two groups of respondents with income levels of $15,001 -$ 30,000 and $70,001 -$90,00 0 were found to be significantly different in the perceived risk construct. The means scores of the two groups showed that respondents with an income level of $70,001 $90,000 had a higher perceived risk (4.6057) compared to respondents with an income level of $15,001 $ 30,000. In relation to willingness to use, significant difference was found between two groups $30,001 $50,000 and $50,001 $70,000. A comparison of the means scores showed that respondents who had an income level of $50,001 $70,000 (5.8625) were more willing to use e-banking compared to those who had an income level of $30,001 $50,000 (4.6513).Model TestingIn order to validate the measures of each construct, exploratory ingredient analysis was conducted using principal components extraction with varimax rotation. The items in each factor were then tested for scale reliability using standard Cronbach alpha indices.As the items for both perceived risk and specific trust in e-banking were used together as a hit scale in the survey instrument, factor analysis was ran on them both, to ensure that the two different factors were still valid. To check for the appropriateness of the data for factor analysis, the Kaiser-Meyer-Olkin (KMO) and Bartletts Test of Sphericity was examined. Results showed that the KMO statistic for the data set was 0.885 and the Bartlett test showed that non-zero correlations exist at the 0.000 significance level. This indicates that the data is appropriate for factor analysis. The results of the factor analysis showed that two factors were indeed present, however, one of the items from the scale measuring specific trust in e-banking Compared with other forms of banking, e-banking would be more risky had moved to the factor measuring perceived risk (see delay 2 , item attach with asterisk). A reliability analysis was conducted on this adjusted factor a Cronbach alpha index of .926 was obtained. The factor loading of the item, whilst not very high at .651 was much h igher than the items alternate factor loading which was .253. The item content was examined, and was found to also be applicable to the context of perceived risk due to the items wording which could be interpreted as a higher perception of risk in the medium of the Internet in comparison to other mediums. Given all these results, it was decided that the adjusted factor would be used as is in the analysis.Items measuring the construct of willingness to use e-banking were also analysis to ensure that it was indeed a singular factor (Table 3). The results showed that the KMO statistic for the data set was 0.873 and the Bartlett test showed that non-zero correlations exist at the 0.000 significance level. This indicates that the data is appropriate for factor analysis. The results revealed a unidimensional structure, and corroborated that all five items in the scale loaded onto one factor. The factor loadings of each item were high, indicating strong relevance of each item within the sc ale. When in faction with the high Cronbach alpha of .957, the results of the analysis show that this factor is a highly useful measure.Regression AnalysisTo test the relationship between the constructs of specific trust, perceived risk and willingness to use e-banking, hierarchical moderated regression was conducted. This method was proposed by Baron and Kenny (1986) to examine moderating effects. In conducting hierarchical moderated regression analysis, a series of regressions were performed. The first regression (Model 1) involved regressing the dependent variable (DV) on the independent variable (IV) the second regression (Model 2) involved regressing the DV on the IV and the moderator and the final regression (Model 3) regressing the DV on the IV, the moderator, and a cross-product of the DV and the moderator.The three regression models were tested for explanatory power, and yielded R-squared values of 0.396, 0.454, and 0.508 respectively (see Table 4). Results of the R-square d comparisons showed that Model 3, which included specific trust, perceived risk, and the cross product of specific trust and perceived risk, had significantly improved R-squared values from Model 1 and Model 2. The analysis yielded results sort of different to what was hypothesized. Besides Model 1 where specific trust was the only IV in the regression, specific trust was shown not to have a direct influence on the DV of willingness to use e-banking. Rather, perceived risk was shown to have a direct influence on the DV of willingness to use e-banking in Models 2 and 3. Model 3, which had the greatest R-squared value, suggests that it is not specific trust that influences a consumers willingness to use e-banking, but rather perceived risk. The regression coefficients from Model 3 (see Table 5) showed that perceived risk had a significant negative impact on willingness to use e-banking (p = 0.000, Beta = -1.179, t = -5.588). Specific trust in e-banking instead was found to have a p ositive moderating influence on the relationship between perceived risk and willingness to use e-banking (p = 0.000, Beta = 0.759, t = 4.386).The results derived from the regression analysis thus do not support the two hypotheses H1 and H2. It appears that the roles of the independent variable and the moderator have swapped. Figure 3 shows the amended model reflecting these new roles, where the independent variable of perceived risk is shown having a indigenous role with a direct influence on a consumers willingness to use e-banking and specific trust in the banks e-banking website having a secondary role as a moderator.Discussion and ImplicationsAdoption of Internet and E-bankingThe results showed that there was no plain usage of e-banking till the late 1990s. This was firstly attributed to the late adoption of e-banking facilities by the four major banks in Australia. It was only at the end of 1997 when e-banking facilities were provided by the banks in Australia (Sathye, 1999). Secondly, a report by the Australia Bureau of Statistics (1999) stated that the use of internet by adults to pay bills and transfer funds were only around 2 per cent during that time. These findings deserve attention, as Australians were considered to be technology dread being at the forefront of United States as the worlds third highest users of electronic point of transfer (Eftpos) in the 1990s (Macfarlane, 1997). However there were other reasons for the late adoption of e-banking in Australia. These reasons include the lack of knowledge of service availability, the internet website being not user friendly, and security concerns (Sathye, 1999). In the eventually decade, banks have addressed these problems through the use of effective marketing strategies, procreation and adopting innovative technology in security measures and information technology. It has proven to be effective as the latest statistics showed that approximately 40% of the internet users in Australia have ado pted e-banking (comScore, 2008). This proportion however is still relatively low, and concurs with the results of past research such as White and Nteli (2004), Lichtenstein and Williamson (2006), and the current research showing that the adoption of e-banking has not kept up with the pace of internet usage. This is contempt figures for internet access quadrupling from 16% to 67% in the fit decade from 1998 to 2007/08 (Australian Bureau of Statistics, 2008).Demographics and Specific Trust, Perceived Risk and the Willingness to Use ConstructsResults showed that respondents who are aged 29 and below, earning an income level of $50,001 $70,000 and with post graduate qualifications were more willing to use e-banking. This finding is congruent with the findings of past studies that claimed that consumers who are well educated and with higher incomes are more willing to engage e-banking services (Kolodinsky et al., 2000 Gartner, 2003). Furthermore results of this study concur with past research studies on the unwillingness to use e-banking by the older/elderly generation (Ilett, 2005 Perumal and Shanmugam, 2005). Further examination of the results showed that respondents who are unwilling to use e-banking have a trade qualification/diploma and are earning an income of $30,001 $50,000.In relation to the perceived risk constructs, males who have a post graduate qualification and earning $70,001 -$90,000 have higher perceived risk. This finding is rather surprising as it does not concur with previous studies which found females to have a higher perceived risk. Females were found to be more concerned on the level of risk in technology (Lichtenstein and Williamson, 2006), more anxious with privacy protection and ethical standards (Shergill and Li, 2005) and have greater fears in new technologies such as the internet (Morahan-Martin, 2000) compared to males. Further examination of the results showed that respondents who have a lower perceived risk are females, earning an income of $15,001-$30,000 and have completed secondary school.Results from this research showed that males have higher specific trust than females regardless of income, age and qualification. Drawing from the findings of the perceived risk construct, an interesting discovery was made males have higher perceived risk as well as higher specific trust compared to the females. The authors of this study propose that a possible reason for this may be explained by a higher level of involvement in banking services in males. This should be con