Effect Of E-banking On Bank Profitability
[A STUDY OF GUARANTY TRUST BANK PLC ENUGU]

DATA PRESENNTATION AND ANALYSIS

4.1     Data Presentation

4.1.1  Necessary Data for Analyses

Sources: Computed by the Researcher from GT Bank Annual Report (2014-2017)

Chart 4.1.1  Return on Earnings of GT Bank from 2014 to 2017

The trend in the above chart shows that Return on Equity of GT Bank has been increasing significantly from 2014 to 2017.

Chart 4.1.2  Return on Assets of GT Bank from 2014 to 2017

Chart 4.1.2 shows that the return of asset has been increasing marginally within the period under review

Chart 4.1.3  Web Transactions of GT Bank from 2014 to 2017

Total value of web transactions has been increasing progressively as shown by the upward movement of the trend from left to right.

Chart 4.1.4  Total value of GT Banks’ ATM Transactions from 2014 to 2017

The trend in chart 4.1.4 shows that ATM transaction in GT Bank has been increasing significantly within the period under review

4.2     Data Analyses

Decision Rule: Reject H0 if P-value ≤ .05, otherwise Do not reject.

MODEL I:   ROA = b0 + b1Web + µ

The R of .508 shows that there is a fairly positive relationship between ROA and Internet banking. The R-square of .258 shows that about 25.8% of the variation in ROA can be explained by internet banking at a statistical non-significance of .492. The intercept of 4.112 shows the value of ROA when Internet banking is constant or equal to zero. The slope of .00000041 shows that at every percentage increase in internet banking, return on assets increase by .000041%. After substituting the values of the model from above analysis, we will have

ROA = 4.112 + .00000041Web + .728

Decision

Hypothesis testing I

H0: Internet banking has no significant impact on Return on Asset

The P-value on which basis we can reject the null hypothesis that Internet banking has no significant impact on Return on Asset is .492. Since the P-value > .05, we conclude concurrently Internet banking has no significant impact on Return on Asset.

MODEL II:  ROE = b0 + b1Web + µ

The R of .273 shows that there is a weak positive relationship between ROE and Internet banking. The R-square of .075 shows that about 7.5% of the variation in ROE can be explained by internet banking at a statistical non-significance of .727. The intercept of 24.713 shows the value of ROE when Internet banking is constant or equal to zero. The slope of .00000062 shows that at every percentage increase in internet banking, return on assets increase by .000062%. After substituting the values of the model from above analysis, we will have

ROE = 24.713 + .000000006022Web + 2.213

Decision

Hypothesis Testing II

H0: Internet banking has no significant impact on Return on Equity

The P-value on which basis we can reject the null hypothesis that Internet banking has no significant impact on Return on Equity is .727. Since the P-value > .05, we conclude adamantly Internet banking has no significant impact on Return on Equity.

MODEL III: ROE = b0 + b1ATMch+ µ

The R of .158 shows a weak positive relationship between ROE and ATM Transactions. The R-square of .025 shows that only about 2.5% of the variation in ROE can be explained by ATM Transactions at a statistical non-significance of .842. The intercept of 25.86 shows the value of ROE when ATM Transactions is constant or equal to zero. The slope of .0000003951 shows that at every percentage increase in ATM Transactions, return on assets will increase by .000040%. After substituting the values of the model from above analysis, we will have

ROE = 25.186 + .0000003951Web + 2.272

Decision

Hypothesis Testing III

H0: ATM transactions has no significant effect on return on equity

The P-value on which basis we can reject the null hypothesis that ATM transactions has no significant effect on return on equity is .842. Since the P-value > .05, we conclude that ATM transactions have no significant effect on return on equity.