Relationship Between Customer Satisfaction and Financial Performance

Relationship Between Customer Satisfaction and Financial Performance

In chapter IV, the overall customer satisfaction was recorded higher in case of PNB (see table 4.7). Similarly, the conclusion from financial analysis chapter (V) is that the index o f major financial ratios is higher in case o f PNB compared to JKB except liquidity and NPA (see table 5.13). Thus the analysis in these two chapters establishes that the rank o f PNB in the area o f customer satisfaction as well as in financial performance is higher. The JKB comes on the second rank. It seems that there exists correlation between the two variables (customer satisfaction and financial performance) o f the two banks. However, to what extent the two variables are correlated with each other needs further exploration. Thus to prove statistically that the two variables viz. customer satisfaction and financial performance are correlated, the statistical tool o f testing o f hypothesis, (t-test) has been employed. As such, the hypothesis formulation has been done as under: Null Hypothesis Ho: r = 0, Alternative Hypothesis HI: r^o, There is no correlation between customer satisfaction and financial performance There is relationship between customer satisfaction and financial performance. After formulation o f the above hypothesis, the decision rule to accept/reject the hypothesis has been followed; on the arguments o f statisticians like Levine, Berenson and Stephen (1998) and Mason, Lind and Marchal (1994), which is reproduced as under: ' i f the calculated value o f t is > the critical value o f t, reject the null

hypothesis: Ho; and accept the alternative hypothesis: HI (the conclusion would be that there is correlation between customer satisfaction and financial performance o f the banks. However, if the calculated value o f t is < the critical value o ft, accept the null hypothesis: Ho; and reject the alternative hypothesis: HI (the conclusion would be that there is no correlation between the two variables-customer satisfaction and financial performance o f the banks. The t-value has been calculated with the formula: t ^ 2 ~ l-r2 Thus to have a detailed analysis o f correlation between the two variables and test the above hypothesis, the data in chapters IV and V have been further processed. However, attempts have been made to find the relationships between customer satisfaction and the most important measures o f financial performance, viz. Capital adequacy, Asset quality, Measurement capability, Earning efficiency and liquidity. The analysis is presented in tables 6.1 to 6.7. * Table 6.1 Customer Satisfaction and Capital Adequacy Banks R R2 Beta (P) S.E. of P Level of significance D.F. t. value P PNB.92 85.6% 0.08 0.0190 95% 4 4.23 0.024 JKB.73 54.7% 0.15 0.084 95% 4 1.93 0.153 Source: Same as indicated in Chapters IV and V. C ustom er S a tisfa ctio n and C apital A dequacy An introspection in table 6.1 indicates that there exists perfect positive correlation between Capital Adequacy and Customer satisfaction in both the

banks. Although, correlation in case o f PNB is higher (co-efficient o f correlation being.92) compared to the correlation in case o f JKB (co-efficient o f correlation being.73). A further analysis of the table 6.1 indicates that customer satisfaction and financial performance (in terms o f capital adequacy) are correlated to the extent o f 85.6% in case o f PNB (as the R2 = 85.6%) and to the extent o f 54.7% in case o f JKB (as the R2=54.7%). This makes it clear that in PNB 85.6% o f the variation in Capital Adequacy is explained by the variation in customer satisfaction. Similarly in case o f JKB customer satisfaction is responsible to the capital adequacy o f the bank upto 54.7%. The co-efficient o f non-determination in case o f PNB is 0.144 (1 -.856), which means that 14.4% o f the variation in capital adequacy is not explained by customer satisfaction and must be due to other causes or random variation. Also in case o f JKB the co-efficient o f non-determination being 0.453 (1-.547) which means about 45.3% other causes or randomness in sampling are responsible for the variation in case o f capital adequacy. The S.E. in both the banks (PNB=0.0190 and JKB=0.084) have Shown that the results have not much dispersion but are near (above or below) the regression line. With the help o f computation o f t-value and its comparison with the critical value in the student s t-distribution table (two-tailed) indicates that the null hypothesis Ho: r =0 is rejected and the alternative hypothesis HI: r^o is accepted. Because the calculated value o f t = 4.23 (in case o f PNB) is greater than the critical value (2.77) at 4 degrees o f freedom. However, in case o f JKB, the alternative hypothesis is accepted as the critical value (2.77) is greater than table value 1.93. C ustom er S a tisfa ctio n and A sset Q uality As described earlier, another measure o f financial performance in the study has been termed as the quality o f the assets in the portfolio o f the banks

understudy. A bank is considered financially strong which has less NPAs as % o f total advances compared to the one which has more NPAs. Thus the correlation between the customer satisfaction and NPAs must be negative. In the banks understudy the correlation between the two variables is exhibited in table 6.2. Table : 6.2 Customer Satisfaction and Asset Quality (NPAs to advances) Beta S.E.of Banks R Level of t. R2 D.F. P (ft 3 significance value PNB -0.833 69.4% -0.04778-0.0183 95% 4-2.61 0.080 JKB -0.802 64.3% -0.3918 0.1684 95% 4-2.33 0.102 Source: Same as given in chapters IV and V. It is shown in the table 6.2 that in case o f both the banks customer satisfaction has contributed to the reduction o f NPAs, as in both cases the coefficient o f correlation is negative (-0.83 in PNB and -0.80 in JKB). The coefficient o f determination in case o f PNB explains that the contribution of customer satisfaction in the reduction/containment o f NPAs has been to the extent o f 69.4% which is a big amount; and the co-efficient o f non-determiantion which is.306 (1-0.694) explains that other factors or random variation has contributed in the reduction o f NPAs to the extent o f 30.6%. To test whether this result is statistically significant,'null hypothesis and the alternative hypothesis have been formulated as: Null Hypothesis Ho: r = 0 (There is no relationship between customer satisfaction and asset quality). Alternative Hypothesis HI: r ^ 0 (There is relationship between customer satisfaction and asset quality). Accordingly, the t-values have been computed in case o f PNB which comes -2.61 which is greater than its critical value (-2.77). Thus the Null hypothesis (Ho) that there is no relationship between the two variables is rejected and the alternative hypothesis (Hi) that there is perfect negative correlation between the customer satisfaction and NPAs as % o f advances is accepted.

Similarly, the analysis o f the data regarding JKB in the same table (6.2) reveals that the two variables are highly correlated but in negative way (r = -0.80, and R = 64.3%). The computed value -2.33 being greater than the table value - 2.77, thus the null hypothesis is rejected and the alternative hypothesis being accepted. Thus the analysis has brought it to the forefront that customer satisfaction and asset quality have very high negative correlation. If we improve customer satisfaction, the NPAs as % o f advances gets automatically reduced to a significant extent. C ustom er S a tisfa ctio n and M anagem ent E fficien cy The financial measure o f management efficiency in the present study has been taken as expenditure to income ratio. Since every business has a slogan, Maximize Incomes and minimize expenses. A bank with less expenses to Income Ratio, is considered more financially healthy compared to the one with more Expenses to Income Ratio (Duncan and Elliot, 2004). Therefore, the effort o f management in every organisation is reduce the Expense to Income ratio. For the success o f a bank, efforts in every side must be made to reduce this ratio. If efforts are increased in some direction and achievements made say in customer satisfaction, if it reduces this ratio, it means the two variables are negatively correlated. Thus the relationship between customer satisfaction and Expenses to Income ratio must be negative for better financial health o f a commercial bank. In the banks under study the relationship between these two variables is exhibited in table 6. 3. Banks R R2 Table 6.3 Customer Satisfaction and Management Efficiency Beta (P) S.E. of P Level of significance D.F. t. value PNB -0.43 18.5% -0.0093 0.01179 95% 4-0.83 0.470 JKB -0.09 0.8% 0.0034 0.0219 95% 4 0.16 0.885 P Source: Same as in the Chapters IV and V.

The analysis in the table 6.3 reveals that the relationship o f customer satisfaction with Management efficiency (in terms o f Expenditure to Income in case o f PNB although is negative but is very weak. The co-efficient o f determination (18.5%) between the two variables indicates that only upto 18.5%, the customer satisfaction explains the variation in the Expenditure to Income ratio (management efficiency). The co-efficient o f non-determination 81.5% (1-.185) signifies that other factors and random causes are responsible for variation in the Expenditure to Income ratio. The other factors responsible for this include introduction o f Profit Centre Concept in the organisation and mass cost consciousness, and large scale computerization. Since in the present case the calculated value o f t (-0.83) is greater than the table value (-2.77), the null hypothesis Ho: r = 0, that there is no relationship between customer satisfaction and management efficiency is rejected and the alternative hypothesis HI: r ^ 0, that there is relationship between the two variables is accepted. A further analysis in the table 6.3 shows that in case o f JKB, the two variables (Customer Satisfaction and Expenses to Income ratio) although register a negative correlation co-efficient (r = -0.09) but the relationship between the two is very small which is further supported by co-efficient o f determination (r2=0.8%). This magnifies that customer satisfaction contributes to management efficiency to the extent 0.8%; and other factors as well as variation because of random causes contribute to the extent o f 99.20% (1 -.0080). A discussion with the bank officials reveals that some drastic changes brought in the management o f the bank like diversification to fee-based businesses where revenue is more compared to expenses, productivity improvement through large scale computerization, introduction o f new services like Credit Cards/ATMs where expenditure is less but revenue is more, bringing cost consciousness by regular training programmes etc.

rhe calculated value o f t (0.16) as shown in the table 6.3 is less than the critical value 2.77, thus the hypothesis (Ho) is accepted. It is, therefore, concluded that there is no significant relationship between customer satisfaction and management efficiency in the JKB. C ustom er S a tisfa ctio n and Earnings E fficiency The most important measure o f financial performance is earnings efficiency. The most important measure o f earnings efficiency is Return on Assets, which explains how much a bank earns (net profit) on its assets (working funds). The analysis o f relationship between net profits and R.O.A is given in the table 6.4. Banks R R2 Table 6.4 Customer Satisfaction and Earnings Efficiency (ROA) Beta (P) S.E. of P Level of significance D.F. t. value P PNB 76 58.8% 0.691 0.334 95% 4 2.07 0.130 JKB.82 68.2% 0.262 0.103 95% 4 2.54 0.085 Source: Same as that of chapters IV and V In the table 6.4, it is clear that in case o f PNB, Customer Satisfaction and Earnings Efficiency in terms o f Return on Assets (ROA) are correlated with each other, as the value o f r =.76. However, it is further shown that the variation in earnings efficiency have been explained by the customer satisfaction to the extent o f 58.8%, and other factors including random variations are responsible to the extent o f 41.2%, being the co-efficient o f non-determination (1-.588). Similarly, in case o f JKB, since the co-efficient o f correlation between the two variables is.82, which states strong positive relationship between them. The coefficient o f determination (68.2%) indicates that earnings efficiency in terms o f R.O.A depends upon customer satisfaction to the extent o f 68.2%. The coefficient o f non determination 31.8% (1-.682) shows that the variations in the R.O.A have been explained by other factors including random causes to the

extent o f 31.8%. Hence, the relationship between customer satisfaction and earnings efficiency (ROA) is established in case o f JKB as well. The relationship between customer satisfaction and earnings efficiency has been measured in terms o f net interest margin, the analysis o f which is presented in table 6.5. Table 6.5 Customer Satisfaction and Earnings Efficiency (Net interest Margin) Banks R R2 Beta (P) S.E. ofp Level of significance D.F. t value PNB.85 73.8% 58.4 20.18 95% 4 2.16 0.062 JKB.81 65.9% 65.15 27.08 95% 4 2.41 0.095 Source: Same as that of chapters IV and V The relationship between customer satisfaction and earnings efficiency (in terms o f net interest margin) is further established, as given in table 6.5. In the table, since in both the banks (PNB and JKB), co-efficient o f correlation is 0.85 and 0.81 respectively, it shows strong positive correlation between the two variables. However, customer satisfaction has contributed more to net interest margin (73.8%) in case o f PNB (^=73.8%) compared to JKB where the former has contributed to the extent o f 65.9% (r2=65.9%) The value o f co-efficient of non-determination in case o f PNB and JKB is 26.2% and 34.1% respectively, which shows that other factors including the sampling errors due to randomness are responsible to the extent o f 26.2% and 34.1% in case o f PNB and JKB respectively. C ustom er S a tisfa ctio n and Liquidity The liquidity ratio as a measure o f financial performance o f a bank is considered an important too. For the purpose o f present study among various liquidity ratios as discussed in chapter IV, the ratio o f Liquid assets to Deposits has been used. This ratio is the measure o f ascertaining the risk o f meeting the obligations o f depositors o f the bank who can demand liquidity at any point o f P

time and the bank should be in a position to meet their demands otherwise the confidence o f the customers shall be shaken. The relationship between the customers satisfaction and liquidity ratios (Liquid assets to Deposits) the banks under reference can be gauged from table 6.6. Table 6.6 Customer Satisfaction and Liquidity Beta Banks S.E of R Level of R* D.F. t. value P (» 3 significance PNB.68 46.8% 9.184 5.654 95% 4 1.62 0.203 JKB.86 74.3% 6.140 2.084 95% 4 2.95 0.060 Source: Same as that of chapters IV and V An introspection o f the table 6.6 signifies that in case o f PNB, there is positive correlation between customer satisfaction and liquidity o f the bank as the co-efficient o f correlation between the two variables is.68. A further analysis indicates that customer satisfaction explains the variation in the liquidity to the extent o f 46.8% as the value o f co-efficient o f determination is 46.8%. Other factors including random causes contribute in the variation in liquidity to the extent o f 53.2% as the co-efficient o f determination is 53.2% (1-.468). However, the relationship between the two variables is not statistically significant as the calculated value o f t (1.62) is less than the critical value o f t (2.77). So far as the relationship between two variables in JKB is concerned, it has strong positive correlation (r =.86). The customer satisfaction variable is responsible to the extent o f 74.3% for the liquidity o f the bank as the co-efficient o f determination is 74.3% (1-.743). This suggests that other factors including the random causes contribute to the liquidity o f the bank to the extent o f 25.7/o, only, as the co-efficient o f non-determination is 25.7 (1-.743). The relationship between the two variables has been found statistically significant, as the calculated value o f t (2.95) is more than the table value (2.77). Thus the null hypothesis Ho: that there is no relationship between customer

satisfaction and liquidity is rejected; and the alternative hypothesis HI: that there is relationship between the two variables is accepted. The relationship between customer satisfaction and various parametres of financial performance which has been summed up in table 6.7 reveals that in both the banks (PNB and JKB), the variables like Capital adequacy, Return on assets, Net interest margin, and liquidity show a high degree o f positive correlation with customer satisfaction. Table 6.7 Relationship between Customer Satisfaction and Financial Performance: Summarized results of R and R2 PNB JKB R R2 R R2 Customer Satisfaction and Capital adequacy 0.92 85.6% 0.73 54.7% Customer satisfaction and Asset quality (NPAs as % of total advances) Customer satisfaction and Management efficiency (Expenditure to Income ratio). Customer satisfaction and Earnings efficiency (Return on assets). Customer satisfaction and Earnings efficiency (Net interest margin). Customer satisfaction and liquidity (Liquid assets to deposits ratio) Source: Same as that of tables 6.1-6.6. -0.83 69.4% -0.80 64.3% -0.43 18.5% -0.09 0.81% 0.76 58.8% 0.82 68.2% 0.85 73.8% 0.81 65.9% 0.68 46.8% 0.86 74.3% Similarly, in both the banks, the variable Asset quality (NPAs as % of total advances) registers a high degree o f negative correlation with customer satisfaction. However, the variable Management efficiency (Expenditure to Income ratio) indicates a little correlation with customer satisfaction in both the banks. The results shown in the table 6.7 have serious implications for the banking industry in general and that o f sample banks in particular. If they have to financially healthy, they have to improve the customer satisfaction.

C onclu sion The analysis o f the Chapter VI reveals that there is a strong correlation between customer satisfaction and financial performance. These findings provide evidence o f the empirical relationships between two banks o f key performance indicators commonly used by financial institutions world wide especially used within India. From a financial services marketing perspective, the positive correlation between customer satisfaction and financial performance is the most notable finding. This result provides further empirical support for the purported relationship between customer satisfaction and financial performance which has been argued by Zahorik & Rust (1992) Heskett, et.al (1994), Rust, et.al (1995), Parasuraman (2002), Duncan and Elliot (2004), Bhat and Joo (2005), among others. For the Indian banks these findings should act as eye opener, sooner they realize that if they want to have survive and want to improve financially, they have to improve the satisfaction o f their customers. For this purpose, the suggestions in the Chapter V can be helpful to a significant extent.

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