Factors Affecting Selection Of A Bank For Opening A Fixed Deposit Account A Market Research Report For Term 2 Mba (F & B)

Public savings is a key source of cheap and inexpensive source of money in the Indian Banking System. For all the banks, deposits are the 'source of funds' having lesser cost of funds with a predefined lock in period. Hence, it is of utmost importance to dictate the booming economy of India. A major component of such savings is through Time deposits constituting nearly 85% of the Total deposits. Furthermore, Term deposits constitute a major component of such Time deposits. Statistics from the RBI website show that the CAGR growth of Time Deposits with Scheduled Commercial Banks is close to 20%.

As far as the Indian households are considered, their deposits in banks are more than the combined quantum parked by the government and private sector. As per the latest RBI data, the household sector accounted for 58.1% of the total deposits of Rs. 6411 Thousand Cr (approximately) in Indian banks as of March 2012.
Changes in macro-economical factors and increased competition in the financial services have led the market situation where consumer satisfaction is of immense importance along with growth in business. From consumers' point of view, in the current market situation of financial turmoil, they are looking for safer investment options to park their money. It is very important for banks to know about the consumer perception and choices to sustain and grow in the competitive environment. Once the customer has opted for opening a FD with the bank, it will also provide an excellent platform for cross selling of other financial products.
With so much at stake, the banks need to understand the factors that guide a customer for opening a Fixed Deposit with any bank. This study will help us to understand the various consumer considerations and preferences for selecting a Bank while opening a fixed deposit. It will also guide the banks to understand what are the factors having maximum priority in the minds of the customers and hence they can plan accordingly while redesigning the product and adopting a suitable marketing strategy.
2. Literature Review
In today's scenario, level of adaption of the advance technology by private and public sector banks are impacting the customers' selection of a bank for financial product and services. Also, other than technology what are the factors impacting the consumer satisfaction. (Jani, 2012)
Study of Equation Modelling (Factor) approach has been used to demonstrate the effect of various IMC (integrated marketing communication) factors such as coverage, commonality and cost on Brand awareness, loyalty, Emotional association and Financial Value. (Omdeep Gupta, 2012)
As far as the financial products are concerned, the most attractive features of a product in descending order of importance are Returns (4.6), Safety and Security (4.14), Maturity Period (3.63), Transparency (3.00). (Naidu, 2012)
Banks are a very lucrative mode for investing among the various forms of investments. Also consumer preferences for choosing financial policies are as follows in decreasing order of importance. Security (61.22), Tax (57.84). (K. Rajeswari, 2012)
3. Research Gap
Till now most of the banks have focused on optimizing the interest rate and tenure of the FDs and less focus has been put on the other factors affecting consumer perception and satisfaction. This research paper attempts to fill this gap between consumer perception and bank's perception by identifying various factors which affects consumer preferences. This will also help the banks to redesign their offerings optimized according to consumer preferences.
4. Objective and Hypothesis

4.1.1. Objectives of the Study
' To identify factors affecting consumer preferences for the selection of the bank for FDs
' To assess the relative importance of these factors on the consumer perception
' To examine the relationship between consumer preference towards FD and demographic variables
5. Research Methodology
The purpose of this research is to evaluate the factors influencing customer's decision process while opening a new Fixed Deposit.
The research aims to find a direct linkage among various aspects like Interest Rates, Penalty charged for pre closing of the FD, Service Quality, Ease of Operation, Brand Image of the bank, Other facilities available like opening of Locker, Proximity of the branch to residence or office, Existing relationship with the bank, Reference from friends/relatives/financial advisors, Advertisements from Bank, and Type of Bank.
5.1.1. Research Design
For this proposed study, descriptive research design will be followed. Descriptive research is the exploration of the existing certain phenomena. It is used to obtain information concerning the current status of the phenomena to describe "what exists" with respect to variables or conditions in a situation. The main goal of this type of research is to describe the data and characteristics about what is being studied. The idea behind this type of research is to study frequencies, averages, and other statistical calculations.

This study is about the consumers' preference towards a bank being impacted by the bank's website. The level of consumer awareness about the various online offerings by the bank will also be examined. Basically this research will describe the population surveyed and its characteristic, so it is a descriptive research.

5.1.2. Sampling Design

' Target Population: Adult Indian citizen above 18 years of age and having an appetite for opening fixed deposits with single/multiple bank. The population surveyed will be pan India.
' Sampling Technique: Judgemental sampling which is a part of Non probabilistic Convenience Sampling will be the sampling technique used to carry out this research. Non-probability sampling focuses on sampling techniques where the units that are investigated are based on the judgment of the researcher. As this proposed study is to be conducted in a short span of time with limitations in mobility and population outreach, this sampling design was chosen due to convenience and with the purpose of fulfilling the objectives of this proposed study.
' Sample Size: A sample size of 60 respondents will be taken for conducting this study.

5.1.3. Data Collection Strategy
' Type of Data: Primary data will be used for conducting the research.
' Data Collection Tools: The survey instrument used in this study is a structured questionnaire through an empirical study. The variables are measures using multiple items. All of the scale items represented in the survey instrument is on a five-point categorical (likert) rating scale. The anchors used include: a) 1= Very Low, b) 2= Low, c) 3= Average, d) 4= High, e) 5= Very High. The data obtained are responses from the target population specified above. We used an online survey method using Google Forms.
' Time Period of Data: The data will be collected over a fortnight period from 14th March, 2014
6. Questionnaire
The questionnaire prepared for this purpose can be viewed at the following link:
http://docs.google.com/forms/d/1eKHir29qh8hgU7VBoW3obwtSxXn3u2zbXLAGXcpJKY/viewform
7. Statistical Analysis
We have used SPSS to interpret the results.
Descriptive Statistics
The first output from the analysis is a table of descriptive statistics for all the variables under consideration. Typically, the mean, standard deviation and number of respondents (N) who participated in the survey are given. Looking at the mean, one can conclude that Interest Rate is the most important variable that influences customers to open a new Fixed Deposit. It has the highest mean of 4.57, whereas Impact of Advertisements plays the least significant role with lowest mean of 2.98.
Descriptive Statistics
Mean Std. Deviation Analysis N
Interest Rate charged 4.57 .698 60
Penalty charged for preclosing of FD 3.67 1.130 60
Prev Experience with the bank 4.00 .974 60
Service Quality 4.27 .861 60
Ease of Operation (mobile/phone) 4.15 .971 60
Brand Image of the bank 3.88 .922 60
Other Facilities like locker etc available 3.62 .993 60
Proximity of the bank with respect to home/office 3.83 .977 60
Existing Relation with a bank 3.97 .920 60
Reference from friends/relatives/financial advisors 3.25 1.099 60
Impact of Advertisements from Banks 2.98 1.172 60
Type Of Bank (private, public etc) 3.67 1.020 60

Reliability Analysis
Cronbach's alpha is the most common measure of internal consistency ("reliability"). It is most commonly used when we have multiple Likert questions in a survey/questionnaire that form a scale and we wish to determine if the scale is reliable. Cronbach's alpha is 0.864 which indicate a high level of internal consistency for our scale with this specific sample.
Reliability Statistics
Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items
.864 .871 12

The Correlation matrix
The next output from the analysis is the correlation coefficient. A correlation matrix is simply a rectangular array of numbers which gives the correlation coefficients between a single variable and every other variable in consideration. The correlation coefficient between a variable and itself is always 1; hence the principal diagonal of the correlation matrix contains 1s. The correlation coefficients above and below the principal diagonal are the same. The determinant of the correlation matrix is shown at the foot of the table below.
Interest Rate charged Penalty charged for preclosing of FD Prev Experience with the bank Service Quality Ease of Operation (mobile/phone) Brand Image of the bank Other Facilities like locker etc available Proximity of the bank with respect to home/office Existing Relation with a bank Reference from friends/relatives/financial advisors Impact of Advertisements from Banks Type Of Bank (private, public etc)
Correlation Interest Rate charged 1.000 .416 .199 .478 .448 .447 .294 .464 .188 .210 .364 .413
Penalty charged for preclosing of FD .416 1.000 .077 .232 .139 .369 .292 .302 -.092 .341 .175 .152
Prev Experience with the bank .199 .077 1.000 .687 .591 .585 .350 .445 .397 .459 .208 .273
Service Quality .478 .232 .687 1.000 .620 .595 .538 .416 .268 .340 .257 .373
Ease of Operation (mobile/phone) .448 .139 .591 .620 1.000 .758 .254 .330 .385 .345 .270 .342
Brand Image of the bank .447 .369 .585 .595 .758 1.000 .357 .561 .395 .397 .312 .445
Other Facilities like locker etc available .294 .292 .350 .538 .254 .357 1.000 .492 .283 .384 .329 .257
Proximity of the bank with respect to home/office .464 .302 .445 .416 .330 .561 .492 1.000 .352 .229 .501 .403
Existing Relation with a bank .188 -.092 .397 .268 .385 .395 .283 .352 1.000 .210 .141 .331
Reference from friends/relatives/financial advisors .210 .341 .459 .340 .345 .397 .384 .229 .210 1.000 .438 .424
Impact of Advertisements from Banks .364 .175 .208 .257 .270 .312 .329 .501 .141 .438 1.000 .492
Type Of Bank (private, public etc) .413 .152 .273 .373 .342 .445 .257 .403 .331 .424 .492 1.000
a. Determinant = .002

Kaiser-Meyer-Olkin (KMO) and Bartlett's Test:
The KMO measures the sampling adequacy which should be greater than 0.5 for a satisfactory factor analysis to proceed with. Looking at the table below, the KMO measure is 0.724, hence we can proceed with our factor analysis.
Bartlett's test is another indication of the strength of the relationship among variables. This tests the null hypothesis that the correlation matrix is an identity matrix. From the same table, we can see that the Bartlett's test of sphericity is significant That is, its associated probability is less than 0.05. In fact, it is actually 0.000, i.e. the significance level is small enough to reject the null hypothesis. This means that correlation matrix is not an identity matrix.

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .724
Bartlett's Test of Sphericity Approx. Chi-Square 331.987
Df 66
Sig. .000

Communalities
The next item from the output is a table of communalities which shows how much of the variance in the variables has been accounted for by the extracted factors. For instance over 79% of the variance in Penalty charged for pre-closing of account is accounted for while 74.1% of the variance in Brand Image of the bank is accounted for.
Communalities
Initial Extraction
Interest Rate charged 1.000 .535
Penalty charged for preclosing of FD 1.000 .790
Prev Experience with the bank 1.000 .727
Service Quality 1.000 .726
Ease of Operation (mobile/phone) 1.000 .715
Brand Image of the bank 1.000 .741
Other Facilities like locker etc available 1.000 .401
Proximity of the bank with respect to home/office 1.000 .554
Existing Relation with a bank 1.000 .599
Reference from friends/relatives/financial advisors 1.000 .409
Impact of Advertisements from Banks 1.000 .733
Type Of Bank (private, public etc) 1.000 .630
Extraction Method: Principal Component Analysis.

Total Variance Explained
The next item shows all the factors extractable from the analysis along with their eigen values, the percent of variance attributable to each factor, and the cumulative variance of the factor and the previous factors. It can be seen that first factor accounts for 42.41% of the variance, the second 11.556%. All the remaining factors are not significant.

Total Variance Explained
Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %
1 5.089 42.411 42.411 5.089 42.411 42.411 3.403 28.356 28.356
2 1.387 11.556 53.967 1.387 11.556 53.967 2.626 21.883 50.238
3 1.082 9.015 62.982 1.082 9.015 62.982 1.529 12.744 62.982
4 .931 7.761 70.743
5 .866 7.218 77.961
6 .670 5.583 83.544
7 .586 4.882 88.427
8 .457 3.807 92.234
9 .394 3.280 95.514
10 .260 2.163 97.676
11 .151 1.255 98.931
12 .128 1.069 100.000
Extraction Method: Principal Component Analysis.

Scree Plot
The scree plot is a graph of the eigen values against all the factors. The graph is useful for determining how many factors to retain. The point of interest is where the curve starts to flatten. It can be seen that the curve begins to flatten between factors 3 and 4. Note also that factor 4 has an eigenvalue of less than 1, so only three factors have been retained.

Component (Factor) Matrix
The table below shows the loadings of the eight variables on the three factors extracted. The higher the absolute value of the loading, the more the factor contributes to the variable. The gap on the table represent loadings that are less than 0.5, this makes reading the table easier. We suppressed all loadings less than 0.5.
Component Matrixa
Component
1 2 3
Interest Rate charged .629
Penalty charged for preclosing of FD .621
Prev Experience with the bank .709
Service Quality .776
Ease of Operation (mobile/phone) .738
Brand Image of the bank .825
Other Facilities like locker etc available .616
Proximity of the bank with respect to home/office .711
Existing Relation with a bank
Reference from friends/relatives/financial advisors .601
Impact of Advertisements from Banks .563
Type Of Bank (private, public etc) .627
Extraction Method: Principal Component Analysis.
a. 3 components extracted.

Rotated Component (Factor) Matrix
The idea of rotation is to reduce the number factors on which the variables under investigation have high loadings. Rotation does not actually change anything but makes the interpretation of the analysis easier. Looking at the table below, we can see that Penalty Charged on pre closure of FD and Interest Rate loaded on Factor (Component) 3 while Type of Bank, Impact of Advertisement are substantially loaded on Factor 2. All the remaining variables are substantially loaded on Factor 1. These factors can be used as variables for further analysis.

Rotated Component Matrixa
Component
1 2 3
Interest Rate charged .517
Penalty charged for preclosing of FD .869
Prev Experience with the bank .834
Service Quality .788
Ease of Operation (mobile/phone) .824
Brand Image of the bank .763
Other Facilities like locker etc available
Proximity of the bank with respect to home/office .597
Existing Relation with a bank .525
Reference from friends/relatives/financial advisors .531
Impact of Advertisements from Banks .848
Type Of Bank (private, public etc) .761
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 5 iterations.

Source: Essay UK - http://ntechno.pro/free-essays/finance/factors-selection-bank.php


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