EuroEconomica, Vol 34, No 2 (2015)

Financial consumer protection and customer satisfaction. A relationship study by using factor analysis and discriminant analysis

Marimuthu SELVAKUMAR¹, Veluchamy SATHYALAKSHMI²

¹ Ayya Nadar Janaki Ammal College Sivakasi, professorselvakumar@gmail.com

²Ayya Nadar Janaki Ammal College Sivakasi, sathyalakshmi1092@gmail.com

Abstract. This paper tries to make an attempt to study the relationship between the financial consumer protection and customer satisfaction by using factor analysis and discriminant analysis. The main objectives of the study are to analyze the financial consumer protection in commercial banks, to examine the customer satisfaction of commercial banks and to identify the factors of financial consumer protection lead customer satisfaction. There are many research work carried out on financial consumer protection in financial literacy, but the identification of factors which lead the financial consumer protection and the relationship between financial consumer protection and the customer satisfaction is very important, Particularly for banks to improve its quality and increase the customer satisfaction. Therefore this study is carried out with the aim of identifying the factors of financial consumer protection and its influence on customer satisfaction. This study is both descriptive and analytical in nature. It covers both primary and secondary data. The primary data has been collected from the customers of commercial banks using pre-tested interview schedule and the secondary data has been collected from standard books, journals, magazines, websites and so on.

Keywords: bank, financial education, financial disclosure.

1 Introduction

Until the financial crisis of 2007-09, the glob­al economy was adding an estimated 150 million new consumers of financial servic­es each year. Rates of increase have since slowed but growth continues apace. The financial crisis highlighted the importance of financial consumer protection for the long-term stability of the global financial system. At the same time, rapid increases in the use of financial ser­vices have pointed to the need for strengthened finan­cial regulation and consumer education to protect and empower consumers. In the absence of strong financial consumer protection, the growth-enhancing benefits of expanded financial inclusion may be lost or severely un­dermined.

Consumer protection and financial literacy can contribute to improved efficiency, transparency, competition and access to retail financial markets by reducing information asymmetries and power imbalances among providers and users of financial services.

Rapid progress toward widespread financial inclusion must be appropriately complemented with “checks and balances” that ensure a responsible provision of financial services and products.

Consumer protection and financial literacy capability can support financial inclusion by Encouraging competition which leads to more cost-effective and higher quality products and by increasing consumer confidence and reducing risk when purchasing financial products and services, because they know remedies exist when things go wrong.

The global financial crisis has highlighted the importance of financial consumer protection for financial stability. The report of the Financial Stability Board (FSB) on Consumer Finance Protection with Particular Focus on Credit endorsed by the G20 notes that “Policies that protect the interests of consumers of financial products and services contribute to enhanced risk management by households, more competitive financial markets, and greater financial stability. This financial crisis demonstrated the desirability of strengthening such policies and ensuring that the use (or misuse) of individual financial products do not become a source of financial instability”.

Effective implementation of consumer protection regulation is not easy, even when regulatory capacity is less constrained. It tends to require less intensive supervision than prudential regulation, because it focuses on specific products and practices rather than the overall financial performance and risk profile of a financial services provider. On the other hand, basic consumer protection regulation may bring many additional providers under oversight, and it focuses on the numerous transactions between providers and consumers. And appropriate standards are still in early stages of development.

2 Related work

The related works in the field of financial consumer protection in commercial banks is limited only to the global agencies who try to increase global level of financial education, financial inclusion and financial consumer protection by providing some working papers, data and regulatory suggestions. In this view, the researcher searched for previous studies in this area. The previous studies available are as follows:

• Lusardi (2008) demonstrates widespread financial literacy among the U.S population, particularly among specific demographic groups. Those with low education, women, African-Americans and Hispanics display particularly low levels of literacy.

• Rutledge (2010) analyzed the need for financial literacy. A common challenge among the nine countries is the need of an adequate institutional structure for financial consumer protection. However independent of the specific institutional structures, financial consumers should have one single agency where to submit complaints and inquiries. Financial institutions should be required to apply fair, non-coercive and reasonable practices when selling and advertising financial products and services to consumers. Personal data should also be carefully protected.

• Lumpkin (2010) suggests that financial service providers should have appropriate internal controls to minimize the chances that consumers take on inappropriate exposures. Even the best disclosures alone may not be adequate, so to avoid situations in which retail investors become involved with unsuitable products, institutions should be encouraged to develop sufficient measures for client protection as part of their product development activities. Strict penalties should be used when needed to address mis-selling, fraud or firm misconduct.

• Dias & Mckee (2010) say that regulation and supervision are not sufficient to deal with all consumer protection problems. Sometimes problems are rooted in consumers’ lack of understanding, knowledge and awareness with regard to financial services and redress mechanisms.

• Ardic et al.(2011) presents the results of a survey on consumer protection regulation in 142 countries. The findings indicate that although consumer protection legislation is in place in the majority of countries, these do not necessarily address the issues specific to financial services.

• Melecky & Rutledge (2011) discuss the role and design of financial consumer protection, weaknesses of current FCP frameworks in light of the recent global financial crisis, policy responses to the crisis and policy issues in FCP that remain to be addressed. This has been advanced by thinking about the need for a sound and safe design of future financial architecture, including benchmarks for FCP worldwide.

• Dulare (2011) pointed out that in Fiji, the rights of consumers of all products are protected through agencies like the Ministry of Industry and Trade, Commerce Commission and the Consumer Council of Fiji. The Reserve Bank of Fiji provides some protection through policy statements and institutional arrangements based on specific clauses in the Reserve Bank of Fiji Act and the Banking Act.

• Bank of Uganda (2011) states that financial consumer protection are intended to be cost effective and proportionate and to make a real difference to the welfare of consumers and potential consumers of financial products and services.

• Vivek Kudva (2011) presents that financial literacy and investor protection are clearly intertwined and any efforts to enhance them needs to be a holistic process that takes into consideration investor interests as well the need to develop and grow the industry.

• Jean Braucher (2012) examines the theory underlying the new agency’s anti-abuse regulatory power and its early implementation efforts. Armed with insights from behavioral economics supported by extensive research, the CFPB is targeting credit products designed to exploit consumer error.

• Evgeniev & Filipova (2012) have pointed that optimal consumer protection in financial services and high consumer financial capability are at the heart of a financial sector in Bulgaria that aims to be effective, competitive and fair.

• Robert C.Merton (2013) suggest that to develop the next generation of consumer financial and retirement plan services, we must develop truly effective ways to make consumers smarter about their retirement. In addition, however, we must ensure that the protections we put in place elicit, indeed encourage, the right behavior and do not thwart the ultimate goal of providing secure financial futures for consumers.

• Polat & Alsaif (2014) found through principle component analysis that providing high quality of banking is also a way for consumer protection. The Second dimension is privacy of consumers. Consumer enhancement of protection can be increased by three factors which are training, media and electronic means of communications.

• Canadian Payments Association (2014) pointed out that a comprehensive financial consumer code should apply to all financial institutions, service providers and scheme operators offering similar payment services. Limiting coverage to federally regulated financial institutions impacts the overall effectiveness of the proposed code in terms of protecting consumers’ rights and promoting consumer confidence with financial products in a rapidly evolving and innovative financial marketplace.

• Muller et al. (2014) say that inadequate consumer protection, especially in the U.S mortgage market, not only led to considerable consumer detriment but was a major contributor to the global crisis. In the EU, mis-selling of financial products has also resulted in significant consumer harm. Considering the significant potential detriment that financial services can cause to individual consumers and to the single market, consumer protection policy needs to properly focus on this area.

There are many research work carried out on financial consumer protection and financial literacy, but the identification of factors which lead the financial consumer protection and the relationship between financial consumer protection and the customer satisfaction is very important, Particularly for banks to improve its quality and increase the customer satisfaction. Therefore this study is carried out with the aim of identifying the factors of financial consumer protection and its influence on customer satisfaction.

3 Problem statement

Financial Consumer Protection has been in the top agenda of financial system regulators to improve customer protection policies and regulations recently. If regulation is correctly designed and properly enforced, it sustains consumer and investor confidence, which is necessary if the financial system is to attract capital and function efficiently. Market confidence and consumer protection are undermined if the financial system is not adequately protected from abuses. Economic exchanges, in general and financial transactions in particular rely importantly on trust and confidence. Financial transactors must have some assurance that financial markets and institutions are safe, sound and operate according to rules and procedures that are fair, transparent and free from conflicts of interest and other agency problems.

But consumer protection does not stop with safety and soundness regulation. There are also measures that focus on the interface between service providers and consumers and the potential risk that the interests of the providers of financial services may not be sufficiently aligned with those of the consumers of the products. Various norms of behaviour work in this context to prevent fraud, malpractices and other forms of mis-conduct by which service providers put their own interests or those of affiliates ahead of consumers’ or take unfair advantage of consumers’ lack of sophistication, their limited access to market alternatives and their limited economic resources.

So Consumer protection also improves governance of financial institutions. By strengthening transparency in the delivery of financial services and the accountability of financial institutions, consumer protection helps build demand for good governance and the strengthening of business standards in the financial system. Therefore this article makes an attempt to analyze the relationship between the financial consumer protection and customer satisfaction in commercial banks.

Concepts and terms

Bank

According to Prof. Sayers, “Banks are institutions whose debt-usually referred to as ‘bank deposits’- are commonly accepted in final settlement of other people’s debts”.

Customer

According to Dr.Hart, “A Customer is one who has an account with a banker or for whom a banker habitually undertakes to act as such”.

Commercial bank

Normally, the main function of a commercial bank has been to attract deposits from the public for short periods and lend them to traders, industrialists and others for short periods that is up to 12 months, by way of advances, overdraft facilities, discounting of bills and so on.

Financial consumer protection

The term financial consumer protection refers to the fair treatment, by financial services providers of their customers and potential customers. The term does not extend to prudential regulation – which is regulation intended to secure the financial soundness and effective management of financial services providers – even though one of the purposes of prudential regulation is to protect consumers.

Financial Literacy

It is the process by which financial consumers/investors improve their understanding of financial products and concepts and, through information, instruction and/or objective advice, develop the skills and confidence to become more aware of financial risks and opportunities, to make informed choices, to know where to go for help, and to take other effective actions to improve their financial well-being.

Solution approach

Scope of the Study

The research is mainly confined to the study the relationship between the financial consumer protection and customer satisfaction of commercial banks in Srivilliputtur, South town in Tamilnadu

Objectives of the Study

The following are the objectives of the study.

• To analyze the financial consumer protection in commercial banks.

• To examine the customer satisfaction of commercial banks.

• To identify the factors of financial consumer protection lead customer satisfaction.

Methodology

This study is both descriptive and analytical in nature. It covers both primary and secondary data. Primary data has been collected from the customers of commercial banks using pre-tested interview schedule. The secondary data has been collected from standard books, journals, magazines, websites and so on.

Sampling Design

Since, the population of the study is large in number; it is decided to use sampling method. To decide the sample size, the researcher has used online sample size calculator, www.surveysystem.com. According to online sample size calculator, the size 228 is appropriate sample size for this study. Then the researcher has applied purposive sampling technique to identify the sample respondents of the study.

Tools Used for Analysis

In order to analyze the financial consumer protection, the following statistical tools have been used.

• Percentage

• Factor Analysis

• Discriminant Analysis

Period of the Study

The study period covers one year from June 2014 to May 2015.

4 Analysis of results

Banking Profile of the Customers

In this article, the researcher has made an attempt to analyze the financial consumer protection in commercial banks. For this purpose, the researcher has gathered socio-economic profile of the respondents and banking profile of the customers. The details of the analysis are presented in the following Table 1 and Table 2.

Table 1 Socio-Economic profile of the respondents

S.No	Particulars	No. of Respondents	Percentage
Nature of Residence
1	Urban	149	65.35
2	Rural	79	34.65
Total		228	100.00
Gender wise Classification
1	Male	122	53.51
2	Female	106	46.49
Total		228	100.00
Age wise Classification
1	18-25 Years	70	30.70
2	26-35 Years	85	37.28
3	36-45 Years	46	20.18
4	46-55 Years	12	5.26
5	Above 55 Years	15	6.58
Total		228	100.00
Marital Status
1	Married	168	73.68
2	Unmarried	60	26.32
Total		228	100.00
Educational Status
1	Literate	199	87.28
2	Illiterate	29	12.72
Total		228	100.00
Educational Qualification
1	Primary Level	19	9.55
2	Secondary Level	29	14.57
3	Higher Secondary Level	42	21.11
4	UG Level	60	30.15
5	PG Level	22	11.05
6	Professional Course	19	9.55
7	Diploma/Certificate Course	8	4.02
Total		199	100.00
Employment Status
1	Employed	172	75.44
2	Unemployed	56	24.56
Total		228	100.00
Occupation
1	Entrepreneurs	15	8.72
2	Government Employees	61	35.47
3	Private Employees	58	33.72
4	Professionals	16	9.30
5	Agriculturists	14	8.14
6	Coolie	8	4.65
Total		172	100.00
Unemployment Details
1	Student	34	60.71
2	Job Seeker	7	12.50
3	Home Maker	5	8.93
4	Pensioners	10	17.86
Total		56	100.00
Monthly Income of Respondents
1	Up to Rs.10,000	9	3.95
2	Rs.10,000 to Rs.20,000	43	18.86
3	Rs.20,000 to Rs.30,000	92	40.35
4	Rs.30,000 to Rs.40,000	43	18.86
5	Above Rs.40,000	41	17.98
Total		228	100.00
Number of Earning Members
1	One Member	155	67.98
2	Two Members	61	26.75
3	Three Members	7	3.07
4	Four Members	5	2.19
Total		228	100.00

Source: Primary data

Table 1 shows that Out of 228 respondents, Majority of the respondents are belonging to urban area, are male, are under the age group of 26-35 years, are married, are literate, have completed under graduate degree, are employed, are government employees, are Students, have income between Rs.20,000 and Rs.30,000 per month, have one earning member in family.

Table 2 Banking profile of the customers

S.No	Particulars	No. of Respondents	Percentage
Type of Bank
1	Public Sector Bank	172	75.44
2	Private Sector Bank	56	24.56
Total		228	100.00
Number of Years deal with bank
1	Within 5 Years	113	49.56
2	6 to 10 Years	69	30.26
3	11 to 15 Years	2	0.88
4	Above 15 Years	44	19.30
Total		228	100.00
Frequency of visiting the bank per month
1	Less than 5 Times	188	82.46
2	5 to 10 Times	35	15.35
3	More than 10 Times	5	2.19
Total		228	100.00
Kind of Account
1	Savings Bank Account	218	95.61
2	Current Account	10	4.39
Total		228	100.00
Number of Account
1	One Account	141	61.84
2	Two Account	83	36.40
3	Three Account	4	1.75
Total		228	100.00
Number of Operative Account
1	One Account	159	69.73
2	Two Account	66	28.95
3	Three Account	3	1.32
Total		228	100.00
Reasons for Non-Operative Account
1	Change in Customer's Location	7	38.89
2	Lack of Reliability of Services	2	11.11
3	Poor Quality of Service	7	38.89
4	Completion of the Purpose	2	11.11
Total		18	100.00
Nature of Using the Bank Account
1	Personal	213	93.42
2	Business	15	6.58
Total		228	100.00
Average Balance
1	Below Rs.5,000	16	7.02
2	Rs.5,000 to Rs.10,000	28	12.28
3	Above Rs.10,000	184	80.70
Total		228	100.00
Number of Transaction
1	Up to 5	129	56.58
2	5 to 10	73	32.02
3	10 to 15	26	11.40
Total		228	100.00
Services availed by Customers
1	ATM Cum Debit Card	225	98.68
2	Credit Card	59	25.88
3	Internet Banking	42	18.42
4	Mobile Banking	3	1.32
5	Tele Banking	0	0.00
6	Locker Facility	66	28.95
Purpose of Opening Bank Account
1	To Save Money	87	38.16
2	Convenience	16	7.02
3	To Access Government Benefits	8	3.50
4	To Access Credit	46	20.18
5	Safety	71	31.14
Total		228	100.00
Persons Influence to open the account
1	Bank Employees	2	0.88
2	Friends and Relatives	85	37.28
3	Family Members	50	21.93
4	Government	8	3.51
5	Self Interest	83	36.40
Total		228	100.00
Factors Considered for selecting the bank
1	Need	38	16.67
2	Safety/Security	161	70.61
3	Location Factor	18	7.89
4	Convenient Facility	6	2.63
5	Better Customer Service	1	0.44
6	Reasonable Rate of Interest	4	1.75
Total		228	100.00

Source: Primary Data

Table 2 shows that Out of 228 respondents, Majority of the respondents have account in public sector bank, have opened the account with five years, are visiting less than 5 times per month, have savings bank account, have one account in bank, have operate one account in bank, reason for non operative account is change in customer’s location and another reason for non operating account is poor quality of service, have the account for personal use in bank, have above Rs.10,000 as average balance in the account, have up to five transactions in the last month, 225 respondents are availing ATM cum debit card services, 59 respondents are availing credit card services, 42 respondents are availing internet banking services, 3 respondents are availing mobile banking services, none of them is availing Tele banking services and 66 respondents are availing locker facility, open the bank account to save money, are influenced by friends and relatives and select the bank by safety/security.

Factors influencing the financial consumer protection in commercial banks

In this article, the researcher makes an attempt to analyze the factors influencing of financial consumer protection in commercial banks and studies the relationship between the financial consumer protection and customer satisfaction.

In order to analyze the factors influencing financial consumer protection, the researcher identified 44 statements from various studies already done. To get the correct opinion from the respondents the statements are designed likert five point scale technique. The SPSS software has been used to group the statements and identified the factors which influenced the financial consumer protection of commercial banks.

Table 3 shows the opinion of customers about the factors affecting the financial consumer protection.

Table 3 Factors affecting the financial consumer protection

Statement No	Particulars	SA	A	SWA	DA	SDA	Total
1.	Bank deals fairly and honestly with consumers at all stages of their relationship	2 (0.88)	115 (50.43)	103 (45.18)	7 (3.07)	1 (0.44)	228 (100.00)
2.	Care also be made and special attention given to the needs of vulnerable persons and groups	1 (0.44)	100 (43.86)	112 (49.12)	15 (6.58)	0 (0.00)	228 (100.00)
3.	Provides up to date information about products and services to customers	1 (0.44)	32 (14.04)	186 (81.57)	9 (3.95)	0 (0.00)	228 (100.00)
4.	Information are easily accessible, clear, simple to understand, accurate	1 (0.44)	72 (31.58)	74 (32.46)	81 (35.52)	0 (0.00)	228 (100.00)
5.	Discloses the details of fees, pricing and any potential penalties that the consumer may incur	0 (0.00)	36 (15.79)	159 (69.73)	32 (14.04)	1 (0.44)	228 (100.00)
6.	All decisions are taken predetermined procedure	1 (0.44)	67 (29.39)	97 (42.54)	63 (27.63)	0 (0.00)	228 (100.00)
7.	Provide all information to customer whenever they asked	0 (0.00)	39 (17.11)	155 (67.98)	34 (14.91)	0 (0.00)	228 (100.00)
8.	Decisions are taken with open minded and transparent to all	0 (0.00)	48 (21.05)	119 (52.19)	60 (26.32)	1 (0.44)	228 (100.00)
9.	Developes programmes and appropriate mechanisms to help existing and future customers	0 (0.00)	42 (18.42)	165 (72.37)	20 (8.77)	1 (0.44)	228 (100.00)
10.	Bank communicates with customer in a clear manner	0 (0.00)	48 (21.05)	147 (64.47)	31 (13.60)	2 (0.88)	228 (100.00)
11.	Bank speaks customer language	1 (0.44)	64 (28.07)	114 (50.00)	48 (21.05)	1 (0.44)	228 (100.00)
12.	Bank shares useful information that is specific to customer needs when customer need it	0 (0.00)	36 (15.79)	152 (66.66)	39 (17.11)	1 (0.44)	228 (100.00)
13.	Demonstrating on how to use services of banks to customers	0 (0.00)	43 (18.86)	136 (59.65)	48 (21.05)	1 (0.44)	228 (100.00)
14.	Bank works in a professional manner for the benefits of customers during their relationship	2 (0.88)	19 (8.33)	171 (75.00)	36 (15.79)	0 (0.00)	228 (100.00)
15.	Bank is primarily responsible for the protection of the financial interests of the customers	2 (0.88)	30 (13.16)	84 (36.84)	112 (49.12)	0 (0.00)	228 (100.00)
16.	Bank provides courteous customer service	1 (0.44)	27 (11.84)	160 (70.18)	40 (17.54)	0 (0.00)	228 (100.00)
17.	Bank treat customers friendly and respect manner	1 (0.44)	26 (11.40)	95 (41.67)	105 (46.05)	1 (0.44)	228 (100.00)
18.	Bank gives flexible, understand and respond to customers need	1 (0.44)	26 (11.40)	159 (69.74)	42 (18.42)	0 (0.00)	228 (100.00)
19.	Ensure that the transactions are as per the procedure	1 (0.44)	43 (18.86)	95 (41.66)	89 (39.04)	0 (0.00)	228 (100.00)
20.	Better employee morale	0 (0.00)	31 (13.60)	120 (52.63)	75 (32.89)	2 (0.88)	228 (100.00)
21.	Information are kept confidential	2 (0.88)	128 (56.14)	94 (41.23)	4 (1.75)	0 (0.00)	228 (100.00)
22.	Proper control on customer records	2 (0.88)	136 (59.64)	89 (39.04)	1 (0.44)	0 (0.00)	228 (100.00)
23.	Ensure the policy about protection of privacy is as per the law	2 (0.88)	89 (39.03)	135 (59.21)	2 (0.88)	0 (0.00)	228 (100.00)
24.	Separate cell complaint redressal	0 (0.00)	78 (34.21)	79 (34.65)	70 (30.70)	1 (0.44)	228 (100.00)
25.	Availability of policy and procedure for quick redressal	0 (0.00)	54 (23.68)	96 (42.11)	77 (33.77)	1 (0.44)	228 (100.00)
26.	Redressed within a stipulated time	0 (0.00)	51 (22.37)	112 (49.12)	64 (28.07)	1 (0.44)	228 (100.00)
27.	Create the consumers who are able to search, compare and where appropriate, switch between products and services	1 (0.44)	6 (2.63)	198 (86.84)	23 (10.09)	0 (0.00)	228 (100.00)
28.	Apply ethical marketing practices	1 (0.44)	23 (10.09)	63 (27.63)	141 (61.84)	0 (0.00)	228 (100.00)
29.	Provide full information to the public to take purchase decision	2 (0.88)	15 (6.58)	173 (75.88)	38 (16.66)	0 (0.00)	228 (100.00)
30.	Allow the customers act independently	1 (0.44)	24 (10.53)	76 (33.33)	127 (55.70)	0 (0.00)	228 (100.00)
31.	Create the situation for healthy competition	1 (0.44)	21 (9.21)	169 (74.12)	37 (16.23)	0 (0.00)	228 (100.00)
32.	Treat the competition as the factor to develop themselves	1 (0.44)	13 (5.70)	104 (45.61)	110 (48.25)	0 (0.00)	228 (100.00)
33.	Bank should responsible and accountable for the actions of their authorized agents	1 (0.44)	7 (3.07)	151 (66.23)	69 (30.26)	0 (0.00)	228 (100.00)
34.	Authorized agents work in the best interest of their customers	1 (0.44)	15 (6.58)	70 (30.70)	142 (62.28)	0 (0.00)	228 (100.00)
35.	Authorized agents responsible for upholding financial consumer protection	1 (0.44)	13 (5.70)	63 (27.63)	151 (66.23)	0 (0.00)	228 (100.00)
36.	Bank gives proper training to their authorized agents for betterment of service	1 (0.44)	13 (5.70)	63 (27.63)	151 (66.23)	0 (0.00)	228 (100.00)
37.	Bank have sufficient monitoring procedure to control their authorized agents	1 (0.44)	3 (1.32)	84 (36.84)	140 (61.40)	0 (0.00)	228 (100.00)
38.	All policies and procedures in written form	3 (1.32)	140 (61.40)	77 (33.77)	8 (3.51)	0 (0.00)	228 (100.00)
39.	Every transaction of bank supported by documents	1 (0.44)	101 (44.30)	123 (53.94)	3 (1.32)	0 (0.00)	228 (100.00)
40.	Operational guidance was placed in the promises of the bank	1 (0.44)	126 (55.26)	100 (43.86)	1 (0.44)	0 (0.00)	228 (100.00)
41.	The transactions carried out according to the written policies of the bank	1 (0.44)	91 (39.91)	132 (57.89)	4 (1.75)	0 (0.00)	228 (100.00)
42.	There is no oral policies or instructions	1 (0.44)	129 (56.58)	98 (42.98)	0 (0.00)	0 (0.00)	228 (100.00)
43.	All procedures and instructions are given to customers	1 (0.44)	90 (39.47)	135 (59.21)	2 (0.88)	0 (0.00)	228 (100.00)
44.	The conflicts are clarified with the support of written documents	1 (0.44)	129 (56.57)	95 (41.67)	3 (1.32)	0 (0.00)	228 (100.00)

Source: Primary data

Application of Cronbach’s Alpha Test for factors influencing the financial consumer protection- reliability test

In order to test the reliability of opinion of the customers about financial consumer protection, Cronbach’s Alpha Test has been applied and the result has been shown in Table 4.

Table 4 Reliability statistics for the opinion of the customers about FCP

Cronbach’s Alpha Score	0.880
No. of Items	44

Source: Computed data.

The Chronbach’s Alpha value of 0.880 infers that the Likert’s scale used for identifying the factors influencing the financial consumer protection of customers is considered reliable.

Factor Analysis - Analytical Framework

Various factors to determine the customers’ opinion about financial consumer protection in commercial banks are identified by the researcher. These factors are interrelated but not independent. Hence in order to group the related variable the factor analysis has been applied.

Factor analysis is a multi-variant statistical technique that explains the inter-relationship among the total set of observed variables. None of these variables is treated more differently than the others. Factors analysis is a way of grouping of variables based on the criterion of common characteristics which serve as a common denominator for such a classification. It is an analytical tool which can aid preliminary investigations and in the interpretation of the relationship among a large number of inter-related and inter-dependent variables.

There are several methods available for factor analysis. But the principle factor method with orthogonal varimax rotation is mostly used and widely available in factor analytic computer programme. One of the final outcomes of factor analysis is called rotated factor matrix, a table of coefficients that expresses the relation between the variables and the factors that have been prepared. The sum of squares of the factor loading of a variable is called communalities (h2).

The communalities of a factor are its common factor variance. The factors where factor loading is 0.50 or greater are considered significant factors. This limit is chosen because it had been judged that factors with less than 50 per cent common variation with the rotated factor pattern are too weak to report.

In the present study the principal factor analysis method with orthogonal varimax rotation is used to identify the significance of different variable of financial consumer protection in commercial banks.

Mathematically factor analysis is somewhat similar to multiple regression analysis. In factor analysis, each variable is expressed as a linear combination of the underlying factors. The amount of variance a variable shares with all the other variables included in the analysis is referred to communality. The co-variation among the variables is described in terms of a small number of common factors plus a unique factor for each variable. These factors are not over observed. If the variables are standardized, the factor model may be represented as

X₁₌A_ijF₁+A_i2F₂+A_i3F₃+……+A_imF_m+V_iU_i (1)

Where

X_i = i^th standardized variable

A_ij = Standardized multiple regression coefficient of variable i on common Factor _j

F = common factor

V_i = standardized regression coefficient of variable I on unique factor i

U_i = the unique factor for variable i

M = number of common factors

The unique factors are uncorrelated with each other and with the common factors. The common factors themselves can be expressed as a linear combination of the observed variables.

F_i=W_i1X₁+W_i2X₂+W_i3X₃+…..W_ik+X_k (2)

Where

F_{i =} estimate of i^th factor

W_{i =} weight or factor score coefficient

K = number of variables

It is possible to select weights or factor score coefficient so that the first factor explains the largest portion of the total variance. Then a second set of weight can be selected, so that the second factor accounts for most of the residual variance, subject to being uncorrelated with the first factor. This same principle could be applied for selecting additional weights for the additional factors. Thus, the factors can be estimated so that their factor scores, unlike the value of the original variables, are not correlated. Furthermore, the first factor accounts for the highest variance in the data, the second factor the second highest, and so on.

Application of factor analysis – customers opinion towards financial consumer protection

The rotated factor matrix for the variables relating to the opinion of the customers about financial consumer protection is given in Table 5.

Table 5: Rotated Factor matrix for the opinion of customers towards FCP in commercial banks

Statement No	F1	F2	F3	F4	F5	h2
S13	0.731	0.066	0.065	0.034	-0.223	0.594
S08	0.728	-0.016	0.052	0.005	0.225	0.584
S26	0.656	-0.154	0.038	0.275	0.190	0.566
S20	0.648	0.111	-0.036	-0.016	0.364	0.566
S11	0.638	0.120	0.089	0.080	-0.127	0.452
S06	0.619	0.155	0.042	0.299	0.205	0.541
S25	0.598	-0.144	0.059	0.244	0.197	0.480
S04	0.586	0.091	0.011	0.296	0.127	0.455
S19	0.505	0.270	-0.062	0.280	0.285	0.491
S29	-0.004	0.691	-0.016	0.087	0.152	0.508
S27	-0.029	0.657	0.000	0.022	0.088	0.441
S33	-0.118	0.650	0.155	0.072	0.076	0.472
S31	0.010	0.628	-0.009	0.054	0.160	0.423
S22	0.295	0.616	-0.081	-0.134	0.209	0.534
S21	0.273	0.604	-0.054	-0.158	0.276	0.544
S37	-0.096	0.583	-0.006	0.440	0.084	0.550
S35	-0.008	0.576	0.044	0.265	-0.092	0.413
S40	0.001	0.118	0.864	0.005	-0.063	0.765
S42	-0.063	0.088	0.831	0.147	-0.005	0.724
S39	0.043	0.167	-0.805	0.177	-0.020	0.709
S41	-0.075	0.228	-0.794	0.080	0.014	0.695
S44	-0.047	0.101	0.755	0.162	-0.056	0.612
S43	-0.040	0.143	-0.724	0.163	0.040	0.575
S38	0.097	0.133	0.630	-0.020	0.051	0.427
S30	0.247	0.041	0.083	0.756	0.115	0.654
S28	0.147	0.123	-0.007	0.686	0.135	0.525
S32	0.353	0.085	0.053	0.656	0.140	0.585
S34	0.145	0.206	-0.057	0.608	0.122	0.451
S36	0.093	0.283	-0.048	0.634	0.137	0.512
S01	0.061	0.230	0.048	-0.579	0.032	0.395
S18	0.100	0.237	-0.047	0.142	0.702	0.582
S14	0.095	0.212	-0.054	0.231	0.685	0.579
S16	0.085	0.288	-0.041	0.225	0.685	0.613
S12	0.442	-0.060	-0.107	-0.061	0.633	0.615

Note: Rotated Factor matrix with communalities is used to extract factors

Table 5 represents the matrix of common factor co-efficient or factor loadings. The number of factors extracted was five. The ratio which have the highest loadings ( 0.50) in each factor are grouped, that is the ratios which are more closely related to a particular group are boxed. The last column in the table is communality (h²) that is the variance explained by the factor.

Results and interpretation for the opinion of customers towards financial consumer protection in commercial banks

The factors with identified new names which influence the opinion of customers towards financial consumer protection in commercial banks are discussed in Tables 6, 7, 8, 9 and 10.

Table 6 Financial education and disclosure (Factor I)

Statement No	Variables	Factor Loading	Communality (h2)
S13	Demonstrating on how to use services of banks to customers	0.731	0.594
S08	Decisions are taken with open minded and transparent to all	0.728	0.584
S26	Redressed within a stipulated time	0.656	0.566
S20	Better Employee Morale	0.648	0.566
S11	Bank speaks customer language	0.638	0.452
S06	All decisions are taken predetermined procedure	0.619	0.541
S25	Availability of policy and procedure for quick redressal	0.598	0.480
S04	Information are easily accessible, clear, simple to understand, accurate	0.586	0.455
S19	Ensure that the transactions are as per the procedure	0.505	0.491

Source: Computed primary data.

The item with high loadings on Factor I is demonstrating on how to use services of banks to customers (0.731). Decisions are taken with open minded and transparent to all (0.728), Redressed within a stipulated time (0.656), Better Employee Morale (0.648), Bank speaks customer language (0.638), All decisions are taken predetermined procedure (0.619), Availability of policy and procedure for quick redressal (0.598), Information are easily accessible, clear, simple to understand, accurate (0.586) and Ensure that the transactions are as per the procedure (0.505). The factor I (F₁) is characterized as “Financial education and disclosure”.

Table 7 Competition and customer privacy (Factor II)

Statement No	Variables	Factor Loading	Communality (h2)
S29	Provide full information to the public to take purchase decision	0.691	0.508
S27	Create the consumers who are able to search, compare and where appropriate, switch between products and services	0.657	0.441
S33	Bank should responsible and accountable for the actions of their authorized agents	0.650	0.472
S31	Create the situation for healthy competition	0.628	0.423
S22	Proper control on customer records	0.616	0.534
S21	Information are kept confidential	0.604	0.544
S37	Bank have sufficient monitoring procedure to control their authorized agents	0.583	0.550
S35	Authorized agents responsible for upholding financial consumer protection	0.576	0.413

Source: Computed primary data.

In the second factor, provide full information to the public to take purchase decision (0.691), create the consumers who are able to search, compare and where appropriate, switch between products and services (0.657), Bank should responsible and accountable for the actions of their authorized agents (0.650), Create the situation for healthy competition (0.628), Proper control on customer records (0.616), Information are kept confidential (0.604), Bank have sufficient monitoring procedure to control their authorized agents (0.583) and Authorized agents responsible for upholding financial consumer protection (0.576). The Factor II (F₂) is named as “Competition and customer privacy”.

Table 8: Conflicts of interest (Factor III)

Statement No	Variables	Factor Loading	Communality (h2)
S40	Operational guidance was placed in the premises of the bank	0.864	0.765
S42	There is no oral policies or instructions	0.831	0.724
S39	Every transaction of bank supported by documents	-0.805	0.709
S41	The transactions carried out according to the written policies of the bank	-0.794	0.695
S44	The conflicts are clarified with the support of written documents	0.755	0.612
S43	All procedures and instructions are given to customers	-0.724	0.575
S38	All policies and procedures in written form	0.630	0.427

Source: Computed primary data.

The third factor consists of the three variables namely, operational guidance was placed in the premises of the bank (0.864), There is no oral policies or instructions (0.831), Every transaction of bank supported by documents (-0.805), The transactions carried out according to the written policies of the bank (-0.794), The conflicts are clarified with the support of written documents (0.755), All procedures and instructions are given to customers (-0.724) and All policies and procedures in written form (0.630). Factor III (F₃) is characterised as “Conflicts of interest”.

Table 9 Marketing ethics (Factor IV)

Statement No	Variables	Factor Loading	Communality (h2)
S30	Allow the customers act independently	0.756	0.654
S28	Apply ethical marketing practices	0.686	0.525
S32	Treat the competition as the factor to develop themselves	0.656	0.585
S34	Authorized agents work in the best interest of their customers	0.608	0.451
S36	Bank gives proper training to their authorized agents for betterment of service	0.634	0.512
S01	Bank deals fairly and honestly with consumers at all stages of their relationship	-0.579	0.395

Source: Computed primary data.

The fourth factor consists of the variables namely, allow the customers act independently (0.756), Apply ethical marketing practices (0.686), Treat the competition as the factor to develop themselves (0.656), Authorized agents work in the best interest of their customers (0.608), Bank gives proper training to their authorized agents for betterment of service (0.634) and Bank deals fairly and honestly with consumers at all stages of their relationship (-0.579). These variables are characterised as “Marketing ethics”.

Table 10 Behaviour and work ethics (Factor V)

Statement No	Variables	Factor Loading	Communality (h2)
S18	Bank gives flexible, understand and respond to customers need	0.702	0.582
S14	Bank works in a professional manner for the benefits of customers during their relationship	0.685	0.579
S16	Bank provides courteous customer service	0.685	0.613
S12	Bank shares useful information that is specific to customer needs when customer need it	0.633	0.615

Source: Computed primary data.

In the fifth factor, Bank gives flexible, understand and respond to customers need (0.702), Bank works in a professional manner for the benefits of customers during their relationship (0.685), Bank provides courteous customer service (0.685), Bank shares useful information that is specific to customer needs when customer need it (0.633). As the above variables relate to the behavior and work ethics, Factor V (F₅) is characterised as “Behaviour and work ethics”.

Table 11 Variables with the highest factor loadings for the factors influencing the customers towards financial consumer protection

Factor	Name of the Newly Extracted Factors	Selected Statement	Factor Loading
F1	Financial Education and Disclosure	Demonstrating on how to use services of banks to customers	0.731
F2	Competition and Customer Privacy	Provide full information to the public to take purchase decision	0.691
F3	Conflicts of Interest	Operational guidance was placed in the premises of the bank	0.864
F4	Marketing Ethics	Allow the customers act independently	0.756
F5	Behaviour and Work Ethics	Bank gives flexible, understand and respond to customers need	0.702

Source: Computed primary data.

It is apparent from Table 11 that the statement, Demonstrating on how to use services of banks to customers with factor loadings 0.731, Provide full information to the public to take purchase decision with factor loadings 0.691, Operational guidance was placed in the premises of the bank with factor loadings 0.864, Allow the customers act independently with factor loadings 0.756, Bank gives flexible, understand and respond to customers need with factor loadings 0.702 are the statements with highest factor loadings under the dimensions namely Financial Education and Disclosure (F₁), Competition and Customer Privacy (F₂), Conflicts of Interest (F₃), Marketing Ethics (F₄), Behaviour and Work Ethics (F₅) respectively. Hence these are identified dimensions (factors), which influence the financial consumer protection. Figure 1 depicts the diagrammatical presentation of factors influencing the financial consumer protection in commercial banks.

Opinion about the customer satisfaction

The researcher has gathered information from the respondents about the satisfaction level regarding services provided by the commercial banks. The details are presented in the Table 12

Table 12 Customer satisfaction

S.No	Particulars	VG	G	SWG	P	VP	Total
1.	Products/Services	1 (0.44)	138 (60.52)	89 (39.04)	0 (0.00)	0 (0.00)	228 (100.00)
2.	Formalities and Procedures	0 (0.00)	144 (63.16)	83 (36.40)	0 (0.00)	1 (0.44)	228 (100.00)
3.	Grievance Formalities	0 (0.00)	76 (33.33)	152 (66.67)	0 (0.00)	0 (0.00)	228 (100.00)
4.	Infrastructure	2 (0.88)	159 (69.73)	66 (28.95)	1 (0.44)	0 (0.00)	228 (100.00)
5.	E-Banking Services	4 (1.75)	92 (40.35)	132 (57.89)	0 (0.00)	0 (0.00)	228 (100.00)
6.	Attitude of Employees	0 (0.00)	137 (60.08)	88 (38.60)	2 (0.88)	1 (0.44)	228 (100.00)
7.	Safety/Security	2 (0.88)	108 (47.37)	118 (51.75)	0 (0.00)	0 (0.00)	228 (100.00)
8.	Reliability/Goodwill	3 (1.32)	124 (54.39)	101 (44.29)	0 (0.00)	0 (0.00)	228 (100.00)

S26

S21

S42

S43

S34

Figure 1 Financial consumer protection model for banks

Table 12 shows that 138 respondents (60.52%) have good with the statement “products/services”, 144 respondents (63.16%) have good with the statement “formalities and procedures”, 152 respondents (66.67%) have somewhat good with the statement “grievance formalities”, 159 respondents (69.73%) have good with the statement “infrastructure”, 132 respondents (57.89%) have somewhat good with the statement “e-banking services”, 137 respondents (60.08%) have good with the statement “attitude of employees”, 118 respondents (51.75%) have somewhat good with the statement “safety/security” and 124 respondents (54.39%) have good with the statement “reliability/goodwill”.

It is inferred that majority of the respondents say good or somewhat good for all the statements regard with customer satisfaction.

Level of customer satisfaction

The respondent’s level of customer satisfaction has been determined by 8 statements. These 8 statements are used to calculate the level of customer satisfaction in commercial banks. Likert’s five point scaling technique has been used to determine the level of customer satisfaction. The level of customer satisfaction has been determined by the score values calculated from 8 statements by adopting scaling technique. The responses observed for each statement in the schedule has been scored. To secure the total customer satisfaction score for the respondents, five points are given for “Very Good”, four points are “Good”, three points for “Somewhat Good”, two points for “Poor” and one point for “Very Poor” responses.

The level of customer satisfaction has been derived from the mean ( ) values of the 228 respondents. The calculated value of   is 3.55.

If the score values are greater than , it has been taken as satisfied whereas, if the score values are less than , it has been taken as dissatisfied.

The level of customer satisfaction is measured in the two levels, satisfied and dissatisfied. The respondents who have scored 3.55 and above are come under satisfied and that whose score is 3.55 and below have dissatisfied. The level of customer satisfaction of 228 sample respondents in commercial banks are shown in Table 13.

Table 13 Level of customer satisfaction

S.No	Particulars	No. of Respondents	Percentage to Total
1.	Satisfied	137	60.09
2.	Dissatisfied	91	39.91
Total		228	100.00

Source: Primary data

Table 13 shows that 60.09 per cent of the respondents are satisfied with services of commercial banks and the remaining 39.91 per cent of the respondents are dissatisfied with services of commercial banks.

Discriminant analysis

The researcher has applied the discriminant analysis to find which factor absolutely predicts customer satisfaction. For that purpose the factor analysis has been applied and the factor scores are treated as independent variable in discriminant analysis. A rule of thumb the dependent variable should be nominal or ordinal scale with two distinct parameter. So, the scale statement recorded with two factors namely satisfied and dissatisfied.

Discriminant analysis is used to predict group membership. This technique is used to classify objects into one of the alternative groups on the basis of a set of predictor variables. The dependent variable in discriminant analysis is categorical and on a nominal scale, whereas the independent or predictor variable are either interval or ratio scale in nature. Discriminant analysis is used to identify the variables / statements that are discriminating and on which people with diverse views will respond differently. The mathematical form of the discriminant analysis model is:

Y=b₀+b₁X₁+b₂X₂+b₃X₃+…..+b_kX_k (3)

Where,

Y = Dependent variable

b_s = Coefficients of Independent variable

Xs = Predictor or Independent variable

The method of estimating b_s based on the principle that the ratio of ‘between group sum of squares’ to ‘within group sum of squares’ be maximized. This will make the groups differ as much as possible on the values of the discriminant function. After having estimated the model, the b, coefficients are used to calculate Y, the discriminant score by substituting the values of Xs in the estimated discriminant model. The relative importance of the independent variables could be determined from the standardized discriminant function co-efficient and the structure matrix. The difference between the standardized and unstandardized discriminant function is that in the unstandardized discriminant function have a constant term, whereas in the standardized discriminant function, there is no constant term. Factor values obtained from Factor analysis have been used for discriminant analysis. By using SPSS, the discriminant analysis has been applied.

Wilks’ Lambda Test

In discriminant analysis the researcher should first analyze the Wilks’ Lambda test for valid of the model. Wilks’ lambda test is a test, which identifies whether the variables contribute significantly to discriminant function, if the Wilks’ lambda value is closer to zero the model is more contributed by the variable. The test also explains the group membership through Chi-Square test. If the P-value is less than 0.05, it concludes the corresponding function explains the group membership well. Table 14 shows the Chi-Square and Wilks’ Lambda values.

Table 14: Wilks’ Lambda

Test of Function(s)	Wilks’ Lambda	Chi-square	df	Sig.
1	0.877	29.294	5	0.000

Source: Computed primary data

Table 14 shows the significance of the discriminant model. The value of Wilk’s Lambda is 0.877 that is, 87.7 per cent of the variables not explained by the group differences. The Wilk’s Lambda takes a value between 0 and 1 and lower the value of Wilk’s lambda, the higher is the significance of the discriminant function. The statistical test of significance for Wilk’s lambda is carried out with the chi-squared transformed statistic, which in our case is 29.294 with 5 degrees of freedom (degrees of freedom equals the number of predictor variables) and a P value is 0.000 which is less than the cutoff point 0.05. Therefore the researcher concludes that there is a relationship between dependent and independent variables. Hence the researcher further analyses the other tests for effectiveness of the model.

Table 15 Classification results^a,b,c

		Satisfaction	Predicted Group Membership		Total
Original	Count	Satisfied	110	27	137
		Dissatisfied	53	38	91
	%	Satisfied	80.3	19.7	100.0
		Dissatisfied	58.2	41.8	100.0
Cross Validated	Count	Satisfied	109	28	137
		Dissatisfied	57	34	91
	%	Satisfied	79.6	20.4	100.0
		Dissatisfied	62.6	37.4	100.0

Source Computed primary data.

a) Cross validation is done only for those cases in the analysis. In cross validation, each case is classified by the functions derived from all cases other than that case; b) 64.9% of original grouped cases correctly classified; c) 62.7% of cross-validated grouped cases correctly classified.

Table 15 shows the classification results of discriminant model. Overall 100 per cent of the cases correctly classified in the model.

Table of Eigen value is often cited in Discriminant function analysis. The Eigen values describe the effectiveness of discriminant function. Larger Eigen values indicate that the discriminant function is more useful in distinguishing the groups and canonical correlation indicates a function that discriminates well. The canonical correlation is the multiple correlations between the predictor and the discriminant function. With only one function it provides an index of overall model fit which is interpreted as being the proportion of variance explained (R²). The Eigen values are presented in the Table 16.

Table 16 Eigen values

Function	Eigen Value	% of variance	Cumulative %	Canonical Correlation
1	0.140a	100.0	100.0	0.350

Source: Computed data

First 1 canonical discriminant functions were used in the analysis. The last column of Table 16 indicates canonical correlation, which is the simple correlation coefficient between the discriminant score and their corresponding group membership (Dissatisfied). An Eigen Value indicates the proportion of variance explained. A large Eigen value is not associated with a strong function. A high correlation indicates a function that discriminates well. The present correlation is 0.350, the square of the canonical correlation is (0.350)² = 0.123, which means 12.3 per cent of the variance in the discriminating model between a prospective group dissatisfied is due to the changes in the five predictor variables, namely Financial Education and Disclosure, Competition and Customer Privacy, Conflicts of Interest, Marketing Ethics and Behaviour and Work Ethics.

5 Conclusion

In this article the researcher made an attempt to know the relationship between the financial consumer protection and customer satisfaction in commercial banks and also analyzed the factors influencing the financial consumer protection in commercial banks, the researcher has applied factor analysis. The result reveals that the factor analysis is considered an appropriate technique for analysis of data. Factor analysis was run with 44 statements by orthogonal varimax rotation for financial consumer protection in commercial banks. The five factors have been extracted from only 34 statements; remaining statements are removed from this analysis. The five factors are named by the researcher which are (i) Financial Education and Disclosure, (ii) Competition and Customer Privacy, (iii) Conflicts of Interest, (iv) Marketing Ethics, (v) Behaviour and Work Ethics. The statement with the highest loading under each factor was identified.

From the above discussion it is evident that all the factors that have been identified are important but they all have been rated differently. By incorporating these factors in the best proportion, commercial banks can improve their financial consumer protection.

The researcher has also applied the discriminant analysis to find which factors absolutely predict customer satisfaction. From the analysis it is understood that only 12.3 percent of the variable predict the customer satisfaction. Hence factors of financial consumer protection do not have any significant influence on customer satisfaction.

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