Chapter 4 FINDINGS AND DATA ANALYSISshodhganga.inflibnet.ac.in/bitstream/10603/65866/8/08_chapter 4.pdfSyndicate Bank HDFC Bank Ltd. Magma Fincorp Ltd. Allahabad Bank Axis Bank Ltd

Chapter 4

FINDINGS AND DATA ANALYSIS

Sl. No. CHAPTER CONTENTS PAGE

4.1 Comparative Analysis of the Demographic and

181 Psychographic profiles of the populations of the two regions

4.2 Current Market Composition and Future Forecasting 222

4.3 Identifying the Key CRM Factors and Issues 229

4.4 (a) Performance of The Financing Institutions- Consumer

243 Perceptions

4.4 (b) Performance of The Financing Institutions- Channel

260 Partners' Perceptions

4.5 GAP ANALYSIS 277

- 180-

Chapter 4.1: Comparative Analysis of the Demographic and Psychographic profiles of the populations of the two regions

§ 4.1.1 Identifying the Key Demographic variables:

For identifying the key demographic variables a qualitative exploratory study was conducted

wherein the credit templates I application forms for the commercial vehicle loan was collected

from the following Financial Institutions in the organized sector.

Public Sector Bank Private Sector Bank NBFC

State Bank Oflndia, ICICI Bank Ltd. Tata Motor Finance Ltd.

Syndicate Bank HDFC Bank Ltd. Magma Fincorp Ltd.

Allahabad Bank Axis Bank Ltd. Shriram Transport Finance Ltd.

Bank of Baroda Indus lnd Bank Ltd. Sundaram Finance Ltd.

Corporation Bank Srei International Finance

Punjab National Bank GE TFS Ltd.

Bank of India Cholamandalam Finance Ltd

These templates have been thoroughly studied and coupled with an in-depth consultation with

the marketing personnel of the aforesaid Financing Institutions. This endeavor helped the

researcher to identify the key demographic variables considered by the financing Institution in

deciding whether or not the loan could be sanctioned to the applicant. For the current study the

researcher included them as the top ten demographic variables of comparison between the 2

regions. They are :

1 Age Distribution

2 Education Level

- 181 -

3 Marital Status

4. Family structure

5. No. of Years in Transport Business

.6. Annual Turn over in the transport business

7. Type of Business

8. No. of Generations in the Transport Business

9. Fleet size

10 Free to finance ratio in the fleet

For the current study 2 other variables of importance were identified. They are :

II Financing Institution preferred for the present loan

12 Financing Institution preferred for their Next Loan

These variables help the researcher to find out the satisfaction level of the customers with their

present arrangement and understanding the future preference in availing a retail Commercial

automobile loan. These variables attempted in understanding the present market share holding

pattern of the various types of Financing Institutions and further speculate on what the future

market scenario could be.

Assumptions: For the purpose of the current research it was considered that all of these

demographic variables are independent of each other and a critical comparison just gives the

researcher an approximate idea about the two populations over the two regions.

The data thus collected have been cross tabulated region wise for both Demographic and

Psychographic profiles and analyzed using the following statistical testing methods namely

i) i test for homogeneity of population

ii) Z Test

- 182-

wherever applicable to draw inferences and get an approximate idea about the demographic

and psychographic profiles of the customers of Retail Commercial Automobile Loans in

the aforesaid regions. Region I (Asansol- Burdwan) and Region II (Dhanbad- Bokaro)

§ 4.1.1 Demographic profiling

This section comprises of a descriptive analysis of the Demographic Profiling of the

Commercial Automobile owners engaged in transport business in the two Regions under

study, based on the sample survey of 360 customers (180 from each region):

i) Age wise classification:

The age wise distributions of the customer population of the two regions are as follows:

Age in years Region 1 (N = 180) Reg II (N= 180)

20-30 29 (16%) 47 (26%)

30-40 89 (49%) 97 (54%)

40-50 37 (21%) 20(11%)

50-60 25 (14%) 16 (9%)

MEAN AGE 38.22 35.28

The age w1se distribution suggests that in both the reg1ons more than 70 % of the

population are above 30 years of age. A chi square test for homogeneity of populations

reveals the following results.

1.1. test for Homoeeneity (d. f= 3, a= 0.05 Null Hypothesis Alternative Hypothesis : ·l t !! .::

,, Inference :Do HA calculated Critical !1 The 2

There is significant populations are

difference between the age 20.87 7.82 HAAccepted similar age wise

distributions of the over the 2

population in the 2 regions. regions.

- 183-

The populations over the two regions are found to be significantly different in their age

wise distribution at 5% level of significance. And on a closer look it was found that the

average of the population of Region I customers is 38.22 years and that of Region II is

35.28 Years.

Thus, it can be inferred that the average age of a Retail commercial automobile loan

customer in the Region I is higher than that in Region II. So, we can say that the customers

of Region II are earlier starters as compare to their counter parts in Region I when it comes

to getting in to the transport business and also availing a loan for procuring a commercial

automobile loan.

ii) Education level wise Classification:

The educational wise distributions of the customer population of the two regions are as

follows:

Education Level Region I (N = 180) Reg II (N= 180)

No formal schooling 13 (7%) 16 (9%) Class X 63 (36%) 67 37%) Class XII 40 (22%) 37(21%) Graduate 54 (30%) 47 (26%) Post Graduate 5 (2%) 13 (7%) Professional Qualified 5 (3%) 0

The educational level wise distribution over the two regions of the customer population of a

Retail commercial Automobile Loan reveals that the two groups are usually educated with

more than 90% of the population in both the regions are at least Class X pass or more. More

than 55% of the populations in both the Regions are having an educational level of graduate or

Post Graduate. A closer look for generalization and a statistical comparison gives the

following results as depicted in the table below:

- 184-

·l test for Homogeneity (d. f = 5, a = 0.051

Null Hypothesis : llo Alternative Hypothesis : t '1.2 Inference

HA calculated Critical There is significant

The 2 populations are difference between the 9.59 11.07 HoAccepted similar education level educational level of the wise over the 2 region population in the 2 region

The populations are similar over the 2 regton educational level wtse at 5% level of

significance and it has been found that the modal class is the matriculation level which

means that in both regions the average education level of the customers is class X pass.

However, on a close look of the data it can be further inferred that the level of Education is

higher amongst the Region I customers being more of graduates post graduates and

professional qualified then the counter parts in Region II.

iii) Marital Status wise Classification: The marital status wise distributions of the

customer population of the two regions are as follows:

Marital Status Region I (N = 180) Reg IT (N= 180)

Single 41 (23%) 36 (20%) Married 139 (77%) 144 (80%)

1.!· test for Homo2eneity (d. f= 1, a= 0.05)

Null Hypothesis: Ho Alternative Hypothesis : '1.2 '1.2 :

Inferenc~, , HA calculated Criticll

The 2 populations are There is significant

similar Marital Status difference between the 0.41 3.84 HoAccepted

wise over the 2 region Marital Status of the population in the 2 region

The profiles are found to be similar over the two regions at 5% level of significance with

having dominant no. of married in the populations.

- 185-

iv). Family Structure wise classification

The family structure wise distributions of the customer population of the two regions reveal

quite an interesting picture. They are as follows:

Family Structure Region 1 (N = 180) Reg II (N - 180)

Nuclear 97(54%) 72 (43%) Joint Family 83 (46%) 103 (57%)

·l test for Homogeneity (d. f = l, a = 0.05)

Null Hypothesis : H0 Alternative Hypothesis : x: t Inference

HA calculated Critical


similar Family difference between the 4.45 3.84 HAAccepted

Structure wise over the Family Structure of the

2 region population in the 2 region

It can thus be concluded that the populations are significantly different over the 2 regions

at, 5% level of significance, when it comes to their orientation towards the family structure

with Region II thriving mainly from a joint family structure and Region I depending mainly

on a nuclear family structure.

v) Experience in the field of Transport business:

The experience wise distributions of the customer population of the two regions reveal

quite an interesting picture. They are as follows:

No. of Years Region I ( N = 180) Region II ( N = 180)

Less than 1 years 7 (4%) 9 (6%)

1-5 Years 83 (46%) 79 (44°/o)

5-10 Years 54 (30%) 58 (30%)

> 10 Years 36 (20%) 34 (20%)

- 186-

The distribution shows that more than 90% of the population have an experience of more than

one year in the transport business out of which 50% of the population of both the regions have

an experience of five years or more in the transport business.

i test for Homogeneity (d. f = 3, a = 0.05)

Null Hypothesis: Ho Alternative Hypothesis : 1.1. i Inference


There is significant The 2 populations are difference between the similar in the number of populations of the two 0.55 7.82 HoAccepted years of experience in regions with respect to the transport business their experience in the over the 2 region transport business.

The populations can thus, be concluded to be similar in their tenure of experience in the

transport business at 5% level of significance. The distribution show the modal class in

both the region is between one and five years so it can be said that retail commercial

automobile loan customer is usually a starter in the business with an experience of less than

five years in the transport business.

vi) Annual Turnover wise classification:

The distributions of the customer population of the two regions with respect to the annual

turnover in their transport business reveal quite an interesting picture. They are as follows:

Annual Turnover in Rs. Region I (N = 180) Region II ( N = 180)

Less than 10 Lacs 146 (81 %) 144 (80%)

10 to 25 Lacs 25 (14%) 27 (15%)

25 to 50 Lacs 5 (3%) 5 (3%)

Greater than 50 Lacs 4 (2%) 4 (2%)

- 187-

The distribution shows that the population has an annual turnover of arrange within 10

Lacs. Usually the customers are new to the business and are struggling for reaching the

breakeven as a result their turnover are within limit of 10 Lacs in both the regions.

lz test for Homo2eneity (d. f = 3, a = 0.05) Alternative Hypothesis : 1.2 1.2 ;

Null Hypothesis : He Inference HA calculated Critical .i

There is significant The 2 populations are difference between the similar in the terms of populations of the two 0.09 7.82 HoAccepted Annual Turn Over in regions with respect to transport business over Annual Turn Over m the 2 region transport business.

The chi- square test for homogeneity of populations reveal that the population of the two

region are similar in their average annual turn over, at 5% level of significance, and the

modal class has been found to be less than Rs. 1 0 Lacs in both the Region.

vii) Type of Business wise classification:

Business Type Region I (N = 180) Regio* ll ( N = 180)

Family owned 25 (14%) 23 (13%)

Sole proprietorship 128 (71%) 139 (77%)

Partnership 27 (15%) 18 (10%)

The distribution reveal that the majority of the population is sole proprietorship form of

business and mostly they are either family run or self established

- 188-

l test for Homo2eneity (d. f = 2, a = 0.05)

Null Hypothesis: H0 Alternative Hypothesis : '1.2 t Inference


There is significant The 2 populations are difference between the similar in the terms of populations of the two 2.34 5.99 Do Accepted Type of Business over regions with respect to the 2 region Type of Business.

The populations in the two regions are similar, at 5% level of significance, and mostly having a

sole proprietorship from with the modal class in both regions being the same.

viii) No. of Generation in the transport Business

The distribution as per the number of generation in the transport business of the owner is as

follows over the two region.

Generation Region I (N = 180) Region II (N = 180)

First Generation 151 (84%) 144 (80%)

Second Generation 27 (15%) 39 (17%)

Third Generation 2 (1%) 5 (3%)

·l test for Homogeneity (d. f = 2, a = 0.05)

Null Hypothesis : H0 Alternative Hypothesis : '1.2 t Inference


The 2 populations are There IS significant difference between the similar in the terms of populations of the two Number of 2.34 5.99 Do Accepted

Generation in the regions with respect to

Transport Business Number of Generation in the Transport over the 2 region Business

- 189-

The results of the chi-square test depict that the populations are similar over the two

regions at 5 % level of significance and mainly comprise of the first generation

Transporters. Thus it can be said that the customers are usually the first in their family to

get in to this transport business with fleet of less then three vehicles .

ix) Fleet Size

The distribution according to the fleet size of the customers in the Transport Business is

given as follows.

Fleet Size Region I (N = 180) Region II (N = 180)

1 - 2 158 (88%) 79 (44%)

3-4 7 (4%) 68 (34%)

5-6 4 (2%) 14 (8%)

7-8 11 (6%) 18 (10%)

i! test for Homogeneity (d. f = 3, a = 0.05)

Null Hypothesis: Ho Alternative Hypothesis : 1.: xz ' Inference HA calculated Critical !

The 2 populations are There IS significant difference between the similar in the terms of populations of the two 82.42 7.82 HAAccepted Fleet Size in the

Transport Business regions with respect to

over the 2 region Fleet Size m the Transport Business

The populations are significantly different in the two regions at 5% level of significance.

Whereas, the majority of the customers are having fleet sizes of less then three vehicles in

Region I, there is a substantial population in region two having a fleet size of grater then

- 190-

three in Region II. This means that the people of Region II have started earlier and are

gradually expanding their business while the population of Region I have just taken to the

Transport business.

x) Current Preference Pattern:

In an attempt to find the current preference pattern of the customers in both the region for

the availing of retail commercial auto mobile loan it was found that the preference of the

two region differed slightly from each others.

Type ofFI Region I (N = 180) Region II (N = 180)

NBFC 104 (58%) 117 (65%)

Public Sector Bank 13 (7%) 18 (10%)

Private Bank 63 (35%) 45 (25%)

The distribution reveal that in both the regions it is the NBFCs who are more preferred in

their current purchase cycle of availing are retail commercial auto mobile loan over the

other two types of financing Institution like the public sector banks and the Private Banks.

A closer look and statistical analysis brings to light the following facts as depicted in the

table below.

"l test for Homogeneity (d. f = 2, a = 0.05)

Null Hypothesis: Ho Alternative Hypothesis : x:· t Inference


The 2 populations are There is significant difference between the similar in the terms of populations of the two of their choice of FI

for availing the retail regions with respect to their choice of FI for 4.57 5.99 HoAccepted commercial auto availing the retail mobile loan m the commercial auto mobile current purchase loan the current cycle the 2 m over purchase cycle. region

- 191 -

The current preference pattern is therefore found to be similar at 5% level of significance,

across both Region I & II. The most preferred type of FI is the NBFC and the major players

are Magma Fincorp. Pvt. Ltd. and T A TA Motors Finance Ltd.

xi) Future preference pattern :

The future preferences were sought for from the customers of the two regions in their

second purchase cycle of availing are retail commercial automobile loan from the

organized sector of the financing Institutions . The survey results have been tabulated

below.

Type ofFI Region I (N = 180) Region II (N = 180)

NBFC 75 (41%) 73 (41%)

Public Sector Bank 8 (7%) 12(4%)

Private Bank 99 (52%) 95 (55%)

The sample study reveals that the preference pattern has slightly shifted towards the Private

Banks from the NBFC and the Public Sector Banks. A Closer look and statistical

comparison gives the following information.

i' test for Homogeneity (d. f = 2, a = 0.05)

Null Hypothesis : Do Alternative Hypothesis : "l t j Inference HA calculated Critical

There IS significant The 2 populations are difference between the similar in the terms of populations of the two of their choice of FI regions with respect to for availing the retail their choice of FI for 0.88 5.99 HoAccepted commercial auto availing the retail mobile loan in the commercial auto mobile next purchase cycle loan m the next over the 2 region purchase cycle.

- 192-

There is a general shift of the consumers' preference towards the Private Sector Players

irrespective of the regions namely the HDFC Bank and ICICI Bank and they perceive that

the private banks give the dual advantage of better rates and better post delivery services.

§ 4.1.2.a Identifying the key Behavioral/Psychographic variables

The idea behind collating the psychographic I behavioral variables is to gather an

understanding of the key deciding factor/s in the choice of an FI for the Retail Commercial

Automobile Loan for a customer. In this context the AIO (Activities, Interest and Opinions)

inventory list has been considered by the researcher as the most appropriate tool which could

help the financing Institution to understand the consumer decision making process and hence

draw up a suitable CRM strategy for the Groups of customers in Region I and Region II.

The variables have been drawn up based on a purely exploratory study which featured the in

depth interview of the marketing professional of the financing Institution in the organized

sector (The 15 Financing Institutions as mentioned in the previous section) .The variables

identified are as follows :

1. Fl Choice influencers (self decision, family member, opinion leaders, dealers)

2. Loan availing propensity

3. Risk taking propensity

4. Openness to new forms of financial transactions

5. Trust Quotient

6. Orientation towards Relations (Importance of personal relations, professional

commitments, attitude towards networking)

7. Attitude towards politics

8. Food Habits (Vegetarian or Non Vegetarian)

- 193-

9. Entertainment preferences (like regular partying, watching movies, watching TV for

serials, watching TV for sports ,holidays/outings with family, holiday spot preference)

10. Family Orientation

11. Media Habits (preference of newspaper, TV, Internet as the medium, Preference of

language of communication)

12. Social Conservativeness

13. Financial Conservativeness

14. Orientation towards Aesthetics

15. Orientation towards Education

Assumption: It has been assumed for the purpose of the research that each of the above

psychographic variables are independent of each other and a critical comparison just gives the

researcher an approximate idea about the two populations over the two regions.

The above 15 variables were translated into 30 statements and where us to response by their

degree of indulgence in that particular activity categorized as always, sometimes and never.

The data thus collected is cross tabulated region wise for both Demographic and Psychographic

profiles have been analyzed using the following statistical testing methods namely

i) x2 test for homogeneity of population

ii) Z Test

wherever applicable to draw inferences and get an approximate idea about the demographic

and psychographic profiles of the customers of Retail Commercial Automobile Loans in

the aforesaid regions. Region I (Asansol- Burdwan) and Region II (Dhanbad- Bokaro)

- 194-

§ 4.1.2.b PSYCHOGRAPHIC PROFILING

I) Loan decision influencer :

The customer base of the two regions were approached with the question whose opinion

did they Bank upon while taking the final decision of where to avail the loan from. The

responses obtain are tabulated below

Loan decision Region I (N = 180) Region II (N = 180)

influencer

Self previous experience 20(11%) 42 (23%)

Dealers 38(21%) 33 (18%)

Friends 110(61%) 103(58%)

Family Members 12 (7%) 2 (I%)

The sample survey responses reveal that the major loan decision influencer in the choice of

financing Institution for availing a retail commercial automobile loan is mostly the friends

or the opinion leaders already established in the business. A Closer probe into the situation

and a statistical analysis by chi-square test reveal the following results

·l test for Homogeneity (d. f=3, a= 0.05)

Null Hypothesis: Ho Alternative Hypothesis : "/.,2 "/.,2 Inference

HA calculated Critical There is significant

The 2 populations are difference between the populations of the two

similar in the terms of regions with respect to

their preference of loan their preference of loan 15.53 7.82 HAAccepted

decision intluencers for availing the retail

decision intluencers for availing the retail

commercial auto mobile commercial auto mobile

loan 2 region loan

- 195-

The preferences for the opinions sought for in taking the final decision is significantly

different over the two regions.

The researcher on a closer study further into the situation with an attempt to draw up an

idea as to which is the most preferred source opinion for the final decision making, has

been confronted with a very interesting fact. Each of the sources has been separately tested

amongst the other sources and the results are given as follows:

For preference of Self previous experience as the loan decision influencer

Z-test for equality of proportions (a= 0.05)

Pt = 0.11, p2= 0.23 , Nt= 987, N~ 764, nt= n2= 180

Null Hypothesis : H0 Alternative Hypothesis : z z Inference

HA calculated Critical The 2 populations are The proportion of similar in the terms of population preferring self their preference of loan previous experience for decision influencers as availing the retail the self previous commercial auto mobile experience for availing loan in Region II is greater -3.45 -1.645 HAAccepted the retail commercial auto mobile loan

than the proportion m over Region I the 2 regions

Pt:::::: P2 Pt <P2

The Z-test results above suggested that Self previous experience is more acceptable

among the consumers of the Region II than in Region I. It may be so that, since we have

seen the fleet size of the customers are on an average higher then their counterparts in

Region II, they have relatively higher experience in this sort of transactions and therefore,

they bank more on their self previous experience over the other sources when it comes to

taking the vital decision of where to avail the loan from.

However, we found that, majority of the population are quite new to the business and are

just the first generation in this business. As a result, they lacked self previous experience.

Hence, it was found that in both the regions, the most preferred source of

- 196-

For preference of Opinion Leaders' views as the loan decision influencer


Pt = 0.61, p2= 0.58 , Nt= 987, N2= 764, nt= n2= 180

Null Hypothesis : H0 Alternative Hypothesis : z z

Inference HA calculated Critical

The 2 populations are The proportion of

similar in the terms of population preferring

their preference of loan Opinion Leaders' views decision influencers as for availing the retail the Opinion Leaders'

commercial auto mobile views for availing the loan in Region I is greater 0.65 1.645 HoAccepted retail commercial auto mobile loan over the 2 than the proportion in

regions Region II

P1~P2 P1>P2

Opinion is the "Friends" i.e. the experienced people who have availed such a loan and

belong to the same area and in the same business. In textual terminology we normally refer

to such individuals as "opinion Leaders" and this form of promotion is referred to as word

of mouth or buzz marketing. In both the Region l and ll majority of the population

preferred the opinion leader's view over the other sources of information while availing the

loan

For preference of Dealers' views as the loan decision influencer

Z-test for equality of proportions (a = 0.05)

PI= 0.21 ' P2= 0.18' Nt= 987, N2= 764, nt= n2= 180


Inference HA calculated Critical The 2 populations are

The proportion of similar in the terms of their preference of loan population preferring

Dealers' views for decision influencers as

availing the retail the Dealers' views for availing the retail

commercial auto mobile 0.81 1.645 HoAccepted commercial auto mobile loan in Region I is greater

loan over the 2 regions than the proportion m Region II

Pt~P2 Pt >P2

- 197-

The two regions are similar in their preferences towards dealers' opinion and keep it as the

third most preferred source for information while availing the loan.

II) Loan availing propensity :

The population of the customers over the two region were approached with the question

whether they calculate and recalculate before availing the retail commercial automobile

loan and avail it only as the last option or not. To the statement the following responses has

been obtained.

Response Region I (N = 180) Region II (N = 180)

Always 120 (67%) 135(75%)

Sometimes 56 (31%) 43 (24%)

Never 4 (2%) 2 (1%)

i' test for Homogeneity (d. f=2, a= 0.05)

Null Hypothesis : Ho Alternative Hypothesis : t t Inference HA calculated Critical

There is significant difference between the

The 2 populations are populations of the two similar in the Terms of regions in the Terms of

3.26 5.99 HoAccepted their loan availing their loan availing propensity over the 2 propensity for availing the regions retail commercial auto

mobile loan.

The populations of the two regions have responded similarly to their loan availing

propensity variable when it comes to availing a retail commercial automobile loan. It has

been found that both the populations calculate and recalculate before they take the final

decision. And it is only the ultimate option that they prefer availing the loan from the

- 198-

organized sector, so it can be concluded that the consumer of both the reg1ons are

conservative in their approach.

III) Risk taking propensity :

The consumer were approached with the statement whether hard earned money is better

then earning from shares and market linked financial products which involve high risk, to

judge the financial risk taking propensity among the group . The responses thus obtained

are tabulated here under.


Always 113(63%) 103 (57%)

Sometimes 65 (36%) 72 (40%)

Never 2 (1%) 5 (3%)

1.2 test for Homogeneity (d. f=2, a= 0.05)

Null Hypothesis : Ho Alternative Hypothesis : ·l ·l Inference HA calculated Critical

There is significant

The 2 populations are difference between the populations of the two

similar in the Terms of regions in the Terms of 2.11 5.99 HoAccepted

their risk taking propensity over the 2

their risk taking propensity

regions for availing the retail commercial auto mobile loan.

The two populations, as is evident from the results are similar in their risk taking

propensity. They can be considered that they are low to moderate risk takers with the

modal class of response featuring that they always calculate and recalculate before making

an investment or availing a loan.

- 199-

IV) Openness to new forms of financial transactions (Phone and Net Banking)

The respondents have been approached with the question whether they preferred the

modern forms of financial transaction like phone and net banking over the traditional

methods while the making the financial transactions or not. To this the responses are as

follows.


Never 103 (58%) 121 (67%)

Sometimes 62 (34%) 54 (30%)

Always 15 (8%) 5 (3%)


Null Hypothesis : H11 Alternative Hypothesis : 1.2 t Inference HA calculated Critical


The 2 populations are difference between the

similar in the Terms of populations of the two

their Openness to new regions in the Terms of 6.998 5.99 HAAccepted

forms of financial their Openness to new

transactions over the 2 forms of financial

regions transactions for availing the retail commercial auto mobile loan.

The statistical analysis of the responses bring to like that the attitude the two regions differ

significantly when it comes to handling financial and banking transaction like availing a

retail commercial automobile loan through modern means like phone and net banking,

portals etc., at 5% level of significance. Though the people of both the regions are quite

conservative yet the members of Region - I are a bit more open as compared to their

counterparts in Region II and prefer the modern methods more.

-200-

S) Trust Quotient

The customers of both the regions were approached with the question whether they prefer

to handle the financial transactions by themselves or are ready to trust and hand over the

job to the people around. The responses thus obtained are tabulated as here under


Always 131(73%) 140 (78%)

Sometimes 47 (26%) 36 (20%)

Never 2 (1%) 4 (2%)

x2 test for Homogeneity (d. f=2, a= 0.05)

Null Hypothesis: H0 Alternative Hypothesis : i "/.2


The 2 populations are There is significant similar in the Terms of difference between the their Trust on people populations of the two 2.42 5.99 HoAccepted for financial regions in the Terms of transactions over the their Trust on people for 2 regions financial transactions

The results suggest that the two populations are similar in their approach to handling of

financial transactions at 5% level of significance. It has been found that the customers of

both the regions are very cautious and they rarely trust the people around when it comes to

financial transactions and money. This result therefore is of prime importance for the

financing Institution because it is they who have to walk that extra mile to win the trust of

the customers in the financial transaction during the loan tenure.

- 201 -

6) Attitude towards relationships and networking

i) Personal relations get top prioritv: - The customers of both the regions were asked what

gets top priority for them in life whether it is the personal relation or not. To this the

responses were as in the table below:


Always 99 (55%) 68 (38%)

Sometimes 76 (42%) 90 (50%)

Never 5 (3%) 22 (12%)


Null Hypothesis: Ho Alternative Hypothesis : "1.2 "/.2 Inference HA calculated Critical

The 2 populations are There is significant difference between the

similar in the Terms of populations of the two 17.63 5.99 HAAccepted

their attitude towards personal relations in life

regions in the Terms of their attitude towards

over the 2 regions personal relations in life

There are significant differences between the populations when comes to the approach

towards personal relations over the two region, at 5% level of significance. While a

majority of the customers of Region I value the personal relations more , a majority of

customers region II give a special priority to their professional commitments .

ii) Professional commitments get top priority:

The customers of the both regions were asked whether professional commitments are more

important than their personal relations or not. To this the responses are as under.

-202-


Always 77 (43% 106 (59%)

Sometimes 99 (55%) 70 (39%)

Never 4 (2%) 4 (2%)


Null Hypothesis : Ho Alternative Hypothesis : ·l lz Inference



similar in the Terms of populations of the two

their attitude towards professional

regions in the Terms of 9.57 5.99 HAAccepted their attitude towards

commitments vis-a-vis professional commitments

personal relations in life over the 2 regions

vis-a-vis personal relations in life

The i test for Homogeneity of populations suggest that , there is significant difference

between the populations of the two regions in the Terms of their attitude towards

professional commitments vis-a-vis personal relations in life at 5 %level of significance. A

closer probe into the statistics suggests the following results.

For attitude towards professional commitments vis-a-vis personal relations in life


Pt = 0.43 , p2= 0.59 , Nt= 987, N2= 764, Dt= 02= 180

Null Hypothesis : Ho Alternative Hypothesis : z z Inference



similar in the terms of population having a

their attitude towards positive attitude towards

professional professional commitments vis-a-vis personal relations

commitments vis-a-vis in life Region II is greater -3.03 -1.645 HAAccepted personal relations in life

than the proportion in over the 2 regions Region I

Pt ::::P2 Pt <P2

-203-

A confirmatory Z test reveals that the majority of the customers of Region II is very

professional in their out look and for them professional commitments is much more

important than their personal relationships in life. A comparison with the region I gives us

an insight that the Region I people are more fond of their personal relations but the Region

II people value professional commitments more.

iii) AlTITUDE TOWARDS NETWORKING

The customer samples of the two regions were asked whether they felt that networking is

important for the success in their business or not. To this the responses are as follows.


Always 50 (28%) 93(51%)

Sometimes 124 (69%) 82 (46%)

Never 6 (3%) 5 (3%)

"1.2 test for Homogeneity (d. f=2, a= 0.05)

Alternative Hypothesis : "/..2 t :t

Null Hypothesis : Bo ij Inference BA calculated Critical

The 2 populations are There IS significant difference between the similar in the terms of populations of the two 21.58 5.99 HAAccepted their attitude towards

networking over the 2 regions in the Terms of their attitude towards regions networking

The statistical analysis suggests that there is significant difference among the populations

of the two regions in terms of their attitude towards networking at 5% level of significance.

While the customers of Region I feel that networking becomes important only on special

-204-

occasions, a majority of the customers of Region II feel that networking is always required

and is an inevitable ingredient for success in business.

7) Attitude towards politics:

The respondent were approached with the question whether political backing is required for

their success in Transport Business or not . To this the responses are tabulated below.


Always 45 (25%) 122 (68%)

Sometimes 131(73%) 58 (32%)

Never 4 (2%) 0


Null Hypothesis : H0 Alternative Hypothesis : ·l t Inference HA calculated Critical

The 2 populations are There is significant difference between the similar in the terms of populations of the 67.69 5.99 HAAccepted

their attitude towards two

Politics over the 2 regions in the Terms of

regions their attitude towards Politics.

It is clearly evident from the statistical test above that there is a significant difference

between the opinions of the customers of the two regions when it comes to politics, at 5%

level of significance. While the customers of Region I occasionally bank on their political

contacts, their counterparts in Region II bank on them as if it is a major source of

sustenance for their business and further growth.

-205-

8) Media Habits:

i) Preference of Newspaper as a Medium :

The customer samples were approached with the question whether they preferred

newspaper as a medium rather than any other media. To this the responses were as under.


Always 130 (72%) 127 (71%)

Sometimes 48 (27%) 47 (26%)

Never 2 (1%) 6 (3%)

i test for Homogeneity (d. f=2, a.= 0.05)

Null Hypothesis : Ho Alternative Hypothesis : ·l t Inference HA calculated Critical i


similar in the terms of populations of the two 2.05 5.99 HoAccepted

preference of news regions in the Terms of

paper as a medium. over the 2 regions

their preference of news paper as a medium.

The two region are similar in the cases when comes to news paper as a choice of medium

to gather information at 5% level of significance. The customers do feel comfortable to go

through news paper when it comes to gathering market related at other news concerned

with their business. Majority of them claim that they go through the news paper on a daily

basis.

-206-

ii) Preference of Hindi as a language for communication over English:

The respondent samples were approached with the query whether they preferred English or

the local region language (Bengali in Region I and Hindi Region II) as the mode of

communication. The responses are tabulated below:

Preference of English as a language for communication


Always 27 (15%) 22 (12%)

Sometimes 58 (32%) 63 (35%)

Never 95 (53%) 95 (53%)

·i test for Homogeneity (d. f==2, a= 0.05)

Null Hypothesis : Do Alternative Hypothesis : ·l' t Inference HA calculated Critical

The 2 populations are There IS significant similar in the terms of difference between the their preference of populations of the two 0.72 5.99 HoAccepted English as a language regions in the Terms of for communication over English as a language for the 2 regions communication.

Preference of Hindi I Bengali as a language for communication


Always 52 (29%) 48 (27%)

Sometimes 112(62%) 122 (67%)

Never 16 (9%) 10 (6%)

-207-

·l test for Homogeneity (d. f =2, a = 0.05)

Null Hypothesis : H0 Alternative Hypothesis : lz lz



similar in the terms of populations of the two

their preference Hindi I regions in the Terms of 1.97 5.99 HoAccepted

Bengali as a language their preference Hindi I

for communication over English over the 2

Bengali as a language for

regions communication over English.

A closer inspection and the statistical test over the two regions bring to light a very

interesting fact. There is a gross similarity in the two regions when it comes to the language

for communication majority of the customer in both the region the populations do preferred

Hindi I Bengali as the mode of communication over English, at 5% level of significance.

It can be said that the people of these two regions are fonder of being communicated with,

in their mother tongues over any foreign language. The marketers should make a note of

this fact and should design all templates and literature for communication in both English

and the regional language. This will bring them one step closer to the customers.

iii) Preference of Television as a media:

The consumer samples were asked whether they preferred television over other medium for

viewing and gathering infonnation or not. The responses are here by tabulated below.

Response Region I (N = 180) Region ll (N = 180)

Always 110 (61%) 83 (46%)

Sometimes 61 (34%) 79 (44%)

Never 9 (5%) 18 (10%)

-208-


Null Hypothesis: Ho Alternative Hypothesis : 1..7. 1..7. Inference



similar in the terms of populations of the two 9.09 5.99 HAAccepted

their preference of television as a medium

regions in the Terms of

over the 2 regions their preference of television as a medium.

There is significant difference in the choice of preference Television viewing for news

among the customers of the two Regions, at 5% level of significance. The customers, we

find hold a majority of the populations in Region I are regular viewers of television news

and they out number their counter parts of region two who are mere occasional viewers.

iv) Preference oflnternet as a medium.

The respondents were asked whether they preferred internet as a source of information or

not. The responses are tabulated as follows:


Always 23 (13%) 22 (12%)

Sometimes 43 (24%) 34 (19%)

Never 114 (63%) 124 (69%)

7..2 test for Homogeneity (d. f=2, a= 0.05)

Null Hypothesis: H0 Alternative Hypothesis : 1..2 t Inference



similar in the terms of populations of the two 1.49 5.99 HAAccepted

their preference of Internet as a medium


over the 2 regions their preference of Internet as a medium.

-209-

The two regions are in general similar in their attitudes towards using Internet as a medium

for gathering information at 5% level of significance. Both the populations are not so

techno savvy and prefer old and traditional modes of medium like news papers and

television for gathering information. It can thus be said that e-banking and e-loan portals

are yet to be accepted by the populations of both this regions. The financing Institutions

should therefore concentrate more on the traditional modes of communication.

9) Food habits:

The customers of both the regions were approached for their preference of Vegetarian food

over Non-veg food. The responses are tabulated below:


Always 59 (33%) 29 (16%)

Sometimes 92 (51%) 99 (55%)

Never 29 (16%) 52 (29%)

·l test for Homogeneity (d. f =2, a = 0.05)

Null Hypothesis : H 0 Alternative Hypothesis : x.z t Inference

HA calculated Critical '


similar in the terms of difference between the 17.02 5.99 HAAccepted

their food habits over populations of the two

the 2 regions regions in the Terms of their food habits

There is a significant difference between the customers of the two regions in terms of their

food habits at 5 % level of significance.

- 210-

For attitude towards Non Vegetarian food.


PI= 0.84' P2= 0.71 ' Nt= 987, N~ 764, n1= n2= 180




similar in the terms of population having a

their food habits positive attitude towards over non-vegetarian food 1.645 HAAccepted the 2 regions m 3.36 Region I is greater than the

Pt::::: P2 proportion in Region II

Pt >P2

A closer look and a statistical analysis helps us to conclude that the proportion of Non

vegetarian are more in Region I than in Region II. It can also be said that the customers

residing in this zone of Region I are mostly Bengalis, Sikh and Muslims, who are primarily

non vegetarians. However, the customers of Region II are basically North Indian and Bihari

and are more adapted to the North Indian culture of vegetarianism. The Muslim and Sikh of

Region II also have adapted to the culture of north India and preferred to be more of an

occasional non vegetarian than a perpetual one.

10) Entertainment preferences:

i) Partv habits: The customers of both the regions have been approached with the question

whether they preferred partying on a regular basis or not. The responses are tabulated as

under


Always 50 (28%) 43 (25%)

Sometimes 105 (58%) 95 (54%)

Never 25 (14%) 37 (21%)

-211-

l test for Homogeneity (d. f =2, a = 0.05)

Null Hypothesis : Ho Alternative Hypothesis : 1..z t Inference



The 2 populations are difference between the

similar in the terms of populations of the two 3.28 5.99 HoAccepted

their partying habits regions in the Terms of their partying habits i.e.

over the 2 regions they prefer partying regularly

The statistical analysis of the data so obtained reveals that the two regions are similar in

their partying habits at 5% level of significance. Majority of the customers prefer partying

regularly as an entertainment option.

ii) Watching movies: The respondents were asked whether they preferred watching movie

as an entertainment option or not. The responses are tabulated below.


Always 52 (29%) 48 (27%)

Sometimes 112 (62%) 122 (67%)

Never 16 (9%) 10 (6%)

l test for Homogeneity (d. f=2, a= 0.05)

Null Hypothesis : Ho Alternative Hypothesis : 1..z 1..z


The 2 populations are There is a significant difference between the

similar in the terms of populations of the two their watching movie regions in the Terms of 1.97 5.99 HoAccepted as an entertainment their preference of option over the 2 watching regions

movie as an entertainment option.

The two regions are similar in their movie watching habits. Majority of their customers of

the two regions are occasional viewers of regional language and Hindi Movies.

-212-

iii) Watching television serial: The respondents have been asked whether they preferred

watching TV Serial as an entertainment option or not. The responses are as under.


Always 57 (32%) 49 (27%)

Sometimes 94 (52%) 86 (48%)

Never 29 (16%) 45 (25%)

x2 test for Homogeneity (d. f=2, a= 0.05)

Null Hypothesis : Ho Alternative Hypothesis : l l Inference


The 2 populations are There is a significant difference between the

similar in the terms of populations of the two their approach regions in the Terms of 4.42 5.99 HAAccepted

towards watching their preference of

television serial as an entertainment options.

watching television serial

over the 2 regions as an entertainment options.

The customers of both the regions are more or less similar in their entertainment habits

when it comes to watching TV Serial for entertainment, at 5% level of significance. A

majority of them are only occasional viewers of such entertainment programme on

television.

iv) Watching Television sports: The customer sample of both the regions were asked

whether they preferred watching television for sports programme or not. The responses are

as below.


Always 96 (53%) 94 (52%)

Sometimes 79 (44%) 67 (37%)

Never 5 (3%) 19(11%)

-213-


Null Hypothesis : Ho Alternative Hypothesis : 1.!' ·l Inference

HA calculated Critical The 2 populations are There is a significant similar in the terms of difference between the their approach populations of the two towards watching regions in the Terms of 9.17 5.99 HAAccepted television sports as an their preference of entertainment options. watching television sports options. over the 2 as an entertainment regions options.

The two regions differ substantially in their interests in sports viewing on Television at the

5% level of significance. The people of Region I are found to be greater lovers of sports

then those of Region II. A confirmatory Z test for proportion suggests similar views.

For attitude towards watching sports on television


PI= 0.97 , pz= 0.89 , Nt= 987, Nz= 764, nt= nz= 180

Null Hypothesis : Ho Alternative Hypothesis : z z


The 2 populations are The proportion of similar in the terms of population having a their attitude towards positive attitude towards sports over the 2 watching sports on TV in 3.41 1.645 HAAccepted regions Region I is greater than the

proportion in Region II Pt ::::Pz Pt>Pz

v) Holidays I Outing with (amilv: In order to find out whether allowing and outing or

holiday is a lucrative option for entertainment among this customers or not an approach

has been made. The responses are as below :


Always 29 (16%) 9 (5%)

Sometimes 110(61%) 103 (57%)

Never 41 (23%) 68 (38%)

-214-

"J! test for Homogeneity (d. f=2, a= 0.05)

Null Hypothesis : Ho Alternative Hypothesis : ·l ·l Inference


The 2 populations are There is a significant similar in the terms of difference between the their preference of a populations of the two

17.44 5.99 HAAccepted family holiday or regions in the Terms of outing as an their preference of a entertainment option. family holiday or outing as over the 2 regions an entertainment option.

The two populations differ significantly when it comes to their attitude towards spending

time with their family and taking them out for dinner, at 5% level of significance.

For attitude towards Holidays I Outing with family


Pt = 0.77, Pr 0.62, Nt= 987, N2= 764, nt= n2= 180

Null Hypothesis : Ho Alternative Hypothesis : z z


The 2 populations are The proportion of similar in the terms of

their attitude towards population having a

Holidays I Outing with positive towards Holidays

family over the 2 I Outing with family in 3.52 1.645 HAAccepted regions Region I is greater than the

proportion in Region II

Pt::::: P2 Pt >P2

A confirmatory Z test for proportion help us to conclude that the people of Region I do

prefer spending time with their family and children more than their counter parts of Region

II and they seriously consider family outing as an entertainment option . They usually

prefer religious places more than simple site seeing. Holidays are definitely preferred a

break and a majority of the population in both the regions do take it as a most preferred for

an entertainment than simple watching movies, or television, or sports on television or

meeting celebrities or partying . Thus, this form of entertainment may be considered by the

-215-

financing Institution as an incentive to the customers and may be included in their CRM

Strategy.

11) Belief in God.

The respondents have been verified for their trust in god the Supreme power and were

asked the question whether they believed in the existence of God. The responses are

tabulated as below:


Always 124 (69%) 131 (71%)

Sometimes 56 (31%) 49 (29%)

Never 0 0

7..2 test for Homogeneity (d. f=2, a= 0.05)

Null Hypothesis : He Alternative Hypothesis : 1..2 1..2 Inference


The 2 populations are There is a significant similar in the terms of difference between the their attitude populations of the two 0.66 5.99 HoAccepted towards the belief of regions in the Terms of existence of God over attitude towards the belief the 2 regions of existence of God.

The populations of both the regions are staunch believers of the Supreme power "God"

irrespective of the religion, educational back ground and economic status. As a result of

this belief it has been found that the default rates are much lesser.

12) Attitude towards aesthetics:

i) Aesthetics important for attracting customers: - In order to know the opinions of the

people of the two regions whether they felt that Aesthetics are important for attracting of

the customers in the business or not. The responses hence obtained are given below:

- 216-


Always 104 (58%) 83 (46%)

Sometimes 74(41%) 90 (50%)

Never 2 (1%) 7 (4%)


Alternative Hypothesis : lz lz : Null Hypothesis : Ho

HA calculated Critical Inference

The 2 populations are There is a significant

similar in the terms of difference between the

their belief of populations of the two 6.69 5.99 HAAccepted importance of aesthetics


for attracting customer their belief of importance

over the 2 regions of aesthetics for attracting customers.

The results prove that there is significant difference in the attitude of the people of the two

regions with regard two the importance they place on Aesthetics for attracting customers in

business. It has been found that Region I people seem to have a stauncher belief in the

importance of Aesthetics in business. A confirmatory Z test in this regard reinforces the

concept.

For attitude towards importance of aesthetics in business


Pt = 0.58, p2= 0.46, Nt= 987, N2= 764,

Null Hypothesis : Ho Alternative Hypothesis : Z HA calculated

The 2 populations are The proportion of similar in the terms of population having a their attitude towards positive attitude towards importance of aesthetics importance of aesthetics in in business over the 2 business in Region I is regions greater than the proportion

in Region II Pt::::: P2 Pt > P2

2.57

- 217-

z I Critical

1.645

Inference

HAAccepted

ii) Aesthetics as an indicator of quality of service rendered:

To find whether the population agreed on the particular concept that aesthetics and physical

ambience positively tangibilize the intangible offer in services or not. The responses are

tabulated as given under:


Always 85 (47%) 68 (38%)

Sometimes 94 (52%) 103(57%)

Never 2 (1%) 9(5%)

i test for Homogeneity (d. f=2, a= 0.05)

· Null Hypothesis : Ho Alternative Hypothesis : t t Inference


The 2 populations are There is a significant similar in the terms of difference between the their belief of populations of the two 6.75 5.99 HAAccepted aesthetics are an regions in the Terms of important indicator of their belief aesthetics are service quality rendered an important indicator of over the 2 regions service quality rendered

The two populations are significantly different at 5% level of significance in their opinions

as to whether aesthetics are an indicator of quality or not. The majority of customers of

Region I do staunchly belief that aesthetics are definitely an important indicator of quality

where as the majority ofthe customers of Region II differ from them.

- 218-

13. Attitude towards education :

To understand the attitude towards education the respondents of the two regions were

approached with the question whether they felt that education is important for success in

business or not .To this question, the responses are as under:


Always 108 (60%) 92 (51%)

Sometimes 70 (39%) 85 (47%)

Never 2 (1%) 3 (2%)

l test for Homogeneity (d. f=2, o. = 0.05)

Alternative Hypothesis : t t ·'I

Null Hypothesis : Ho -~

Inference ri HA calculated Critical ·l

The 2 populations are There is a significant difference between the similar in the terms of populations of the two 2.93 5.99 HoAccepted

their attitude towards education over


the 2 regions their attitude towards education

The responses were found to be similar over the two regions at 5% level of significance.

Both of the groups are equally education conscious and feel education is required for the

success in business

14. Social conservativeness:

To determine what level of social conservativeness is prevalent among the populations of

these two regions, the respondents have been asked whether they would prefer women as

their employees or not. The responses are tabulated here by:

- 219-


Always 16 (8%) 7 (4%)

Sometimes 77 (43%) 67 (37%)

Never 87 (49%) 106 (59%)


Null Hypothesis : Ho Alternative Hypothesis : lz lz Inference

HA calculated Critical The 2 populations are There is a significant similar in the terms of difference between the their social populations of the two conservativeness in regions in the Terms of 6.09 5.99 HAAccepted terms of their attitude their social towards women in the conservativeness in terms society over the 2 of their attitude towards regions women in the society

The two populations differ significantly in their approach towards women and social

conservativeness. A confirmatory Z test for proportion suggests that the customer in

Pegion I are less socially conservative then those of Region II. And they are more open to

their women folk joining them in their offices and managing them.

For attitude towards women in the society


Pt = 0.58, p2= 0.46, Nt= 987, N2= 764,

Alternative Hypothesis : Z Null Hypothesis : He HA calculated

The 2 populations are similar in the terms of The proportion of their attitude towards population having a social conservativeness positive attitude towards in terms of their attitude importance of aesthetics in towards women in the business in Region II is society over the 2 greater than the proportion regions in Region I

Pt <P2

-2.145

-220-

z ; Criticai

-1.645

Inference

HAAccepted

15) Orientation towards the family structure :

In order to find out whether the 2 population preferred to have small family to extended

family the respondent of both regions were approached for the same. The responses are

tabulated below:-


Always 135(75%) 131 (73%)

Sometimes 34 (19%) 31 (17%)

Never II (6%) 18 (10%)

i test for Homogeneity (d. f=2, a= 0.05)

Null Hypothesis: Bo Alternative Hypothesis : ·l l~ Inference HA calculated Critical

The 2 populations are There is a significant

similar in the terms of difference between the

their attitude towards populations of the two 1.89 5.99 HoAccepted

family structure over regions in the Terms of

the 2 regions their attitude towards family structure

There is a general tendency of preferring small families to extended ones in both the region

irrespective of the region.

- 221 -

Chapter 4.2- Current Market Composition and Forecasting

4.2.1 Current Preference Pattern

The random sample survey of 360 transporters, 180 in each region, who have availed a retail

loan to purchase the Commercial Automobile, in between the time period of two financial

years FY 2006-2007 and FY 2007-2008, in the regions ofBurdwan- Asansol and Dhanbad to

Bokaro , revealed the results mentioned in the table (table 4.2.1.a) below.

Table 4.2.l.a

TypeofFI Region I (N = 180) Region II (N = 180)

NBFC 104 (58%) 1 I 7 (65%)


Private Bank 63 (35%) 45 (25%)

It is found that only 7 % of the loans in Region I and J 0% of the loans in Region II have been

funded by Public Sector Banks and that too mostly by SBI and closely behind was Allahabad

Bank and Punjab National Bank and Corporation Bank and so on.

The Private Sector Banks like ICICI Bank Ltd. & HDFC Bank Ltd. who held on to about 35%

of the total market share in Region I and 25% of the total market share in Region II were

promising players and had a very positive image in the mental map of the existing Customers.

About 58 % of the vehicles in Region I and 65 % of the vehicles are funded by the NBFCs.

Again here Tata Motor Finance Ltd., of Tata Motors lead the race closely behind was Magma

Fincorp Ltd. (erstwhile Magma Leasing Ltd. and Magma Sraachi Finance Ltd.), Sundaram

-222-

Finance and SREI Transport Finance etc. In fact the present share holding pattern reveals that

the NBFCs are the market leaders in this segment of Retail Commercial Automobile loans.

4.2.2 Future Preference Pattern:

The same groups of respondents over the two regions Region I (Burdwan - Asansol) and

Region II (Dhanbad to Bokaro) have been approached for their future preference of Financial

Institution in the Next Purchase cycle and the results were quite interesting and as tabulated

below:

Table 4.2.2

TypeofFI Region I (N = 180) Region II (N = 180)

NBFC 75 (41%) 73 (41%)


Private Bank 99 (52%) 95 (55%)

There is a marked change in the preference pattern. Only 41% of the respondents in both the

Regions preferred the loan from the NBFC in the next purchase cycle. The preferences for the

Public Sector Banks too have gone down to mere 7% and 4% in Region I and II respectively.

The emerging leaders are the Private Banks and the reason which was mainly cited by the

respondents is the superior service quality and the professionalized relationship handling by

this category of players.

A closer look at the situation and hence drawing up the Transition probability matrix do re-in

force the pattern. Plates ( 4.2.2.a & b) represent the current to future transition cross tabulation

of the preference over Region I.

-223-

Private Banks 35%

Region I

Public Sector

.--oc::::::----- Banks

7%

58%

Current Market Share Pattern

Plate 4.2.2.a

The Transition Probability Matrix and the Markov Chain Analysis reveal that in Region I the

preference for the Private Banks will go up to as high as 55% in the next purchase cycle.

-224-

P=

Region I

The Corresponding Transitional Probability Matrix

0.23 0.31 0.46

0.04

0.02

0.54

0.21

0.42

0.77

The corresponding initial state probability solution:

Q(O) = ( 0.07 0.58 0.35 )

Plate 4.2.2.b

The stage 1 probability solution. (i.e. the states in the next purchase cycle )

Q(1) = ( 0.0463 0.4084 0. 5483 )

The steady state probability solution (in the long run)

a·= { o.o334 o.3184 o.6482 }

The Steady State probability solution in plate 4.2.2.b suggests that the market share that will

be held in the long run, if every other factor remains unchanged , by each category of Fl

likewise (Public Sector Banks, NBFCs, Private Banks) would be 3.34% with the Public Sector

Banks, NBFC s would be holding 31.84% and Private Banks will continue leading with a

64.82% share of the market in Region I.

-225-

The figures in Region II also depict similar results. Plates ( 4.2.2.c & d) represent the current to

future transition cross tabulation of the preference over Region II.

Private Banks

Region II

65%

Current Market Share Pattern

Public Sector Banks 10%

Plate 4.2.2.c

The Transition Probability Matrix and the Markov Chain Analysis reveal that in Region II the

preference for the Private Banks will go up to as high as 53 % in the next purchase cycle, as is

evident from stage I transitional probability solution in Plate 4.2.2.d. The market share is likely

to dip for the NBFCs from 65% to 41% in the next purchase cycle.

-226-

P=

Region II

The Correspondinq Transitional

0.22

0.05

0.04

0.28

0.50

0.22

0.50

0.45

0.73

The corresponding initial state probability solution:

Q(O) = ( 0.1 0.65 0.25 )

Plate 4.2.2.d

The stage 1 probability solution. (i.e. the states in the next purchase cycle )

Q(1) = ( 0.0645 0.4080 0. 525 J The steady state probability solution (in the long run)

a·= { o.o526 o.3o99 o.6375 }

The Steady State probability solution in plate 4.2.2.d suggests that the market share that will

be held in the long run, if every other factor remains unchanged , by each category of FJ

likewise (Public Sector Banks, NBFCs, Private Banks) in Region II would be 5.26% with the

Public Sector Banks, NBFC s would be holding 30.99% and Private Banks will continue

leading with a 63.75%.

This analysis is thus an indicator of the trend of the consumer perceptions about the three

classes of financing institutions dealing in Retail Commercial Automobile loans and is forms

-227-

the foundation of our further study which would definitely be hinged on to find an answer to

this trend. The research makes an effort to unveil the reason and find out whether the CRM

strategies of the three classes of Players have any role to play to create such a perception

among the consumers over both the regions.

-228-

Chapter 4.3: Identifying the Key CRM factors and issues

Phase I:

The exploratory study in the fonn of in-depth interview of the marketing personnel of the

18 Financial Institutions (mentioned in the Methodology section 3.6.3) revealed the

following 32 practices being used presently by the various Financing Institutions for their

continuous CRM:

1. Flexibility in negotiation on interest rates ( for preferred customers allowed by

Pvt. Banks & NBFCs)

2. Flexibility in no.of docs submission ( for preferred customers allowed by Pvt.

Banks & NBFCs)

3. Flexibility in docs submission in tenns of time (for preferred customers allowed

by Pvt. Banks & NBFCs)

4. Flexibility in credit profile judgment ( for preferred customers allowed by Pvt.

Banks & NBFCs)

5. Field Investigation visit (made optional/ customary in special cases by Pvt. Banks

&NBFCs)

6. Flexibility in down payment amounts (preferred customers usually get this)

7. SERVICE in collection of Pre-Disbursal docs

8. SERVICE in Agreement Signing

9. Flexibility in negotiation on Moratorium

10. Flexibility in choice of mode of Repayment

11. SERVICE in PDD collection

12. Welcome kit at the start of the tenure

-229-

13. Amortization Schedule at the beginning of the tenure clearly mentioning the

Interest and Principal amount components in an EMI

14. Copy of Agreement at the beginning of the tenure

15. Tum Around Time in Disbursal Order sanction (Promptness gives a competitive

edge to the Financing Institutions )

16. Regular Statement Of Accounts

17. Statement Of Accounts whenever asked for

18. Assistance in insurance renewal

19. Courtesy call2 days prior to EMI date

20. Thank you call for on time payment

21. SERVICE in EMI Collection

22. EMI can be paid from anywhere in the country

23. Soft Call in 30days default

24. Hard calls in 60 days default

25. Delay Payment Charges for 1 month delay(*** which is revocable for preferred

customers)

26. Regular Updates on other products

27. Efficient grievance handling (Promptness gives a competitive edge to the

Financing Institutions)

28. Family like relations (Empathy, Responsiveness, Assurance, Reliability)

29. Foreclosure easy and fast process (Promptness gives a competitive edge to the

Financing Institutions )

-230-

30. No Objection Certificate release proactive and fast(Promptness gives a

competitive edge to the Financing Institutions )

31. Benefits in repeat funding (special rates, top-up loans etc.)

32. Regular Feedback and Opinions sought in the form of Customer meetings to

develop and re-engineer the existing products and service.

These 32 practices are normally followed by the Financing Institutions, either as a whole

or partially. According to the respondents the customers who have developed a relationship

with such a service business not only expect to receive satisfactory delivery of core service

but also different types of relational benefits through effective customer relationship

management. Customers derive social benefits from long-term relationships with service

firms

In addition to the benefits received from core service, a kind of friendship often occurs

between customer and service providers. A second set of relational benefits reported by

respondents can be described as psychological benefits. Customers realize that there is often

a feeling of comfort and security in having developed a relationship with the service

provider. These feelings of reduced anxiety, trust, and confidence in the provider appear to

develop over time only after a relationship has been established between the customer and the

service providing organization.

The financial benefits relate to discounts or price breaks for those customers who have

developed a relationship with an organization. In addition to monetary benefits, customers

also enjoy non-monetary benefits as well. The economic benefits that customers receive for

engaging in relational exchanges, both monetary and in the form of time saving, are

consistent with what scholars have argued is the primary motivation for developing

relationships with businesses. For their regular customers many service providers may tailor

- 231 -

their service to meet particular needs. In some cases this may be perceived by customers as

preferential or special treatment.

Phase II (Factor Analysis):

KMO and Bartlett's Test (Table 4.3.11 1):

Kaiser-Meyer-Oikin Measure .649

of Samplin2 Adequacy.

Approx. Chi-Square 271.354 Bartlett's Test of Sphericity df 28

Sig. .000

The 32 variables identified in the previous study were further analyzed using the SPSS

factor Analysis package and could be grouped into 10 distinct components

Following the diagnostic KMO-Bartlett's test of Sphericity as is evident in the Table

4.3.II.l above it is seen that The Kaiser-Meyer-Olkin Measure of Sampling Adequacy

indicates the proportion of variance in the variables which is common variance, i.e.

which might be caused by underlying factors. The High value of 0.649 (greater than 0.5)

indicates that a factor analysis may be useful with the data. The Bartlett's test of

sphericity indicates the significance level to have very small values (much less than .05)

indicate that there are probably significant relationships among the considered variables.

Thus Factor Analysis may be used and the results are as under.

The SPSS factor Analysis Principle Component method identifies 10 components having

Eigenvalues more than las is evident from the SPSS output tables below (table 4.3.II. a

&b):

-232-

Initial Compo Eigenvalues

nent

Total

1 6.560 2 4.838 3 4.557 4 3.324 5 2.879 6 2.705 7 1.975 8 1.675 9 1.308 10 1.034 11 .619 12 .192 13 .167 14 7.737E-02 15 4.572E-02 16 3.719E-02 17 5.410E-03 18 1.713E-15 19 1.023E-15 20 9.146E-16 21 6.346E-16 22 3.756E-16 23 1.612E-16 24 1.119E-16 25 2.459E-17 26 5.339E-18 27 1.469E-31 28 -2.755E-32 29 -2.750E-17 30 -2.163E-16 31 -6.094E-16 32 -1.200E-15

Total Variance Explained (SPSS Output)

Extraction Rotation Sums of Sums of Squared Squared Loadings Loadings

%of Cumulativ Total %of Cumulative Total Variance e% Variance % 20.501 20.501 6.560 20.501 20.501 5.060 15.119 35.620 4.838 15.119 35.620 4.930 14.240 49.860 4.557 14.240 49.860 4.069 10.387 60.247 3.324 10.387 60.247 4.022 8.998 69.245 2.879 8.998 69.245 3.080 8.454 77.699 2.705 8.454 77.699 3.067 6.171 83.870 1.975 6.171 83.870 1.921 5.234 89.104 1.675 5.234 89.104 1.847 4.089 93.193 1.308 4.089 93.193 1.732 3.230 96.423 1.034 3.230 96.423 1.128 1.936 98.359 .601 98.959 .523 99.482 .242 99.724 .143 99.867 .116 99.983

1.691E-02 100.000 5.354E-15 100.000 3.197E-15 100.000 2.858E-15 100.000 1.983E-15 100.000 1.174E-15 100.000 5.037E-16 100.000 3.497E-16 100.000 7.686E-17 100.000 1.668E-17 100.000 4.590E-31 100.000 -8.608E-32 100.000 -8.595E-17 100.000 -6.761 E-16 100.000 -1.904E-15 100.000 -3.749E-15 100.000

Extraction Method: Pnnc1pal Component Analysis.

(Table 4.3.11 a):

-233-

%of Cumulative Variance % 15.811 15.811 15.407 31.218 12.715 43.933 12.569 56.502 9.626 66.128 9.584 75.712 6.002 81.714 5.773 87.487 5.412 92.899 3.524 96.423

Rotated Component Matrix (SPSS Output) Components

1 2 3 4 5 6 7 flexibility in negotiation on rates

flexibility in no. of docs submission .967 flexibility in docs submission in terms of time .963

flexibility in credit profile judgment

Field Investigation visit flexibility in down payment amounts

SERVICE in collection of Pre-Disbursal docs .991 SERVICE in Agreement Signing .990 !flexibility in negotiation on Moratorium iflexibility in choice of mode of Repayment

~ERVICE in PDD collection .996 Welcome kit .985 ~mort Schedule .969 !Copy of Agreement .985 ~AT in DO sanction .996 regular SOA .967 ~OA whenever asked for .983 ~ssistance in insurance renewal .987 ~ourtesy call .985 ~hank you call for on time payment .986 ~ERVICE in EMI Collection .983 IEMI can be paid from anywhere in the country .992

IHardcalls in 60 days .988 No DPC for 1 month delay .900 Regular Updates on other products .963 Efficient grievance handling .828 ~amily like relations .979 Fore closure easy and fast process .986 NOC release proactive and fast .983 Benefits in repeat funding .789 Soft Calls in 60 days .986 Feedback sought for service designing .983 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 6 iterations. b Component 1 : Information dissemination and Relational Incentives c Component 2 : Transparency in Operations d Component 3 : EM! Collection e Component 4 : Augmented Services f Component 5 : Default Management g Component 6: TAT in Services h Component 7: Flexibility in documentation i Component 8 : Flexibility in choice of mode of Repayment j Component 9 : Flexibility in Rates k Component 10: Flexibility in Credit Profile Judgement

Table 4.3. II b

8 9 10 .896

.719

.772 .913

.936

.935

The components thus identified from table II (a & b) can be explained as follows:

Component 1: Information dissemination and Relational Incentives

Component 2: Transparency in Operations

Component 3: EMI Collection

Component 4: Augmented Services

Component 5: Default Management

Component 6: TAT in Services

Component 7: Flexibility in documentation

Component 8: Flexibility in choice of mode of Repayment

Component 9: Flexibility in Rates

Component 10: Flexibility in Credit Profile Judgment

Scree Plot 8~----------------------------------------------~

6

4

2

Q)

~ 0 ~~-~~~~~nH~~~] ro > c Q) 0>

w -2~----~~~~--------~~--~~~~----~----~~ 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

Component Number

-235-

The underlying factors govern the CRM strategies of the Financial Institutions in this

segment.

A closer look at the components however gives way to further refinement of the 10

factors thus identified, to answer three major issues in relationship (as tabulated in table

4.3.11 c). They are:

i) Flexibility Issues

ii) Transactional Issues and

iii) Relational Issues

Table 4.3.11 c ' ~ -rr ~ ~'?¥~%"" ~ ~~~}Jlo/Dr'f.o/:f ~· ,v~o/')Y

! ~ I,' ''em•· ll l.l• ~·:'l'lllj;~. '"·~~ ,,;L,:, , ~" ,x ,, '

Factor I Flexibility in documentation

Factor 2 Flexibility in CREDIT PROFILE JUDGEMENT Flexibility in CHOICE OF MODE OF

Factor 3 ~EPAYMENT

IFiexibility in INTEREST RATES AND Factor4 DOWNPA YMENT

Factor 5 [Transparency in Operations

Factor 6 if AT in Service

Factor 7 !Augmented services

IF actor 8 IEMI Collection

IF actor 9 Default management

!Factor 10 nfo dissemination &Relational incentives

,,, ,,;,

:~ lli!HJJJ ~~··' ,:, !Jr, •·

7 16

10 2,3 Flexibility Issues

8 4,5

9 9,10

2 12,13,14,16,17

6 15,28,29 rrransactional iTssues

4 7,8,11,18

3 19 20 21,22

5 23,24 31 !Relational Issues

1 25,26,27 ,30,32

Phase III: (Relative Importance of the factors using Analytic Hierarchy Process)

The third phase comprised of an in-depth study of the identified factors to understand the

relative importance of the factors identified in Phase II among the target consumers,

while making the big choice of "where to avail the loan from". The factors were

presented in a paired comparison pattern and the same aforesaid set of respondents was

asked to respond based on the fundamental scale (mentioned in methodology section

-236-

3.6.2). The responses thus obtained were analyzed using the AHP software and compared

over the two regions and recorded as follows (table 4.3. III a).

Table 4.3.III a- Region I & II

Factors AHPWeights

Region I Region II

Flexibility in Interest rates and down payment 0.2803 0.2831

Flexibility in Documentation 0.135 0.0807

Transparency in Operations 0.1185 0.1987

EMI collection mechanism 0.1101 0.0768

Turn Around Time (TAT) in Service delivery 0.0777 0.0849

Default Management 0.0775 0.0749 Information dissemination and Relational Incentives 0.0738 0.0371

Flexibility in the choice of Mode of Repayment 0.0615 0.0932

Flexibility in Credit profile judgment 0.0509 0.0329

Level of Augmented Services delivered 0.0147 0.0379

Consistency Ratio: 0.0987 Consistency Ratio: 0.0893

The AHP analysis studies revealed that the relative weightage of the ten factor are

recorded in the table (4.3.III a) above for the two different regions.

The table (4.3.III a- Region I) features the AHP Analysis for the Region I (Asansol -

Burdwan Region in West Bengal). The findings reveal that the most important factor for

the choice of a Financial Institution for a Commercial Auto loan in this Region is the

Flexibility in the Negotiation of Interest rates and down payment, followed by Flexibility

in documentation, and transparency in Operations. They also vetoed for an FI which

-237-

facilitates easy and hassle-free collection ofEMI. The least important factor according to

this group of customers is the augmented services offered by the Financial Institutions

The table (4.3.III a- Region II) results depicts the AHP analysis for Region II (Dhanbad

Bokaro Region in Jharkhand) . The findings thus reveal that the most important factor

for this group as well is the Flexibility in the Negotiation of Interest rates and down

payment.

However, the second most important aspect for consideration of a Financial Institution

for a Commercial Auto loan in this Region is transparency in operations.

A closer look at the responses do highlight that the Default management mechanism of an

FI too is a decisive factor in the decision making process for both the regions. The

Default management mechanism of the Financing Institutions like pre-calling, soft

calling, and hard calling do facilitate a close continuous relationship with the customers

and help in managing the NP A levels.

From the customers' point of view, these initiatives on the part of the Financing

Institutions do help them a lot to maintain their Track Records and hence manage a better

Credit Rating for themselves in the CIBIL Database, which can help them further in the

long run to secure an enhanced standard of living.

It seems that the flexibility to negotiate on interest rates gives the consumers something

more than mere monitory benefit. It gives them an immense sense of achievement and

makes them feel very special. It has been observed that even a slightest flexibility do

wonders to the customer - service provider relationship, and it helps the consumer to

move up the ladder of loyalty becoming advocate and partners in business.

-238-

The second most important factor in Region I is flexibility in documentation which can

take the form of either submitting lesser KYC documents or getting a more extended time

period for doing so. The documents that are needed to be submitted by the customers

before the disbursals mostly include:

i) Income statements I company balance sheets I last two years' audited P IL Account

statement.

ii) Past payment track record for credibility (Statement Of Accounts)

iii) Age proof

iv) Residence Proof

v) Memorandum of articles I board resolution

vi) Partners' authorization letter or partnership deed (for partnership firm)

vii) Banks' statement

The documents which the customer need to submit after the disbursal of the loan and

procurement of the vehicle are as follows:

i) Invoice of purchase

ii) Copy of registration certificate

iii) Insurance Certificate

The customers of Region I seem to prefer financing Institutions which demand lesser

KYC document or gives an ample time to submit the same. This once again makes

them feel privileged and strengthens the consumer - service provider relationship.

And thus flexibility like negotiation in documentation contributes a lot in enhancing

the customer life cycle with the financing Institution. However, it is not the same for

Region II, where this factor is ranked as fifth in importance for the choice of a

-239-

financing Institution for availing the retail commercial auto mobile loan. In fact for

them the second more important factor is the Transparency in the Transactions.

The Transparency in the Transactions do form a major decision variable for the

choice of financing Institution for availing the retail commercial automobile loan

among the customers base of Region I as well. This particular factor addresses six

primary relational exchanges namely

1. Trust

2. Commitment

3. Co operation

4. Keeping promises

5. Shared values

6. Communication

An effective management of transparency in Transactions definitely enhance the Trust

Quotient of the consumers with the financial Institution and it also reveals from the FI' s

side how well do the keep the promises, abide by the commitment, co-operate and give

importance to their shared values. This openness in transactions and communication of

these transactions by means of regular statement of Accounts, welcome kit, Amortization

Schedule and other statements from time to time do ensure and re-inforce the inherent

mutual trust in each other, thus giving a boost to this relationship.

The next important variable for Region II customers is the "Tum-Around-Time" (TAT)

in the transactions like releasing the Disbursal Order, Issuing an SOA (statement of

accounts), PDC swapping, Pre-closure of accounts etc. 'Pace' or 'Promptness' in

transactions have been pointed out by many a scholars in prior research studies as major

-240-

decisive variable for consumer purchase decision of availing a Retail Commercial

Automobile loan. The present findings re-emphasize the fact that pace in delivery is vital

factor and often a differentiating factor which contributes to the 'BIG' choice on the

customer's side.

The next factor which holds quite an importance for Region II customers is the Flexibility

in the choice of mode of repayment .This factor includes the decisions like duration of

moratorium, the tenure, the EMI distribution over the tenure, and the repayment mode

whether through cash or Post-dated Cheques etc. The study reveals that the flexibility in

these decisions do make the consumers feel special and entirely in-charge of the situation.

The Financial Institutions have pointed out that, these flexibilities do curb the default

rates to a certain extent as the trust reposed by the Financial Institution on them enriches

the shared values, and motivates the former to keep their promises in most cases.

One of the major factors that have been pointed out as a prime decision variable by both

the Region I & II customers are the services provided by the Financial Institution in the

collection of EMI. The asset is a movable one and usually is on the wheels. Most of the

time the EMI are paid by the customers when they are on a faraway trip. Therefore, they

prefer an FI which has a country wide network and allows payment from anywhere

across the country. A desk-to-desk collection mechanism is also well applauded by them.

It has come to light from the studies that the NBFCs and the Private Banks are most

popular because of these services that they provide to their customers. From the FI' s side

as well this EMI collection mechanism does ensure a continuous relationship with the

customers and helps in managing the default rates.

- 241 -

Default management, a major aspect of the financial business is the 61h most important

factor consider for the choice of the Financial Institution for loan by the customer.

Default management includes the pre-calling before the EMI due date, soft calling in the

1st bucket (0 to 30 days) default, hard calls (30 to 60 days) default, legal notices for 90

days default, and repossession orders for 120 or more days default. There is certain

financial institution who have a very stringent mechanism and resort to even sending

local goons at only a soft bucket default. And repositions without even issuing any legal

notice. In such cases it has been found that the consumers are a bit awe-struck and

becomes highly dissatisfied. This dissatisfied spread like fire and negatively impact the

reputation of the financial institutions to the prospective customers.

The other factors namely the augmented services offer, flexibility m credit profile

judgment, information determination and relational benefit (like discount in repeat

financing, top up funding and communication of exclusive offer for cross selling and up

selling of products), rather occupied a back sit compared to the other factors. The relative

importance clearly features in table 4.3.III.a -Region I & Region II.

-242-

Chapter 4.4 (a) Performance of The Financing Institutions -

Consumers' Perceptions

This study, concentrates on the check list as to what are the CRM tools (32 identified so

far) are implemented by the market leader in each of the three type of financial

institutions namely The Public Sector Bank, The Private Banks and The Non Banking

Financial Corporations.

The consumer perceptions of the image of the Financing Institutions with respect to their

Customer Relationship Management strategies were ascertained by getting the weighted

average score (weights being ascertained as per the AHP analysis in the previous section

and multiplying them with the average score obtained from the check list, which scores

(Yes = 1 and No = 0) the two tables 4.4.a.l and 4.4.a.2 sums up the scores and help us to

compare the consumers' perceptions over the two regions.

Table 4.4.a.l and 4.4.a.2 reveals the consumers perceptions in terms of the following

Issues

A) Flexibility issues

B) Transactional issues

C) Relational issues

The flexibility issues are already identified in the previous section includes

• Flexibility in negotiation of interest rates and down payment

• Flexibility in documentation

• Flexibility in choice mode of repayment

• Flexibility in credit profile judgment of the loan applicant

-243-

Table 4.4.a.l REGION I Average Scores Wei hted Mean scores

Public Private

Public Private AHP Sector NBFC Sector NBFC

Factors Weights Banks Banks

Banks Banks

Flexibility in Interest rates and downpayment 0.2803 0.58 1.50 1.75 0.16 0.42 0.49

Flexibility in Documentation 0.135 0.92 1.08 1.33 0.12 0.15 0.18

Transparency in Operations 0.1185 4.08 4.92 4.08 0.48 0.58 0.48

EMI collection mechanism 0.1101 1.33 3.17 2.58 0.15 0.35 0.28

Tum Around Time (TAT) in Service delivery 0.0777 2.83 3.00 2.92 0.22 0.23 0.23

Default Management 0.0775 0.67 1.50 1.67 0.05 0.12 0.13

Information dissemination and Relational Incentives 0.0738 3.67 3.50 3.00 0.27 0.26 0.22

Flexibility in the choice of Mode of Repayment 0.0615 0.83 1.67 1.00 0.05 0.10 0.06

Flexibility in Credit profile judgment 0.0509 0.75 1.33 1.58 0.04 0.07 0.08

Level of Augmented Services delivered 0.0147 2.75 3.25 2.92 0.04 0.05 0.04

Consistancy Ratio: 0.098 1.5902 2.323767 2.200983

The transactional issues includes the following factors of CRM

• Transparency in operations or transaction

• Term around time in delivering of services

-244-

• Level of Augmented services delivered

The relational issues includes

• EMI collection mechanism of the FI

• Default management mechanism of the FI

• The information dissemination and relational incentives provided by the

financial institutions.

-245-

FLEXIBILITY ISSUES:

a) Flexibility in negotiation of interest rates and down payment:

The perception pattern is more or less similar over the two regions at 5% level of

significance. There is significant difference in the perceptions of the customers over

the three types of financial institutions at 5% level of significance. The Public Sector

Banks as perceived by the consumers are least flexible on this aforesaid issue. In

Region II the Private Sector Banks are consider to be most flexible and Region I it is

the NBFCs who are perceived to be more flexible.

Flexibility in negotiation of Interest rates and down payment

Public Sector Private Banks NBFC

Banks Re2I 0.16 0.42 0.49

Re21I 0.17 0.50 0.47

ANOVA: Two-Factor Without Re(!lication (MS EXCEL out put)

SUMMARY Count Sum Average Variance Region I 3 1.074483 0.358161 0.029645 Region II 3 1.1324 0.377467 0.033951

Public Sector Banks 2 0.32865 0.164325 1.33E-06 Private Banks 2 0.915875 0.457938 0.002811

NBFC 2 0.962358 0.481179 0.000175

ANOVA

Source o[ Variation ss d[ MS F

REGION 0.000559 0.000559 0.460585

TYPE OF FINANCING 0.124763 2 0.062382 51.39388 INSTITUTION

Error 0.002428 2 0.001214

Total 0.12775 5

-246-

Level of significance a = S %

F P-value critical

0.567351 18.51276

0.019086 19.00003

b) Flexibility in documentation :

The perceptions pattern over the two regions are differ significantly over the two regions

as well over the three types of financial institutions at 5% level of significance.

Public Sector Private NBFC

Banks Banks Reg I 0.12 0.15 0.18

Reg II 0.07 0.09 0.11

ANOV A: Two-Factor Without Re~lication (MS EXCEL out Level of significance o. = 5 ut o/o


Public Sector Banks 2 0.197725 0.098863 0.001239

Private Banks 2 0.233675 0.116838 0.00173

NBFC 2 0.294325 0.147163 0.002157

ANOVA Source of Variation ss df MS F P-value F crit

REGION 0.005062 1 0.005062 159.1666 0.006224 18.51276 TYPE OF FINANCING INSTITUTION 0.002384 2 0.001192 37.47661 0.02599 19.00003 Error 6.36E-05 2 3.18E-05

Total 0.007509 5

The Public Sector Banks are perceived to be least flexible and NBFCs are

perceived to be most flexible in the case of documentation. When compared

over the two regions the customers of all the three types of financial

institutions of Region I score high on the perceptions of degree of flexibility

in documentation as compared to their counter parts in Region II.

-247-

c) Flexibility in the choice of mode of repayment :


Banks Banks

Reg I 0.05 0.10 0.06

Reg II 0.08 0.16 0.10

The mean weighted average score figures in the table above depict that the

perceptual score for flexibility in the mode of repayment which includes the

negotiations of the numbers of days of moratorium and choice of PDC I Non PDC I

Security PDC mode etc. It reveals that the private players score high even on this

aspect of consumer perception irrespective the region.

However, the ANOV A results do depict that the pattern of consumer perception the

similar of the two regions. And the private players score high on consumer

perception in terms of the flexibility in the choice of mode of repayment.

ANOV A: Two-Factor Without Replication (MS EXCEL out put)


Public Sector Banks 2 0.128917 0.064458 0.000349 Private Banks 2 0.2656 0.1328 0.001836 NBFC 2 0.162467 0.081233 0.000779

ANOVA Source of Variation ss df MS F

REGION 0.002666 0.002666 17.92075 TYPE OF FINANCING INSTITUTION 0.005074 2 0.002537 17.05168 Error 0.000298 2 0.000149

Total 0.008038 5

-248-

Level of significance a =5 °/o

P-value F crit 0.051526 18.51276

0.055397 19.00003

The Public Sector Banks and the NBFCs trail in this arena and have more or

less similar consumer perception scores.

d) Flexibility in credit profile judgment of the loan applicant :

Public Sector Private Banks NBFC Banks

Re2I 0.04 0.07 0.08 Reg II 0.02 0.05 0.05

ANOV A: Two-Factor Without Renlication (MS EXCEL out put) Level of significance a = 5 %


Public Sector Banks 2 0.06285 0.031425 9.11E-05

Private Banks 2 0.114475 0.057238 0.000226

NBFC 2 0.132683 0.066342 0.000406

ANOVA Source of Variation ss df MS F P-va/ue F crit REGION 0.000667 1 0.000667 23.70391 0.039692 18.51276

TYPE OF FINANCING INSTITUTION 0.001312 2 0.000656 23.31931 0.04112 19.00003 Error 5.63E-05 2 2.81 E-05

Total 0.002035 5

The consumers' perceptions scores in the terms of the flexibility in credit profile

judgment suggest that Private Banks and NBFCs has a similar consumer

perceptions and a consider to be more flexible in credit profile judgment in the both

regions than there counter parts enrolled with the Public Sector Banks.

-249-

However, when compared over the two regwns it further reveals that these

financing institutions' consumer perceptual scores are higher in Region I than in

Region II. The region may be that most of these financial institutions have started

this business in Region I earlier than Region II and therefore has a wider customer

based in Region I than in Region II. As a result, the credit profile parameter for

existing customers or referred customers like - mandatory field investigations, field

officers visits, profile devastations etc are more flexible issues.

Further, Raniganj and Asansol Regions being a major hub of transport business

attracts more retail players and they get introduced to this business through the

already established strategic clients and hence the credit profile judgment parameter

are more flexible for them.

TRANSACTIONAL ISSUES

e) Transparency in operations I Transaction :

The figures in table reveal that the Private Banks over the two regions are perceived to

have more transparency in there transactions.

Reg I

Reg II

Public Sector Banks

0.48

0.81

Private Banks

0.58

0.98

Anova: Two-Factor Without Replication

SUMMARY Count Sum

Region I 3 1.550375

Region II 3 2.68245

Public Sector Banks 2 1.295233

Private Banks 2 1.559567

NBFC 2 1.378025

NBFC

0.48

0.89

Average 0.516792

0.89415

0.647617

0.779783

0.689013

-250-

Level of Significance a=5%

Variance 0.003251

0.006854

0.053623

0.077743

0.084163

ANOVA Source of Variation ss df MS F P-va/ue F crit REGION 0.213599 0.213599 221.426 0.004486 18.51276

TYPE OF FINANCING INSTITUTION 0.018281 2 0.00914 9.475261 0.095463 19.00003

Error 0.001929 2 0.000965

Total 0.233809 5

It may be because of the fact that The Private Banks like ICICI Banks and HDFC

Banks do religiously make an afford to deliver an Amortization Schedule with the

welcome kit. Further, they have to make arrangement by which a customers are even

able to checkout their statement account at any point of time during there tenure.

Further, HDFC is one of the initiators in nurturing the concept of CIBIL data base,

where an enroll customers can check out his or her accounts (loan repayment account)

at any point of time, on line. In fact, HDFC and ICICI are both share holders ofC IB1L

and they share data bases of their transactions with their customers and other players in

the retail loans segments.

Further, these banks arrange for customers meets on regular basis and look forward to

their valuable suggestions for Re-engineering the product and services offer. These

initiatives have definitely made a mark on the customers which are evident from the

consumers perception scores.

An interesting fact get divulged from the figures and the ANOV A results that there is

the significant difference in the consumers perceptions when it comes to transparency

in transactions over the two regions at 5 % level of significant. Thus, we can decipher

that in general the consumers' scores for Region II are higher than those of Region I.

- 251 -

f) Turn Around Time (TAT) or promptness in service delivery :

The figures on the tables and the ANNOY A results revealed that there is no significant

difference in the consumers perceptions over the three types of financial institutions

under the head of term around time in delivering services or promptness in delivering

the services like disbursal order sanction, Statement of account release, No Objection

Certificate (NOC) release, post dated cheques (PDC) swaping or for closures an

account or any sort of grievance handling.


Banks Banks

Reg I 0.22 0.23 0.23 Reg II 0.24 0.25 0.25


SUMMARY Count Sum Average Variance Region I 3 0.679875 0.226625 4.19E-05 Region II 3 0.74995 0.249983 6.67E-05

Public Sector Banks 2 0.4607 0.23035 0.000208 Private Banks 2 0.4878 0.2439 0.000233

NBFC 2 0.481325 0.240663 0.000394

ANOVA Source of Variation ss df MS F P-value F crit REGION 0.000818 1 0.000818 96.02905 0.010254 18.51276

TYPE OF FINANCING INSTITUTION 0.0002 2 0.0001 11.75038 0.078429 19.00003 Error 1.7E-05 2 8.52E-06

Total 0.001036 5

However, there is an interesting revelation in the consumer perception over the two

regions and the Region II people score higher on this aspect over their Region I counter

parts. It may be that a smaller target audience and business volume in Region II,

-252-

actually it makes it possible for a faster and prompter service delivety. Further, it can

also be said that since the financing institutions are just tasting the waters in Region II,

they are more aggressive in increasing there business volume, as a result they are more

proactive in delivering services in Region II.

g) Augmented services delivered :

It is a normal practice among the financial institutions that, they give, extra customized

services like - collection of documents, shining of the agreement at the customers door

steps, getting insurance and renewal of insurance done and getting the registration of

vehicle done, so as to gain a competitive edge in the market.

The consumers' perception scores reveal that the efforts are perceived to be similar

irrespective of the type of financial institutions over the two regions at 5% level of

significance. In fact, all of the three types of FI in a race to cut the clutter and gain the

competitive edge make similar efforts I offers to there customers.

Reg I

Reg II

Public Sector Banks

0.04 0.10

Private NBFC Banks

0.05 0.04 0.13 0.13


SUMMARY Count Sum Average Region I 3 0.131075 0.043692 Region II 3 0.36225 0.12075

Public Sector Banks 2 0.144375 0.072188 Private Banks 2 0.176925 0.088463 NBFC 2 0.172025 0.086013

-253-

Variance 1.4E-05

0.000212

0.002018 0.003311 0.003722


REGION 0.008907 1 0.008907 124.2553 0.007952 18.51276 TYPE OF FINANCING INSTITUTION 0.000308 2 0.000154 2.148391 0.317623 19.00003 Error 0.000143 2 7.17E-05

Total 0.009358 5

However, there is a substantial difference in the endeavors of the financial institutions

over the two regions. The consumers in Region II have a higher perceptual scores

indicating increased efforts by all types of Financing Institution in there region. It may

be again as a result of the ever growing business, and high competitions in this

unexplored yet lucrative market the gives way to this higher levels of efforts

RELATIONAL ISSUES

h) EMI collection mechanism:

The EMI collection mechanism is yet another decisive variable for the 'Big choice' of

the consumer CIBIL loan availing process.

Reg I

Reg II

Public Sector Banks

0.15 0.10

Private NBFC

Banks

0.35 0.28 0.27 0.20


SUMMARY Count Sum Average Region I 3 0.779875 0.259958 Region II 3 0.5696 0.189867

Public Sector Banks 2 0.2492 0.1246 Private Banks 2 0.61745 0.308725

NBFC 2 0.482825 0.241413

Variance 0.010635 0.006977

0.000986 0.003188

0.0037

-254-

ANOVA Source of Variation ss df MS F P~value F crit

REGION 0.007369 1 0.007369 29.20955 0.032572 18.51276 TYPE OF FINANCING INSTITUTION 0.034719 2 0.017359 68.8074 0.014325 19.00003 Error 0.000505 2 0.000252

Total 0.042593 5

The results bring to light a few interesting facts. The perception scores of the

consumers about the EMI collection mechanism for the Private Sector Banks are the

highest over both the regions. The Private Sector Banks have a multi~faceted EMI

collection mechanism like desk - to - desk collection, on-line collection and even other

ways. Close behind are the NBFCs. The Public Sector Banks ranks the last in the

perceptions of the customers.

Further, a region wise comparison of the consumers' perception score reveals that the

EMI collection mechanism is perceived in Region I to be more intense than their

counter parts in Region II.

i) Default management mechanism :

Managing default rates and effectively ensuring lower NP A levels is one of the major

challenges for the financial institutions laundering loans. As a result several proactive

measures are taken up by these financial institutions. These measures can take the

following forms:

• Pre calling two days prior to the EMI due date

-255-

• Thank you call for an on time payment of EMI

• A reminder soft call for one EMI (0 to 30 days) default

• Hard call for 30 to 60 days default

• Party visit on 60 to 90 days default

• Legal notice for 90 + days default

• Repossession of assets for 120 days or more days of default.

The perception score of the existing customers service reveal that there is substantial

difference irrespective of the regions in the efforts of The Public Sector Banks with

those of the Private Banks and NBFCs at 5 % of significance.

Public Sector Private Banks

Reg I

Reg II

Banks

0.05

0.05

0.12

0.11


SUMMARY Count Sum Region I 3 0.297083

Region II 3 0.293358

Public Sector Banks 2 0.1016

Private Banks 2 0.2286

NBFC 2 0.260242

ANOVA

Source of Variation ss df

REGION 2.31 E-

06 1 TYPE OF FINANCING INSTITUTION 0.00705 2

8.62E-Error 06 2

Total 0.00706 5

NBFC

0.13

0.13

Average Variance 0.099028 0.001724

0.097786 0.001805

0.0508 1.5E-06 0.1143 7.6E-06

0.130121 1.82E-06

MS F

2.31E-06 0.536848

0.003525 818.2431

4.31E-06

-256-

P-value F crit

0.539978 18.51276

0.001221 19.00003

The Private players (Private Banks) seem to be more sophisticated and proactive in

managing default. Rather, it can be said that they start the process right from the credit

appraisal. And they maintain a continuous relationship through their tele-callers

ensuring lower level of defaults. Further, they Delay Payment Charges (DPC) are quite

high and irrevocable. As a result, the Private Banks are better at default management.

However, the NBFCs are more reactive in their approach and are believed to be very

strong at the higher buckets and usually rely on local goons. Thus, curbing the NP A

levels. Some of the NBFCs have even started to implement the Private Banks practices

in the lower buckets.

The Public Sector Banks are rather inert in the lower buckets and there yet to take up a

pro active roll. There reactive only in the cases of high default.

j) Information dissemination and relational incentive :

This business of retail commercial vehicle loan has thrived through the last decade in

the aforesaid regions through pure and effective relationship management. The

relationship between the customer and the financial institutions were valued

possessions and marked with transparency, trust, open communication and commitment

towards shares values. Both the parties mutually benefited from the relations. While, on

the Financing Institution's part it was an effort to provide the customer with a homely

atmosphere, efficient grievance handling, time to time up-dation of the new offers, and

giving special incentives to those who have graduated from being loyal customer to

advocates and partners in business in the form of top-up funding, repeat funding

concessions, brokerages for getting new customers, etc.

-257-

On the customers' side the onus of the relationship was responsible to look after the on

time payment ofEMI, getting more leads or getting new accounts for themselves.


Banks Banks

Reg I 0.27 0.26 0.22

Reg II 0.14 0.14 0.12


SUMMARY Count Sum Average Variance Region I 3 0.7503 0.2501 0.000656 Region II 3 0.398825 0.132942 6.69E-05

Public Sector Banks 2 0.406633 0.203317 0.009054 Private Banks 2 0.397425 0.198713 0.007101

NBFC 2 0.345067 0.172533 0.004776


REGION 0.020589 1 0.020589 120.3254 0.008209 18.51276 TYPE OF FINANCING INSTITUTION 0.001103 2 0.000551 3.222376 0.236833 19.00003 Error 0.000342 2 0.000171

Total 0.022034 5

It has been revealed from the customers' perception score that the approaches in this

regard these days, as perceived by the consumers, are similar in all three types of

financial institution at 5% level of significance. It means every one of them are

comfortable with there own service providers. But an interesting fact lies in the fact that

the consumers in the Region I has a higher perceptual score than those of the Region II.

It may be so that the account of the Region II are still young and fresh and are yet to

benefit from the long term relation. On the face it seems that the Banks (The Private

and Public Sector) are better at their efforts than their NBFC counter parts.

-258-

k) Over all:

On the over all perception rating it can thus be concludes that there is significance

difference of the consumers perceptions over the regions as well as types of Financing

Institutions at 5% level of significance.

Reg I

Reg II

Public Sector Banks

1.59

1.79

Private Banks

2.32 2.67


SUMMARY Count Sum Region I 3 6.11495 Region II 3 6.929667

Public Sector Banks 2 3.375883 Private Banks 2 4.997392

NBFC 2 4.671342

ANOVA

Source of Variation ss df REGION 0.110627 1 TYPE OF FINANCING INSTITUTION 0.735635 2 Error 0.005962 2

Total 0.852224 5

NBFC

2.20

2.47

Averag_e Variance 2.038317 0.154375 2.309889 0.216423

1.687942 0.019107 2.498696 0.0612

2.335671 0.036281

MS F P-value F crit 0.110627 37.11369 0.025902 18.51276

0.367818 123.397 0.008039 19.00003 0.002981

And in both regions the most preferred service provider are the Private Banks which are

very rightly revealed by the Markov Analysis studies of forecasting in chapter 4.2. The

preference rankings are therefore as follows:

• Private Banks

• NBFCs

• Public Sector Banks.

-259-

Chapter 4.4 (b) Performance of the Financin2 Institutions - Channel

Partners' Perceptions

The Channel partners namely the dealer point officials, DSAs (Direct sales agent), brokers

and ISDs (In shop demonstrators) form a major link between the financing institutions and its

customers. They form major influencing factors in the loan decision process of a retail

commercials automobile loan. Therefore they are a major source of information for the

current research. Their perceptions about the performance of the financing institution in the

field of CRM and the customers' expectations form a major input in the current research for

drawing up pragmatic and effective CRM strategies. A thorough study of the perception of

the channel partners was taken up by a sample survey based on structured questionnaire.

Following are the finding and analysis of the survey.

Findings and Analysis

4.4.1 Annual turn over :

The channel partners include namely: the Dealers (lSD +dealer point officials), DSAs

and the brokers.

FOR DEALERS ((lSD +dealer point officials)

Annual turn over in Crores of

Rs. Region I (N=30) Region II (N=30)

3-5 crores 18 (60%) 24 (80%)

5-7 crores 12 (40%) 6 (20%)

Table 4.4.1.a

FORDSAs Annual turn over in Crores of


1-3 crores 6 (100%) 6 (100%)

Table 4.4.1.b

-260-

FOR Brokers Table 4.4.l.c

Annual turn over in Crores of


Less than 1 crore 5 (55.56%) 6 (66.67%)

1-3 crores 4 (44.44 %) 3 (33.33 %)

The average range of Annual Turnover for the dealers is 3 - 5 Cr. (modal class), for DSAs

the average range of Annual Turnover is 1-3 crores, and for the brokers, it has been found

that mostly the annual tum over of both the regions range in the class less than 1 crores. Thus

it can be concluded that these channel partners differ on this particular parameter irrespective

of the regions.

4.4.2. Average number of vehicles sold

The mean sales of vehicles in number of units of the three different types of channel partners

suggest that the dealers have the highest number of vehicles as sales in a particular year. The

results are tabulated below: Table 4.4.2.a

Type of channel partners Region I Region II

Dealer (ISD + dealer point officials) 144 130

DSA 101 97

Broker 15 13

The mean sales in number of units sold, when statistically tested over the two region reveal

that there is no substantial difference in the two regions at 5% level of significance.

However, the average sales in number of units sold do differ significantly over the type of

channel partner at 5% level of significance, as is evident from the row wise calculated F as is

evident from the ANOV A table 4.1.2.b below.

In fact this particular factor forms one of the bases to distinguish between the three type of

channel partners. The dealers have the highest average sales followed by the DSAs and the

-261-

Table 4.4.2.b

ANOV A: Two-Factor Without Replication I (level of significance a = 0.05}

SUMMARY Count Sum Average Variance Dealers 2 274 137 98

DSAs 2 198 99 8

Brokers 2 28 14 2

Region1 3 260 86.66667 4314.333

Region 2 3 240 80 3639

ANOVA

Source of Variation ss df MS F P-value F crit Rows 15865.33 2 7932.667 383.8387 0.002598 19.00003

Columns 66.66667 1 66.66667 3.225806 0.214326 18.51276

Error 41.33333 2 20.66667

Total 15973.33 5

Brokers respectively. Both the Dealers and DSAs are full blown firms who act as mediating

personnel in influencing the customer for the choice of Financing Institution for the purpose

of availing a retail commercial automobile loan irrespective of the region.

4.4.3. Trend of mode of purchase of CV (commercial vehicle) from the dealer points:

The sales figure from the 5 dealers point in each region was collected and analysis for

determining the most preferred mode of financial transaction of the retail customer of

commercial automobiles, during purchase, in the two regions.

The region I and II figures are depicted in the chart below (Chart 4.1.3.a & b) It comes to

light that over the last 5 years that is from financial year 2005 - 06 to FY 2009 - 10 there has

been a steady decrease in the 'complete cash' more and ' finance from public sector banks'

mode of purchase ofCVs from the dealer points. The dip has been quite steep from 13.038%

to 3.101% in region 1 and from 17.42% to 3.87% in region 2 over the 5 years for the

complete cash mode.

-262-

REGION I

Year wise percentage sales in each mode

50.000

40.000

?: ========= pe rce nta ge of 30.000 -

total sales 20.000 -

10.000 .

0 .000 2005 2006 2007 2008

_._Cash 13.038 10.084 7 .130 4 .176

.....,.__ Finance PVT Bank 27.975 35.045 40.515 45.786

- Finance Nat Bank 26.646 25.023 21.494 20.778

....._ Finance NBFC 32.558 30.225 30.888 29.510

Year

Source: Region I dealer point survey Table 4. 1.3.a

REGION II

Year wise percentage sales in each mode 60.000

percentage of total sales

50.000

40.000

30.000 -

20.000 .

10.000

0 .000 -------~ 2005 2006

_._Cash 17.419 9 .707

• 2007 2008

7.035 4 .063

33.045 38.515 45.786

26.023 21.494 1

........_ Finance _FV_T_ B_an_k __ 2_6_.6_1_3 ____________ _

~- Finance Nat Bank 32.419 20.778

1--+- Finance 1\SFC 23.871 31 .225 32.898 29.443

Year Source: Region II dealer point survey

Table 4.1 .3 .. b

~ 2009

3 .101

47.608

18.152

31 .203

• 2009

3 .871

52.000

18.516

25.613

The finance from public sector banks mode saw a relatively less steeper dip from 26.6% to

18.15% in region I and from 32.42% to 18.52% in region II over the 5 years. The preference

of finance from NBFCs have been more over less steady over the last 5 years ranging around

30% in both the regions I and II. However, there has been a sudden decline in the NBFC

preference, along with the over all sales figures during the 2008 and 2009 - recession phase.

Yet the compositions of the mode of financial transaction during purchase of CV at the dealer

point have maintained a more or less similar pattern.

The Private Banks however witnessed and upward trend through out in both the Regions I

and II. There has been a steep increasing trend from 27.98% to 47.61% in Region I and

26.61% to 52% in Region II. According to the channel partners' views the Private Banks'

growth trend have remained unaffected even through the recession phase and the credit goes

to the superior CRM strategies deployed by the Private Banks in both the regions.

4.4.4. Factor affecting the choice of financing institution for tie-ups :

An in depth exploratory study of the marketing personnel of the financing institutions and the

channel partners highlighted the following factors hold p1ime importance for the choice of

financing institution for tie-ups among the three different categories of channel partners

namely the dealers, DSAs and the brokers. The factors are listed below:

i) Tum around Time {TAT) in disbursal order sanction - depicting the promptness and

responsiveness of the financing institution in the transactions.

ii) Flexibility allowed in documentations - in terms of the time and number.

iii) Flexibility in credit profile judgment.

iv) Flexibility in terms and conditions in the choice of mode of repayment for the

consumers.

v) Promptness in disbursal in commission.

vi) Commission amount.

vii) Post delivery servicing.

viii) Relationship with the marketing executive of the financing institutions.

-264-

ix) Brand value.

The in depth exploratory study brought to light an interesting fact that, for a product like a

retail commercial automobile loan, the 'interactive marketing' is the final form of marketing.

The literature review has already established that, to make the interactive marketing effective,

the company should strengthen its internal marketing. In the CRM terminology the

employees the channel partners are consider to be the 'internal customers' of any marketing

firm. And for successful marketing of a high involvement product like retail commercial

automobile loan, a continuous two - fold CRM approach is mandatory. Firstly, with the

internal customers and secondly, with the external customers.

Therefore, for the satisfaction for the external customers' needs the internal customers' needs

~ ... •:)

are required to be assessed and fulfilled. That is why the research makes an attempt to

understand the factors of importance for the channel partners, for the choice of financing

institution for tie-up for generating business.

A) A statistical comparison over the three classes of channel partners using Kruskal-

Wallis test reveal that there is significant difference in the relative importance of each of the

factors amongst the three classes at 5% level of significance.

-265-

Table 4.4.4 .A Kruskai-Wallis Test for identifying the factors important factors responsible for the choice of Financing Institutions f,[)r tie-ups

Ranks

STATUS N Mean Rank

TAT in D.O sanction Dealer 61 56.39 Brnker 18 24.39 D8A 11 19.68 Total 90

Strictness in Dealer 61 52.82 Documentation

Broker 18 44.33 DSA 11 6.82 Total 90

Strictness in Profile Dea1ler 61 48.21 judgement

Broker 18 56.56 DSA 11 12.36 To1tal 90

Strictness in Terms & Dealer 61 44.41 Conditions of repayment

Broker 18 67.94 DSA 11 14.82 Total 90

Commission disbursal Dealer 61 42.58 promptness

Brol<er 18 36.08 DSA 11 77.09 Total 90

Commission amount Dealer 61 44.82 Broker 18 23.67

DSA 11 85.00 Total 90

Post delivery servicing Deaner 61 38.31 Broker 18 68.94 DSA 11 47.00 Total 90

Relationship with the Dealer 61 36.50 Marketing Exec of the FI

Broker 18 51.97 DSA 11 84.82 Total 90

Brand value Dealer 61 41.66 Broker 17 39.53 DSA 11 . 72.00 Total 89

-266-

Table 4.4.4 .B STATISTICAL ANALYSIS

Test Statistics

Strictness Strictness

Commissio Relationshi

TAT in in

Strictness 'n Terms & n disbursal Commissio

Post p with the Brand

D.O Documenta

in Profile Conditions promptnes n amount

delivery Marketing value

sanction judgement of servicing Exec of the tion

repayment s

FI

Chi-Square 35.887 30.546 23.040 33.930 20.827 42.756 21.033 68.231 15.107

df 2 2 2 2 2 2 2 2 2

Asymp. .000 .000 .000 .000 .000 .000 .000 .000 .001 Sig.

a Kruskal Wall1s Test b Grouping Variable: STATUS

It is found that

• Turn around Time(T AT) in disbursal order sanction, flexibility in documentation are

the two least importance factor for the dealers. For them the most importance factor is

the relationship of the marketing executive of the financial institution.

• For DSAs Tum around Time(TAT) in disbursal order sanction, flexibility in

documentation flexibility in credit profile judgment flexibility in terms and conditions

and post delivering servicing are important for their tie-ups.

• For the brokers however the commission amount and the commission disbursal

promptness and brand value are the most important points of consideration for the

choice of financing institution for a tie-up at 5% of significance.

B) A statistical comparison using the Mann-Whitney Test, considering all classes of

channel partners reveal that there is significant difference of the opinion over the two

regions in all the factors except commission disbursal promptness and relationship

with the marketing executive of the financing institution. Both these factors are

considered to be equally important by the channel partners over the two regions at 5%

of significance.

-267-

Table 4.4.4 .c Mann-Whitney Test

Ranks

REGION N Mean Rank Sum of Ranks

TAT in D.O sanction 1.00 45 35.91 1616.00

2.00 45 55.09 2479.00

Total 90 Flexibility in

1.00 45 57.18 2573.00 Documentation

2.00 45 33.82 1522.00

Total 90 Flexibility in Profile

1.00 45 61.93 2787.00 judgement

2.00 45 29.07 1308.00

Total 90 Flexibility in Terms

& Conditions of 1.00 45 55.51 2498.00 repayment

2.00 45 35.49 1597.00

Total 90 Commission

1.00 45 47.69 2146.00 disbursal promptness

2.00 45 43.31 1949.00

Total 90

Commission amount 1.00 45 37.78 1700.00

2.00 45 53.22 2395.00

Total 90 Post delivery

1.00 45 53.03 2386.50 servicing

2.00 45 37.97 1708.50

Total 90 Relationship with the

Marketing Exec of 1.00 45 42.66 1919.50 the FI

2.00 45 48.34 2175.50 Total 90

Brand value 1.00 45 31.78 1430.00 2.00 45 59.22 2665.00

Total 90

Apart from the relationship aspect with the financing institutions' marketing executive

and the commission disbursal promptness the channel partners region I usually place

more importance on the TAT in D.O. sanction the commission amount and the brand

value. For the region II the factors like flexibility in documentation, flexibility in

-268-

Table 4.4.4 .0 STATISTICAL ANALYSIS

Test Statistics

Strictness Strictness Relationship

TAT in in

Strictness 'n Terms & Commission Commissi Post with the Brand

D.O Documenta

in Profile Conditions disbursal on delivery Marketing value

sanction judgment of promptness amount servicing Exec of the tion

reJ!llY_ment FI Mann-

581.000 487.000 273.000 562.000 914.000 665.000 673.500 884.500 395.000 Whitney U Wilcoxon

1616.000 1522.000 1308.000 1597.000 1949.000 1700.000 1708.500 1919.500 1430.00 w z -3.626 -4.357 -6:166 -3.962 -.828 -2.984 -2.867 -1.479 -5.206

Asymp. Sig. (2- .000 .000 .000 .000 .408 .003 .004 .139 .000 tailed)

a. Grouping Variable: REGION

Table 4.4.4 .E STATISTICAL ANALYSIS (Kolmogorov-Smirnov Z)

Test Statistics Strictness in Relationship

TAT in Strictness in Strictness in Terms& Commission Commission

Post with the Brand D.O Documentati Profile Conditions disbursal

amount delivery Marketing

value sanction on judgement of promptness servicing Exec ofthe

r~ment Fl Most

Extreme Absolute .556 .667 .689 .578 .156 .422 .556 .133 .644 Differences

Positive .556 .000 .022 .111 .044 .422 .156 .133 .644

Negative -.111 -.667 -.689 -.578 -.156 -.089 -.556 .000 -.022

Kolmogorov 2.635 3.162 3.268 2.741 .738 2.003 2.635 .632 3.057 -Smirnov Z

!Asymp. Sig. .000 .000 .000 .000 .648 .001 .000 .819 .000 (2-tailed)

a Group1ng Vanable: REGION

credit profile judgment, flexibility in tenns and conditions and post delivering

servicing hold a relatively greater importance at 5% level of significance,

C) The ranking of the factors obtained by the sum of ranks reveal that relationship of the

marketing executive of the financial institutions is the most important factor over the

both regions for all classes of channel partners. Thus relationship marketing and

continuous Customer Relationship Management (CRM) strategies of the financing

institution should be designed in such a way that it not only gives pecuniary benefits

but also relation exchanges like mutual trust, commitment, cooperation, shared values,

keeping of promises and above all a continuous communication. As suggested by the

-269-

literature review HCRM (CRM with a human touch) rather thane CRM (Electronic

CRM) is most effective in this case.

4.4.5. Channel partners' perception of Consumers' perception:

In the literature review section the discussion on the different types of marketing

prevalent in the service in the industries establish the fact that for a high involvement

product like retail commercial automobile loans interaction between the channel

partners and the customers is the most vital moment of truth in service delivery. A

correct perception of the factor importance for the consumer purchase decision is very

much required by the channel partners for an effective communication in the

interactive marketing retail automobile loan.

An ordinal scale was design to determine the relative importance of each of the factor

have in the customers perception, according to the channel perception.

A. The over all rating suggest that the most importance factor is the flexibility interest

rate and down payment, followed by the flexibility in documentation, transparency in

the operations, turn around time in delivering services and so on.

The least importance is led on the factor flexibility in credit on judgment of the Fl.

The channel partners feel that the customers are actually less bother about the

flexibility provided by the financial institutions in credit profile judgment issue and a

lesser emphasis on this particular CRM tool may not affect the customers'

perceptions'.

-270-

Table 4.4.5 A CHANNEL PARTNERS' PERCEPTION OF CONSUMER PERCEPTION

Factors N Mean Std. Deviation

!Flexibility in Interest rates and down payment 90 1.0889 .2862

!Flexibility in documentation 90 2.0444 .4719

!Flexibility in Credit profile judgment 90 7.9000 1.3328

!Flexibility in choice of mode of repayment 90 9.1667 1.3512

TAT in services 90 3.8556 .3535

!Transparency in Services 90 3.0111 .5299

~ugmented Services Rendered 90 8.9333 .2508

EMI Collection 90 5.2000 .7525

!Default management 90 6.2889 .7070

!Relational incentives and Info dissemination 90 7.5111 1.0412

Table 4.4.5 B M ann- 1 ney es Wh't T t

Factors REGION I N I Mean

I Sum of

Rank Ranks 1 45 41.50 1867.50

Flexibility in Interest rates and down payment 2 45 49.50 2227.50 Total 90

1 45 48.97 2203.50

!Flexibility in documentation 2 45 42.03 1891.50 Total 90

1 45 38.60 1737.00

Flexibility in Credit profile judgment 2 45 52.40 2358.00 Total 90

1 45 54.00 2430.00

Flexibility in choice of mode of repayment 2 45 37.00 1665.00 Total 90

1 45 51.00 2295.00

tf AT in services 2 45 40.00 1800.00 Total 90

1 45 40.73 1833.00

rrransparency in Services 2 45 50.27 2262.00 Total 90

1 45 48.50 2182.50

!Augmented Services Rendered 2 45 42.50 1912.50 Total 90

I 45 42.50 1912.50

EMI Collection 2 45 48.50 2182.50 Total 90

1 45 45.00 2025.00

Default management 2 45 46.00 2070.00 Total 90

1 45 45.07 2028.00

Relational incentives and Info dissemination 2 45 45.93 2067.00 Total 90

-271-

B. A comparison of factors over the two regions, using the Mann-Whitney test and

Kolmogorov-Smirnov Z test, suggest that the perception of the channel partners about

the consumer perceptions are similar on a majority of factors at 5% level of

significance.

The perceptions differ significantly over the regions for the following factors at 5 %

level of significance.

i) Flexibility in credit profile judgment

ii) Flexibility in choice of mode of repayment

iii) Augmented services rendered

iv) EMI collection mechanism.

While the factors flexibility of the choice of repayment and the Augmented services

are felt to be important for the customer base of region I by the respective channel

partners, the factors flexibility in credit profile judgment and the strength in

mechanism are perceived to be more important for the region II people than their

region I counter parts.

Thus, according to the channel partners the CRM tools deployed like giving flexibility

or providing augmented services should be emphasized more in the respective regions

which hold it more important and less emphasized in the region where it is considered

less important.

4.4.6. A perception of financial institutions performance on the identified CRM

factors.

A. The general perception analysis and the Kruskal-Wallis test there after suggest

there is significant difference in the perception of the performance and deliverance

of the services of each type of financing institutions to the customers at 5% level

-272-

of significance. According to the perception channel of partners the NBFCs score

high on factors related to flexibility issue, the tum around Time (TAT) in

disbursal sanction order, collection mechanism and default management and

continuous relationship management and communication.

The Private Banks score: high on post delivery servicing, flexibility in

documentation and flexibility in terms and conditions and transparency issue and

efficient service delivery like PDC swapping and hassle-free NOC release. The

public sector bank are yet to leave to a mark and lie far behind the private players

(Private Banks and NBFCs).

Thus it can be concluded that, according to the perception of the channel

partners the private players are more preferred than the public sector banks by the

customers.

Table 4.4.6.A Kruskai-Wallis Test

Ranks

FI TYPE N Mean Rank

TAT in D.O Sanction Public Sector Bank 25 21.88

Private Bank 29 47.41

NBFC 36 60.36

Total 90

Flexibility in Interest Public Sector Bank 25 20.74

Rates and down payment


NBFC 36 55.07

Total 90

Flexibility in Public Sector Bank 25 19.48

Documentation


NBFC 36 55.47

Total 90

-273-

Flexibility in Profile Public Sec:tor Bank 25 20.54

.iudgment


NBFC 36 56.96

Total 90

Strictness in Terms & Public Sector Bank 25 21.06 Conditions


NBFC 36 54.04

Total 90

Post Delivery Servicing Public Sector Bank 25 26.42


NBFC 36 46.11

Total 90

PDC Banking Public Sector Bank 25 33.52


NBFC 36 34.78

Total 90

Disbursal of papers/ Public Sector Bank 25 25.54 transarency


NBFC 36 43.64 I

Total 90

Collection Mechanism Public Sector Bank 25 18.80


NBFC 36 57.56

Total 90

PDC Swapping Public Sector Bank 25 34.16


NBFC 36 40.32

Total 90

NOC Release Public Sec~m Bank 25 26.90


NBFC 36 47.58

-274-

Total

CRM Public Sector Bank

Private Bank

NBFC

Total

Table 4.4.6.B STATISTICAL ANALYSIS Test Statistics

Flexibility

TATinD.O ~n Interesj

J1lexibility in Rates and

Sanction down

Documentation

payment

Chi-Square 33.192 33.165 38.296

df 2 2 2

Asymp. .000 .000 .000

Sig.

Disbursal of Collection PDC

papers/ Mechanism Swapping

transparency

Chi-Square 32.060 38.869 18.346

df 2 2 2

Asymp. Sig. .000 .000 .000

a Kruskal Wallis Test b Grouping Variable: Fl_ TYPE

90

25 19.26

29 52.66

36 57.96

90

Flexibility Flexibility in Post PDC

in Profile Terms& Delivery judgment Conditions Servicing

Banking

38.785 32.213 24.786 36.266

2 2 2 2

.000 .000 .000 .000

NOC Release CRM

21.850 41.040

2 2

.000 .000

B. A region wtse analysis usmg the Mann-Whitney test and Kolmogorov-

Smirnov Z test, of the ,:;hannel partners' perceptions of the financing institution's

performance suggest that the CRM tools deployed over the two regions by the

various Financing Institutions are more or less similar at 5% significance.

A significance difference is detected only in the factors - flexibility in terms and

conditions and NOC release, wherein both these factors has a better score in region

II than in region I. These once again suggest that in the region II the terms and

conditions regarding the repayment are more flexible for all the type of Financing

-275-

Institutions. Further, it also suggest that the NOCs release process is much faster

and efficient in the Region II for all the types of FI s. It may be so that the players

have just started to taste the waters in the given segment in region II and hence, they

are very proactive to generate and sustain leads.

-276-

Chapter 4.5- GAP ANALYSIS

Customer satisfaction is the prime point of focus for Customer Relationship Management

(CRM) aka marketing in gen,;:ral. This customer satisfaction is adjudged by comparing

the customer expectation with the customer perceptions of the service delivered.

Parasurmanan et. al. (1985) in there much acclaimed work has suggested that there are

five dimension of service quality which is of importance for the customer satisfaction.

They are

i) Reliability

ii) Responsiveness

iii) Assurance

iv) Empathy

v) Tangible

These dimension should be properly understood and assed by the marketers. In the case

of the retail automobile loan segment and the current research these five dimensions

could be translated into ten factors and subsequently three primarily issue already

identified in our previous sections (Chapter 4.3 and 4.4 (a)). These issues are:

i) Flexibility issue

ii) Transaction issue

iii) Relational issue

The Flexibility Issues take care of the reliability, empathy, and assurance dimensions of

service quality.

-277-

The Transaction Issues take care of the responsiveness reliability empathy and tangible

dimension.

The Relational Issues incorporate all the five dimensions namely :Reliability,

Responsiveness, Empathy, Tangiblt~ and Assurance.

The current research makes an attempt to analysis the gaps suggested by Parasuraman et.

al. namely:

• Gap I- Market Research gap between customers expectation and management's

perceptions of customers' expectations.

• Gap II - Design Gap between service quality specification and management

perception of customer expectations.

• Gap III - Conformance Gap is the gap between service delivery and service

quality specification.

• Gap IV - Communication Gap between service delivery and promises made by

the executives.

• Gap V- Consumer Gap o:r Customer Satisfaction Gap between the consumers'

perceptions of services delivered and the consumers' expectations.

All these gaps are assessed over the three key CRM issues already identified in the

research as flexibility issues, transactional issues and relational issues.

A questionnaire comprising of five sets of 32 statements each incorporating the three

above issues and the under lying 1 0 factors of CRM had been framed and presented

to the marketing executive or relationship manager of the financing institutions. This

questionnaire were filled up with the in-depth interviews and responses from the

marketing executives of the Financing Institutions and the panel of six ETR I GTR

-278-

customers of each of the customers Financing Institutions to gauge the following

parameters :

i) Customers' expectations

ii) Management's perception of customers expectations

iv) Service quality specification

v) Service delivery specification

vi) The level of promises make to the customers

vii) The consumers perception of service delivered

The values of these variables were scrutinized to adjudge the five gaps mentioned

above. The gaps so identified were compared and analysed using the Kruskal Wallis

test over the different types of financing institutions across the two regions. The

weighted average scores thus. obtained are tabulated below and are probed over the

two regions across the different type of financing Institution for the service gaps I, II,

III, IV, V.

§4.5.1 Gap - I : Market Research Gap

Market Research Gap is g[ven by (Consumers' expectation - Management's

perception of consumer expectations )

The average market research gap for all the group of financing Institution across all

the three CRM Issues suggested negative score, as is evident from the table 4.5.l.a

below. It means the management perception of customer expectations is higher then

the actual customer expectations. The gaps are the least for the NBFC followed by the

Private Bank and the Public Sectors Banks.

-279-

Table 4.5.1.a

l Gap Issues ,,,,

Service ~ " Flexibility Tran~ctional Relational Tvoe of Fl Name Region Gap Issues Is ues Issues '· OVerall

State Bank 1

of India 1 -0.27 -0.41 -0.21 -0.89

State Bank 2 Public Sector of India 1 -0.42 -0.29 -0.45 -1.16

Banks Allahabad

1 Bank 1 -0.16 -0.35 -0.21 -0.72

Allahabad 2 Bank 1 -0.21 -0.12 -0.32 -0.65

HDFC Bank 1 1 -0.23 -0.1 -0.3 -0.63

HDFC Bank 2

Private Banks 1 -0.31 -0.17 -0.2 -0.68

ICICI Bank 1 1 -0.53 -0.12 -0.12 -0.77

ICICI Bank 2 1 -0.42 -0.28 -0.17 -0.87

Magma 1 Fincorp 1 -0.12 -0.02 -0.17 -0.31

Magma 2

NBFC Fincorp 1 -0.07 -0.04 -0.11 -0.22

Tata Motor 1 Finanace 1 -0.04 -0.06 -0.2 -0.3

Tata Motor 2 Finanace 1 -0.08 -0.15 -0.09 -0.32

A comparison over the two region do not suggest any significant difference over the

two regions in the three CRM Issues at 5% level of significant.( refer table 4.5.l.b &c)

From the Kruskal Wallis T·est for Gap I it has been found that for the flexibility issue,

the gaps are the least for the NBFC and highest for Private Sector Banks. It may be so

that the management of the Private Bank perceive that the customers expect much

more from them in flexibility terms in the rates and down payment issue,

documentation issues, credit profile judgment issues and regarding the choice of

-280-

mode of repayment issue. However in reality, the customers expect lesser from the

Private Banks but the management perceives that the expectations are similar to the

expectation they make from the NBFC.

Ranks Table 4.5.l.b

Type ofFI N Mean Rank

Flexibility Issues Public Sector Bank 4 5.63

Private Bank 4 3.38

NE:FC 4 10.50 Total 12

Transactional Issues Public Se~ctor Bank 4 3.38

Private Bank 4 6.38

NEIFC 4 9.75 Total 12

Relational Issues Public Sector Bank 4 3.00

Private Bank 4 7.00

NBFC 4 9.50 Total 12

Overall Public Sector Bank 4 3.75

Private Bank 4 5.25

N13FC 4 10.50 Total 12

Over the transactional issues the least gaps are detected for the NBFCs and the

highest gaps are prevalent in the Public Sector Banks. It suggests that the gaps are

regarding the transparency :[ssues, the promptness in delivery issues and the level of

augmented services provided by the financing Institution. The customers expect more

from the Public Sector Banks and actually receive less in this regard. As a result it

can be said that the major issues of concern should be the transactional issue for the

Public Sector Banks.

- 281 -

Table 4.5.l.c Test Statistics GAP I

Flexibility Iss01~s Transactional

Relational Issues Overall Issues

Chi-Square 8.192 6.282 6.686 7.731

df 2 2 2 2

Asymp. Sig. .017 .043 .035 .021

a Kruskal Wallis Test b Grouping Variable: Type of Fl

The relational issues, however, suggest are similar picture, with the NBFCs having

the least gaps and Public Sector Banks having the highest gaps. The relational issues

include the default management mechanism, the EMI Collection mechanism and the

level of information dissemination and relational incentives offered by the financing

Institution to their existing customers during the tenure. The NBFCs make proactive

efforts followed by the Private Banks. The Public Sector Banks make just a reactive

effort for managing the relational issues.

§4.5.2 Gap - II -The Dtesign Gap

Design Gap is given by: (Service Quality Design Specification - Management's

Perception of Customers' E:xpectations).

The design gap for all the cases across the three types of Financing Institutions over

the two regions suggest a negative score which means the service quality design

specification do not meet the management expectation which are in sync with their

perception of customer expectation. In fact the negative scores actually indicate that

the service designs in terms of flexibility, transactional and relational issues are far

behind the Management's Perception of Customers' Expectations. (refer table 4.5.2 a)

-282-

Table 4.5.2 a

Gai_lssues

. t . · ... I. ;

Service Flexibility Transactio· I Relational.<. l'ti .. .. l!vPe of Fl Name Region Gap Issues Issues ::J Issues of au

State Bank 1

of India 2 -1.33 -0.34 -0.43 -2.1

State Bank 2 Public Sector of India 2 -1.38 -0.57 -0.46 -2.41

Banks Allahabad

1 Bank 2 -0.8 -0.41 -0.22 -1.43

Allahabad 2

Bank 2 -0.76 -0.39 -0.25 -1.4

HDFC Bank 1 2 -0.58 0 -0.1 -0.68

HDFC Bank 2

Private Banks 2 -0.42 0.1 -0.12 -0.44

ICICI Bank 1 2 -0.75 -0.12 -0.1 -0.97

ICICI Bank 2 2 -0.52 0.1 -0.12 -0.54

Magma 1 Fin corp 2 -0.71 -0.02 -0.16 -0.89

Magma 2

NBFC Fincorp 2 -0.75 -0.04 -0.15 -0.94

Tata Motor 1

Finance 2 -0.64 -0.22 -0.21 -1.07

Tata Motor 2

Finance 2 -0.62 -0.26 -0.11 -0.99

The gaps are the highest for the Public Sector Banks especially in the flexibility

issues. The gaps are the least for the Private Banks in all the three issues mainly

flexibility, transactional and relational issue. The NBFC feature some where in

between the Public Sector and Private Sector Banks.

The Kruskal - Wallis Test for gap II (refer table 4.5.2 b & c) suggest that there is

significant difference over the three types of Financing Institution over each of the

three CRM issues at 5% level of significance.

-283-

Ranks Table 4.5.2 b

Type~ ofFI N Mean Rank

Flexibility Issues Public Se:ctor Bank 4 2.50

Private Bank 4 9.63 NBFC 4 7.38 Total 12

Transactional Issues Public Sector Bank 4 2.50


Relational Issues Public Se,~tor Bank 4 2.50


Overall Public Sedor Bank 4 2.50

Private Bank 4 10.00 NB:FC 4 7.00 Total 12

Test Statistics GAP II Table 4.5.2 c

Flexibility Issue!; Transactional Relational Issues Overall

Issues

Chi-Square 8.192 8.800 8.831 8.769

df 2 2 2 2

Asymp. Sig. .017 .012 .012 .012

c. Kruskal Wallis Test b Grouping Variable: Type of Fl

The test confinns that the Private Banks have the least design gaps which once again

have the implication that the service delivery specifications of the Private Banks are

much superior to the other class,es of Financing Institution.

-284-

§4.5.3 Gap- III (Conforntance Gap)

Confonnance Gap is explained by the difference between the (Service Qualities

delivered - Service quality specification).

The figures in the table 4.5.3.a below suggest that there is a positive perception of the

confonnance gap the test the service delivered is higher than the system specification.

Table 4.5.3. a

Gap;Jssues

Service Flexibility Transaction~ Relational TypeofFI Name Renion Gap Issues Issues Issues Overall

State Bank ·t of India 3 0 0.1 0.12 0.22

State Bank 2

Public Sector of India 3 0.08 0.24 0.25 0.57 Banks Allahabad ·I

Bank 3 -0.14 0.11 0.12 0.09

Allahabad :2 Bank 3 -0.32 0.25 0.32 0.25

HDFC Bank 'I 3 -0.35 -0.15 0 -0.5

HDFC Bank ') ·-Private Banks

3 -0.23 -0.135 -0.18 -0.545

ICICI Bank ·I 3 -0.7 -0.45 -0.26 -1.41

ICICI Bank 2 3 -0.3 -0.23 -0.37 -0.9

Magma 'I Fin corp 3 0.5 0.19 0.15 0.84

Magma ')

Fin corp ·-NBFCs

3 0.4 0.16 0.11 0.67

Tata Motor 'I Finance 3 0 O.o1 0.1 0.11

Tata Motor ')

Finance ·- 3 0.02 0.11 0.03 0.16

-285-

For the Public Sector Banks and the NBFCs it can therefore be concluded that the

quality specification, though, do not provide to meet with the customers expectation it

is the sole effort of the relationship managers personally which yields higher levels of

business.

For the Private Banks the gaps are negative suggesting that the management perceive

that the quality specifications are not met by the relationship personnel and therefore

the gaps are the highest.

Ranks Table 4.5.3. b

Type 1()fFI N Mean Rank


Private Bank 4 3.00



Private Bank 4 2.50


Relational Issues Public Se<:tor Bank 4 10.00

Private Bank 4 2.50



Private Bank 4 2.50


The Kruskal - Wallis Test suggest at 5% level of significance that there Is a

significant difference over the three classes of financing Institution in the

-286-

Test Statistics GAP Ill Table 4.5.3. c

Flexibility Transactional Relational Overall

Issues Issues Issues

Chi-Square 7.304 7.652 8.800 7.538

df 2 2 2 2

Asymp. Sig. .026 .022 .012 .023

c Kruskal Wallrs Test b Grouping Variable: Type of Fl

conformance gap over the flexibility, transactional and relational issues. The gaps are

the highest for the private banks and least for the NBFC and Public Sector Banks .

§4.5.4 Gap - IV - Communication Gap

The communication Gap is explained by the difference between the (Service

deliveries - promises) made to the customers.

The promises made by the relationship manager and the promotional literature to the

customers raise the expectation of the customers and if the services are not delivered

accordingly it leads to dissatisfaction. The gaps are the highest for the public sector

Banks followed by the Private Banks and NBFCs as suggested be table 4.5.4.a.

below. Table4 54 a ...

Gap Issues

Service '/' ~~· -7·

Relational Flexibility Transattional Type of Fl Name Region Gap Issues Issues Issues >Overall

State Bank 1 4 -0.67 -0.52 -0.35 -1.54

of India

State Bank 2 4 -0.68 -0.47 -0.6 -1.75

Public Sector of India

Banks Allahabad Bank

1 4 -0.8 -0.27 -0.52 -1.59

Allahabad 2 4 -0.84 -0.24 -0.62 -1.7 Bank

-287-

HDFC Bank 1 4 -0.23 -0.1 -0.25 -0.58

HDFC Bank 2

Private Banks 4 -0.27 -0.2 -0.24 -0.71

ICICI Bank 1 4 -0.27 -0.05 -0.25 -0.57

ICICI Bank 2 4 -0.27 -0.04 -0.35 -0.66

Magma 1 Fincorp 4 -0.45 -0.55 0.16 -0.84

Magma 2 Fin corp 4 -0.56 -0.65 0.17 -1.04

NBFC Tata Motor

1 Finance 4 -0.22 -0.42 0.02 -0.62

Tata Motor 2 Finance 4 -0.25 -0.61 0.06 -0.8

The over all gaps have a negative score suggesting of over promises and under

delivery. The gaps are the highest for the Public Sector Banks followed by the NBFC

and least for the Private Banks.

The gaps are the least for the transactional issues in the Private Banks suggesting

lesser of over promising under delivery. But it is higher for the flexibility issues for

the Private Banks suggesting over promise and under delivery. The relational issues

are better taken care of by the NBFCs, which means the communication Gaps are the

least for the NBFCs for the relational issues like EMI collection Mechanism, Default

Management, and Relational benefits being given to the customers. That is the

NBFCs are better at managing the Relational issues.

The Public Sector Banks fai] to beat the competition with the highest deviation in the

flexibility issues and the transactional issues.

Further the figures in the table above suggest that the gaps are higher in region II than

in Region I. It may be because of the cut-throat competition and aggressive marketing

-288-

taken up by all the classes of players in Region II which prompts the Relationship

managers to make exorbitant promises which are not fulfilled in the due course.

Ranks Table 4.5.4.b





Private· Bank 4 5.25 NBFC 4 8.75 Total 12

Relational Issues Public Sec:tor Bank 4 2.75


OveraJI Public Sector Bank 4 2.75


The Kruskal - Wallis Test for Gap IV suggest that there is a significant difference

over the types of financing Institution regarding the flexibility issue and relatioal

issue at 5% level of significance . The gaps are similar over the transactional issue

accross the three types of financing institution at 5% level of significance.

Test Statistics GAP IV Table 4.5.4.c

Flexibility Issues Transactional


Chi-Square 7.528 2.379 9.302 9.269

df 2 2 2 2

Asymp. Sig. .023 .304 .010 .010

c Kruskal Wall1s Test b Grouping Variable: Type of Fl

-289-

The managerial implication is thus the over promises and under delivery by the

Public Sector Banks and NBFCs create dissatisfaction among the customers of the

NBFCs and Public Sector Banks.

§4.5.5 Gap - V -Consumer Gap or Customer satisfaction gap

Consumer Gap or Customer satisfaction gap is explained by the difference between

the (Consumer's perception 1()f service delivery - consumer expectation of the

level of services).

The consumer gap or the customer satisfaction gap is the culmination of all the four

gaps mentioned above. The figures in the table 4.5.5.a below suggest that the gap is

negative for the public sector banks which mean the consumer perception of service

delivered is much lower than tht~ consumer expectations.

table 4.5.5.a

Gao Issues :'~1'1.

Service Flexibility Transactional Relational Jj TypeofFI Name Region Gap Issues Issues Issues all

State Bank 1 of India 5 -1.2 -1.06 -0.98 -3.24

State Bank 2

Public Sector of India 5 -1.4 -0.99 -1.32 -3.71 Banks Allahabad

Bank 1 5 -1.46 -1.36 -1.22 -4.04

Allahabad 2

Bank 5 -1.6 -1.25 -1.06 -3.91

HDFC Bank 1 5 -0.36 0.45 0.24 0.33

Private Banks HDFC Bank 2 5 0.41 0.55 0.61 1.57

ICICI Bank 1 5 -0.51 0.26 -0.07 -0.32

-290-

ICICI Bank 2 5 0.44 0.28 0.54 1.26

Magma 1 Fincorp 5 0.06 0.28 0.54 0.88

Magma 2

NBFC Fin corp 5 0.02 0.028 0.13 0.178

Tata Motor 1 Finance 5 -0.51 0.26 -0.07 -0.32

Tata Motor 2 Finance 5 -0.12 0.024 0.09 -0.006

The gaps are more or less positive for the private banks suggesting higher consumer

perception or consumer delight for the over all ratings in the two regions. The NBFC

especially, Magma Fincorp have a reputation are delighting there customers with the

services they provide.

Ranks table 4.5.5.b






Relational Issues Public Sector Bank 4 2.50




- 291-

Test Statistics table 4.5.5.c

Flexibility ISSU4!S Transactional


Chi-Square 7.497 8.831 7.785 7.883

df 2 2 2 2

Asymp. Sig. .024 .012 .020 .019

a Kruskal Wallis Test b Grouping Variable: Type of Fl

The Kruskal - Wallis Test in the tables 4.5.5.b & c suggest that there is significant

difference in all the three issue: across the three types of financing Institution over the

two regions. The gaps are the least for Private Bank and highest for the Public Sector

Bank suggesting that their CRM Tools in the issues of Transaction and Relations and

hence are much appreciated by the consumers. As a result , a positive image has been

drafted in the minds of the customers leading a positive preference for the Private

Banks among the populations of two regions.

-292-

Documents

Chapter 4 FINDINGS AND DATA ANALYSISshodhganga.inflibnet.ac.in/bitstream/10603/65866/8/08_chapter 4.pdfSyndicate Bank HDFC Bank Ltd. Magma Fincorp Ltd. Allahabad Bank Axis Bank Ltd