Consumer Preference for Mutual Funds vs Insurance at Annanagar by Sanjay Gupta

Table of Contents :

EXECUTIVE SUMMARY ABSTRACT OF THE WORK TILL THAT DATE INTRODUCTION ABOUT MUTUAL FUNDS HISTORY OF MUTUAL FUNDS ABOUT INSURANCE HISTORY OF INSURANCE

TABLE OF CONTENTS INTRODUCTION EXECUTIVE SUMMARY ABSTRACT OF THE WORK TILL THAT DATE ABOUT SBI LIFE INSURANCE COMPANY DIFFERENCE BETWEEN MUTUAL FUNDS AND INSURANCE ABOUT COMPETITORS ABOUT ANNANAGAR(AREA OF PROJECT) MAIN TEXT Objectives Sampling design Research design Data collection SPSS Output Analysis from SPSS Output Data analysis Findings Limitations Recommendations BIBLIOGRAPHY

Acknowledgement I would like to thank my faculty guide Gopi Chander who not only served as a supervisor but also guided and encouraged me in doing this project.

I would also like to thank my company guide Mr V.Sathish Kumar for giving me the directions and encouraging me in doing this project

I would also like to thank Mr Gopal Branch Manager of SBI Life Insurance company for giving their sincere support and guidance to me in doing this project

Date

April 22, 2008

Place

Annanagar (Chennai)

Executive Summary This report was basically undertaken to find out the consumer preference for mutual funds(Reasons for them to prefer mutual funds) and insurance(Reasons for the people to prefer insurance) in anna nagar. Before doing this project I did a thorough study about mutual funds and insurance.

The basic objective of the research was to find: -

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Consumer Preference for mutual funds ○ Advantages of investing in mutual funds ○ Disadvantages of investing in mutual funds ○ Consumer perception towards mutual funds

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Consumer Preference for insurance ○ Advantages of investing in insurance ○ Disadvantage of investing in insurance ○ Consumer perception towards insurance

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Reasons for migrating from mutual funds to insurance and vice versa

ABSTRACT OF THE WORK TILL THAT DATE:

DATE 22nd feb -29th feb

1 March – 8 March

WORK DONE • Classes conducted regarding insurance products •

Brief introduction about the SBI Life insurance company

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Training given to me regarding selling Lead generation done in annanagar , saidapet

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Collecting details regarding the various other insurance companies and putting the details in a excel sheet to get the summarized form

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Conducted field activities in Arihant flat, meeting professionals in the marketing the insurance products

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I also met my faculty guide Mr Gopi Chander for getting feedbacks about my work

8th March – 15th March

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Discussed about my project to my Unit Manager and submitted my Initial Information Report to my Faculty Guide

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Soldone UNIT PLUS 2 premium of Rs 50,000

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Got permission for conducting field activity near Odyssey Shop to target a bulk of people for insurance.

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Lead generation done in T Nagar and I got a permission to present about the various insurance schemes available in SBI Life Insurance to the people in a MVS training institute

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Also did a follow up of leads generated in the previous week and tried to fix up an appointment with the customers

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On Friday I met my Faculty Guide for getting feebacks

policy for a

15th March – 22nd March

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Project was given to me from SBI headquarters.

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My project title “Consumer Preference of Mutual Funds Vs Insurance”

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I also discussed about my project to faculty guide and I got few tips in preparing questionnaire for my project

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Did field activities in a) Valluvar kottam b) T Nagar c) Century Plaza

22nd March to 29th March

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I also did a follow up of leads that I generated in the last weeks

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Finished one UNIT PLUS 2 policy for 25000

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My questionnaire for the project is approved by Mr Gopi Chander

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Did field work in Odyssey shop and I did the lead generation

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I started working on my project and first I targeted people in Annanagar East Survey for my project done in Annanagar East in all shopping complexes, consultancy, and a few residential areas Survey for my project is done with the people in Annanagar West and Shenoy

1st April to 8th April

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8th April to 15th April

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Nagar to do the market research •

Started collected some secondary data for interim report

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I also discussed about interim report both with my company guide and faculty guide for getting better quality Did surveys regarding my project in Annanagar and collected primary data for secondary data analysis

15th April to 30th April

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1st May to 15th May

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Did data analysis of my primary data and started preparing my final report

INTRODUCTION:

This project was basically taken to find out the consumer preference of mutual funds (Reasons for them to prefer mutual funds) and insurance (Reasons for preferring insurance). Before starting this project I did a thorough study about the mutual funds ,Insurance and their classification Mutual funds: Mutual funds is defined as a method of joint investment by pooling money from many investors and investing them in shares, funds, short term financial institutions etc. The value of mutual fund is calculated as NAV of the company. It is calculated on daily basis NAV=Market Value of Investment + Number of Outstanding Units

Current Assets-Current Liabilities/

Mutual funds can be classified based on maturity value, investment, other equity related funds

Based on maturity mutual fund is classified as a) Open ended funds(No maturity period) b) Closed ended funds(Maturity period varies from 3 months to 15 yrs Based on investment mutual fund is classified as a) Equity or Growth fund b) Debt fund c) Balanced fund d) Money market fund Based on other equity funds mutual fund is classified as a) Tax savings schemes

a. Earnings Linked Savings Scheme(ELSS) b. Earnings Linked Pension Scheme(ELPS) b) Sectoral Schemes It includes investing in IT sector, Banks and other government / nongovernment institutions c) Index schemes HISTORY OF MUTUAL FUNDS : The mutual fund industry in India started in 1963 with the formation of Unit Trust of India, at the initiative of the Government of India and Reserve Bank the. The history of mutual funds in India can be broadly divided into four distinct phases •

First Phase – 1964-87

Unit Trust of India (UTI) was established on 1963 by an Act of Parliament. It was set up by the Reserve Bank of India and functioned under the Regulatory and administrative control of the Reserve Bank of India. In 1978 UTI was de-linked from the RBI and the Industrial Development Bank of India (IDBI) took over the regulatory and administrative control in place of RBI. The first scheme launched by UTI was Unit Scheme 1964. At the end of 1988 UTI had Rs.6,700 crores of assets under management. •

Second Phase – 1987-1993 (Entry of Public Sector Funds)

1987 marked the entry of non- UTI, public sector mutual funds set up by public sector banks and Life Insurance Corporation of India (LIC) and General Insurance Corporation of India (GIC). SBI Mutual Fund was the first non- UTI Mutual Fund established in June 1987 followed by Canbank Mutual Fund (Dec 87), Punjab National Bank Mutual Fund (Aug 89), Indian Bank Mutual Fund (Nov 89), Bank of India (Jun 90), Bank of Baroda Mutual Fund (Oct 92). LIC established its mutual fund in June 1989 while GIC had set up its mutual fund in December 1990. At the end of 1993, the mutual fund industry had assets under management of Rs.47,004 crores.

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Third Phase – 1993-2003 (Entry of Private Sector Funds)

With the entry of private sector funds in 1993, a new era started in the Indian mutual fund industry, giving the Indian investors a wider choice of fund families. Also, 1993 was the year in which the first Mutual Fund Regulations came into being, under which all mutual funds, except UTI were to be registered and governed. The erstwhile Kothari Pioneer (now merged with Franklin Templeton) was the first private sector mutual fund registered in July 1993. The 1993 SEBI (Mutual Fund) Regulations were substituted by a more comprehensive and revised Mutual Fund Regulations in 1996. The industry now functions under the SEBI (Mutual Fund) Regulations 1996. The number of mutual fund houses went on increasing, with many foreign mutual funds setting up funds in India and also the industry has witnessed several mergers and acquisitions. As at the end of January 2003, there were 33 mutual funds with total assets of Rs. 1,21,805 crores. The Unit Trust of India with Rs.44,541 crores of assets under management was way ahead of other mutual funds.

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Fourth Phase – since February 2003

In February 2003, following the repeal of the Unit Trust of India Act 1963 UTI was bifurcated into two separate entities. One is the Specified Undertaking of the Unit Trust of India with assets under management of Rs.29,835 crores as at the end of January 2003, representing broadly, the assets of US 64 scheme, assured return and certain other schemes. The Specified Undertaking of Unit Trust of India, functioning under an administrator and under the rules framed by Government of India and does not come under the purview of the Mutual Fund Regulations.

The second is the UTI Mutual Fund Ltd, sponsored by SBI, PNB, BOB and LIC. It is registered with SEBI and functions under the Mutual Fund Regulations. With the bifurcation of the erstwhile UTI which had in March 2000 more than Rs.76,000 crores of assets under management and with the setting up of a UTI Mutual Fund, conforming to the SEBI Mutual Fund Regulations, and with recent mergers taking place among different private sector funds,

the mutual fund industry has entered its current phase of consolidation and growth. As at the end of September, 2004, there were 29 funds, which manage assets of Rs.153108 crores under 421 schemes. The graph indicates the growth of assets over the years.

GROWTH IN ASSETS UNDER MANAGEMENT

Note: Erstwhile UTI was bifurcated into UTI Mutual Fund and the Specified Undertaking of the Unit Trust of India effective from February 2003. The Assets under management of the Specified Undertaking of the Unit Trust of India has therefore been excluded from the total assets of the industry as a whole from February 2003 onwards.

Brief History Of Insurance Sector In India The insurance sector in India has come a full circle from being an open competitive market to nationalization and back to a liberalized market again. Tracing the developments in the Indian insurance sector reveals the 360-degree turn witnessed over a period of almost 190 years. The business of life insurance in India in its existing form started in India in the year 1818 with the establishment of the Oriental Life Insurance Company in Calcutta. Some of the important milestones in the life insurance business in India are: 1912 - The Indian Life Assurance Companies Act enacted as the first statute to regulate the life insurance business. 1928 - The Indian Insurance Companies Act enacted to enable the government to collect statistical information about both life and non-life insurance businesses. 1938 - Earlier legislation consolidated and amended to by the Insurance Act with the objective of protecting the interests of the insuring public. 1956 - 245 Indian and foreign insurers and provident societies taken over by the central government and nationalized. LIC formed by an Act of Parliament, viz. LIC Act, 1956, with a capital contribution of Rs. 5 crore from the Government of India. The General insurance business in India, on the other hand, can trace its roots to the Triton Insurance Company Ltd., the first general insurance company established in the year 1850 in Calcutta by the British. Some of the important milestones in the general insurance business in India are: 1907 - The Indian Mercantile Insurance Ltd. set up, the first company to transact all classes of general insurance business. 1957 - General Insurance Council, a wing of the Insurance Association of India, frames a

code of conduct for ensuring fair conduct and sound business practices. 1968 - The Insurance Act amended to regulate investments and set minimum solvency margins and the Tariff Advisory Committee set up. 1972 - The General Insurance Business (Nationalization) Act, 1972 nationalized the general insurance business in India with effect from 1st January 1973. 107 insurers amalgamated and grouped into four companies viz. the National Insurance Company Ltd., the New India Assurance Company Ltd., the Oriental Insurance Company Ltd. and the United India Insurance Company Ltd. GIC incorporated as a company. Indian Life Insurance Industry Overview All life insurance companies in India have to comply with the strict regulations laid out by Insurance Regulatory and Development Authority of India (IRDA). Therefore there is no risk in going in for private insurance players. In terms of being rated for financial strength like international players, only ICICI Prudential is rated by Fitch India at National Insurer Financial Strength Rating of AAA(Ind) with stable outlook indicating the highest claims paying ability rating. Life Insurance Corporation of India (LIC), the state owned behemoth, remains by far the largest player in the market. Among the private sector players, ICICI Prudential Life Insurance(JV between ICICI Bank and Prudential PLC)is the largest followed by Bajaj Allianz Life Insurance Company Limited (JV between Bajaj Group and Allianz). The private companies are coming out with better products which are more beneficial to the customer. Among such products are the ULIPs or the Unit Linked Investment Plans which offer both life cover as well as scope for savings or investment options as the customer desires.Further, these type of plans are subject to a minimum lock-in period of three years to prevent misuse of the significant tax benefits offered to such plans under the Income Tax Act. Hence, comparison of such products with mutual funds would be erroneous. Commission / Intermediation fees •

The maximum commission limits as per statutory provisions are:

Agency commission for retail life insurance business:  35 - 40% for 1st year premium if the premium paying term is more than 20 years  25 - 30% for 1st year premium if the premium paying term is more than 15 years

 10 - 15% for 1st year premium if the premium paying term is less than 10 years  7.5% - yr 2 and 3rd year and 5% - thereafter for all premium paying terms. In case of Mutual fund related - Unit linked policies it varies between 1.5% to 60% on the premium paid. ○ Agency commission for retail pension policies:  7.5% for 1st year premium and 2.5% thereafter •

Maximum broker commission - 30%

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Referral fees to banks – Max 55% for regular premium and 10% for single premium. However in any case this fee cannot be more than the agency commission as filed under the product.

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However, the above commission may be further subject to the product wise limits specified by IRDA while approving the product.

TERM PLAN VS PREMIUM-GUARANTEED PLAN DNA Money October 28, 2006 It makes more sense to go for a term plan with no survival benefit MUMBAI: God and devil, they say, is in the detail. And Shalin Saxena was just finding that out. A little bit of research had told him that premium-guaranteed term insurance plans just did not make sense. Shalin was looking to opt for a term insurance plan. In a term insurance plan, if the policy holder expires during the policy period, his nominee will get the sum assured (the insurance amount). If the policy holder survives the policy period, he will not get anything. The insurance advisor who had come to Shalin had told him, “Sir, why do you opt for a term insurance plan? If you survive the policy period, you won’t get the premium back. So, why don’t you opt for a premium- guaranteed term plan. Here, the premium is a little more, but if you survive the policy period, you will get all the premium paid back”. Initially, he was very excited about the fact that he would get all the premium back. But soon he realised that there was more to it than what meets the eye. And some amount of Net surfing told him why.

ICICI Prudential Life Insurance offers a policy called LifeGuard with a level term assurance and a return of premium option. Under this policy, if a healthy male, aged 30, opts for a 20-year policy, with a sum assured of Rs 10 lakh, he needs to pay an annual premium of Rs 10,860. If he survives the policy period, the company will return all the premium paid over 20 years, i.e., Rs 2,17, 200 (Rs 10,860 x 20). So far, so good. Let’s see what happens if the individual, instead of opting for the return of premium option, opts for a level term assurance option, wherein he does not get the premium back, if he survives the policy period. In this case, the premium to be paid for the sum assured of Rs 10 lakh for 20 years is Rs 2,751, almost one-fourth of the earlier case. Now let’s say the individual opts for a simple term assurance option. He obviously has to pay a premium of Rs 2,751 per year. The difference in premium between the two options works out to be Rs 8,109 (Rs 10,860 - Rs 2,751). If the individual were to invest this difference of Rs 8,109 in public provident fund (PPF) for 20 years, he would get an amount of Rs 4,00,770.5. The PPF account pays an interest of 8% per annum and matures 15 years after the end of the financial year in which the first investment was made. Upon maturity, the investor has the option of extending it by five years. So, by simply investing the difference between the premiums, in a PPF, the individual can ensure that he gets 85% more money than he would have got, if he had opted for the return of premium option. There is always the risk of the interest paid on the PPF account coming down. But even if the interest rate were to fall to 3%, which is highly unlikely, the individual would get Rs 2,24,428.6 at the end of 20 years. This is still more than the Rs 2,17, 200 he would have got in case he had opted for a return of premium option. The story holds true even with other insurance companies. Let’s take the example of two policies — Swadhan and Shield-Level Cover - from SBI Life. Swadhan is a premium-guarantee term plan whereas Shield-Level Cover is a simple term plan. If a healthy male, aged 30, opts for a 10-year cover with a sum assured of Rs 20 lakh, in case of Swadhan, he has to pay a premium of Rs 27,631 per annum. If he opts for Shield-Level Cover, the premium drops to Rs 3,985 per annum. If the individual survives the 10 years of the cover, he gets Rs 2,76,310 in case of Swadhan and nothing in case of Shield-Level cover. If the premium differential of Rs 23,646 were to be invested every year for 10 years, and even if the return earned is as low as 3%, he would have got Rs 2,79,207.1 at the end of 10 years. This is more than what he will get in case of Swadhan, the policy which guarantees return of premium.

Having done his research, Shalin concluded that premium-guaranteed term plans do not make sense. He had seen both God and devil in the detail.

INSURANCE:

A promise of compensation for potential future losses in exchange of periodic payment is known as insurance

Types of insurance: A) Health Care Insurance B) Life Insurance C) Home Insurance D) Auto Insurance E) Travel Insurance

Various types of Life Insurance Schemes: The various types of life insurance schemes are as follows a) Investment Scheme a. ULIPS b. UNIT PLUS CHILD PLAN b) Savings Scheme a. Money Back Plan b. Endowment Plan c) Pension Scheme d) Risk Plan a. Swadhan Plan

Differences between Mutual funds and Insurance

MUTUAL FUNDS PREMIUM AMOUNT CANNOT INCREASED/DECREASED

INSURANCE BE FLEXIBILITY IN PREMIUM

LOW ADMINISTRATIVE CHARGES

ADMINISTRATIVE CHARGES ARE HIGH

NO LIFE COVER

LIFE COVER

EASE OF PROCESS

COMPLICATED

NO LOCKUP PERIOD

LOCKUP PERIOD IS THERE

SWITCHING FROM ONE FUND TO OTHE FREE ENTRY/EXIT LOAD OTHER FUND IS COSTLY All mutual funds do not give tax benefits

All insurance schemes provides tax benefits

ABOUT SBI LIFE INSURANCE COMPANY Our Mission:"To emerge as the leading company offering a comprehensive range of life insurance and pension products at competitive prices, ensuring high standards of customer

satisfaction and world class operating efficiency, and become a model life insurance company in India in the post liberalization period". Our Values: •

Trustworthiness

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Ambition

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Innovation

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Dynamism

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Excelllence

SBI Life Insurance is a joint venture between the State Bank of India and Cardif SA of France. SBI Life Insurance is registered with an authorized capital of Rs 1000 crore and a paid up capital of Rs 500 crores. SBI owns 74% of the total capital and Cardif the remaining 26%. State Bank of India enjoys the largest banking franchise in India. Along with its 7 Associate Banks, SBI Group has the unrivalled strength of over 14,500 branches across the country, arguably the largest in the world. Cardif is a wholly owned subsidiary of BNP Paribas, which is the Euro Zone’s leading Bank. BNP Paribas is one of the oldest foreign banks with a presence in India dating back to 1860. Cardif is ranked 2nd worldwide in creditor’s insurance offering protection to over 35 million policyholders and net income in excess of Euro 1 billion. Cardif has also been a pioneer in the art of selling insurance products through commercial banks in France and in 35 more countries. SBI Life Insurance’s mission is to emerge as the leading company offering a comprehensive range of Life Insurance and pension products at competitive prices, ensuring high standards of customer service and world class operating efficiency. SBI Life has a unique multi-distribution model encompassing Bank assurance, Agency and Group Corporate. SBI Life extensively leverages the SBI Group as a platform for cross-selling insurance products along with its numerous banking product packages such as housing loans and personal loans. SBI’s access to over 100 million accounts across the country provides a vibrant base for insurance penetration across every region and economic strata in the country ensuring true financial inclusion.

Agency Channel, comprising of the most productive force of more than 25,000 Insurance Advisors, offers door to door insurance solutions to customers.

SBI COMPETITORS: •

LIC

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ICICI

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BAJAJ

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HDFC

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TATA AIG

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RELIANCE

ABOUT LIC MUTUAL FUNDS:

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Life Insurance Corporation of India set up LIC Mutual Fund on 19th June 1989 and contributed Rs. 2 Crores towards the corpus of the Fund.

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LIC Mutual Fund was constituted as a Trust in accordance with the provisions of the Indian Trust Act, 1882 . The settlor is not responsible for the management of the Trust.

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The settlor is also not responsible or liable for any loss or shortfall resulting in any of the schemes of LIC Mutual Fund. • The Trustees of the LIC Mutual Fund have exclusive ownership of Trust Fund and are vested with general power of superintendence, discretion and management of the affairs of the Trust.

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LIC Mutal Fund Asset Management Company Ltd. was formed on 20th April 1994 in compliance with the Securities and Exchange Board of India (Mutual Funds) Regulations, 1993.

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The Company commenced business on 29th April 1994.

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The Trustees of LIC Mutual Fund have appointed LIC Mutual Fund Asset Management Company Ltd. as the Investment Managers for LIC Mutual Fund.

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The Trustees are responsible for appointing a Custodian.

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The Trustees should also ensure that the activities of the Trust and the Asset Management Company are in accordance with the Trust Deed and the SEBI Mutual Fund Regulations as amended from time to time. The Trustees have also to report periodically to SEBI on the functioning of the Fund.

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The investors under the schemes can obtain a copy of the Trust Deed, the text of the concerned Scheme as also a copy of the Annual Report, on a written request made to the LIC Mutual Fund Asset Management Company Ltd. at a nominal price of Rs.

10/-.

LIC INSURANCE PLANS

As individuals it is inherent to differ. Each individualďż˝s insurance needs and requirements are different from that of the others. LICďż˝s Insurance Plans are policies that talk to you individually and give you the most suitable options that can fit your requirement.

Jeevan Anurag CDA Endowment Vesting At 21 CDA Endowment Vesting At 18 Jeevan Kishore Child Career Plan

Jeevan Aadhar Jeevan Vishwas

Komal Jeevan Marriage Endowment Or Educational Annuity Plan Jeevan Chhaya Child Future Plan

The Endowment Assurance Policy The Endowment Assurance Policy-Limited Payment Jeevan Mitra(Double Cover Endowment Plan) Jeevan Mitra(Triple Cover Endowment Plan) Jeevan Anand New Janaraksha Plan Jeevan Amrit

Jeevan Shree-I Jeevan Pramukh

The Money Back Policy-20 Years The Money Back Policy-25 Years Jeevan Surabhi-15 Years Jeevan Surabhi-20 Years Jeevan Surabhi-25 Years Bima Bachat

Jeevan Bharati

The Whole Life Policy The Whole Life Policy- Limited Payment The Whole Life Policy- Single Premium Jeevan Anand Jeevan Tarang

Two Year Temporary Assurance Policy The Convertible Term Assurance Policy Anmol Jeevan-I Amulya Jeevan (Closed)

ICICI LIFE INSURANCE: On the basis of which life stage you are in and the corresponding insurance needs, ICICI Prudential plans can be categorized into the following three types: •

Education Insurance Plans

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Wealth Creation Plans

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Premium Guarantee plans

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Protection Plans

ABOUT ICICI MUTUAL FUNDS:

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At ICICI Bank we will help you identify an appropriate mix of Mutual Fund schemes for your portfolio using asset allocation strategies.

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Through ICICI Bank you can invest in various schemes of multiple mutual funds with decent performance record.

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You can take the aid of our various research reports on mutual funds and their schemes before choosing a scheme for investment.

ICICI Bank offers investment in Mutual Funds through Multiple Channels. With ICICI Bank, you can invest in Mutual Funds through following channels •

ICICI Bank Branches

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ICICIdirect.com

Dedicated workforce to serve you •

Before being deputed, our officers complete a comprehensive training program and, once deputed, they receive thorough instructions in financial planning skills and techniques. Throughout their careers officers also attend programs to update their skills.

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All officers in charge of Mutual Funds are certified professionals by AMFI (Association of Mutual Funds in India)

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Many of these officers also hold professional degrees like -

MBA, CA, ICWA, CFA etc.

Anna Nagar Anna Nagar is one of the best residential areas located in the city of Chennai. The region lies south of the Chennai central and features a regular and planned township. The region is as much a residential place as it is a commercial centre. The township is hooked with straight road within its premises and links to the major roads that connects it with other city areas. The region marks the boundary of the actual city area. Anna Nagar area is spread out in small regular blocks with straight roads separating the adjacent ones. The blocks are named by single alphabets, like block 'A', as well combination of two alphabets, 'AD', 'AF', 'AG', 'AL', etc. There is a small locality in the east called Anna Nagar East. The eastern side of 'Y' block, at Anna Nagar, is marked by popular Visweswararya Tower Park. The park features an imposing tower structure and the sprawling lawns. The park was rarely visited due to is deplorable conditions following negligence. But the renovations in the past few years has returned back the charm and beauty. The region of Anna Nagar is provided with numerous enterprises that are responsible for various commercial activities. Hotels, restaurants, shopping stores and I.T.Companies are in abundance. One of the best places for shopping at Anna Nagar is at 'Any Shopping Complex.' Some renowned enterprises from the region are as: I.T.Companies: Avanor Systems Pvt. Ltd., Eco Tech Software Pvt. Ltd., Pegasus Software, Palpap Software, Launch Pad, Astra Infotech, L-Cube Innovation Solutions, Precision Software Communications

Hotels: Hotel Saravana, Hotel Soorya, Hotel Sky Park

Restaurants: Nawab's Restaurant, Moghul Feast, Blue Star Biryani, Prabhu Restaurant. Hospitals: Sridevi Hospital, Senthil Hospital, K.H.M. Hospital, Medical Foundation.

Accessibility

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Anna Nagar lies precisely to the west of George Town, the city center. The two, as well as other suburbs, are connected by a network of roads and railways. The road distance between the two is approximately 6 kms.

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Anna Nagar has a railway terminal located towards its northern edge. The railways thus, provide the accessibility.

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Chennai Airport located at Meenambakkam is the nearest and about 10 kms far from Anna Nagar.

Areas Under Anna Nagar •

Shenoy Nagar

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Anna Nagar East

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Anna Nagar West

MAIN TEXT:

The main text will include the following •

OBJECTIVES

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PLANNING RESEARCH DESIGN

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RESEARCH METHOD

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SAMPLING PROCEDURE

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DATA COLLECTION

OBJECTIVES:

The objective of the project is to compare the consumer preference for mutual funds and insurance products

A) CONSUMER PREFERENCE FOR MUTUAL FUNDS

a. REASONS FOR CONSUMER PREFERENCE OF MUTUAL FUNDS b. ADVANTAGES OF INVESTING IN MUTUAL FUND c. DISADVANAGES OF INVESTING IN MUTUAL FUNDS

B) CONSUMER PREFERENCE FOR INSURANCE a. REASONS FOR CONSUMER PREFERENCE FOR INSURANCE b. ADVANTAGES OF INVESTING IN INSURANCE c. DISADVANTAGES OF INVESTING IN INSURANCE C) REASONS FOR CONSUMER INSURANCE AND VICE VERSA

MIGRATING FROM MUTUAL FUNDS TO

RESEARCH METHOD : This research is basically undertaken to find the customer preference of mutual funds and insurance. After preparing a questionnaire a survey is done to the people in anna nagar area to find their preference for mutual funds and insurance

The research design used was basically of exploratory in nature.

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Information was gathered on all the issues pertaining to the research & a variety of techniques were used to analyze the findings of the research.

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Questionnaire was the main tool taken into account for data collection & it was designed in such a way that it catered to the needs of the research being undertaken.

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Both open & closed ended questions were used in the questionnaires involving both probing & in-depth analysis of the questions.

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In the research both secondary & primary sources were taken into consideration for data collection. Questionnaire was the main tool for primary data & secondary sources were newspaper articles, magazines, internet etc.

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The scales used in the study were basically all – nominal, ordinal, interval & ratio. Nominal & Ordinal was used in the findings related to the qualitative data . Interval & Ratio scales were used in the context of quantitative data,

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The instruments used in the findings of our study were basically surveys & questionnaires. Surveys were done in shopping malls ,companies of Annanagar East and West.

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The main strengths of our study were the data collection part. I did a lot of surveys in various parts of Annanagar & also a lot of respondents were taken into account for questionnaires.

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The major weaknesses from our side were the time & money constraints which limited our research to a certain limit.

Sampling Design  Target Population: 1. Age Group between 16-65 years.  Sampling Type: Probability Sampling (Simple Random)  Sample Size: - 100 Respondents.  Level of Confidence: - 95% ( 5% error assumed) DATA COLLECTION: Time of data collection: I started the research in the month of March 2008 & it is expected to be completed the final study by the month of May 2008

Field condition during data collection:

The march month was the main season for insurance and most of the people may prefer insurance in the month of march (Tax benefit) In April month it was a festival season(Tamil New Yearâ&#x20AC;&#x2122;s Day).So shop was more crowded and I could get more customers for survey.I took the surveys taking these factors into consideration 1) Age

2) Sex 3) Income 4) Occupation I took equal no of surveys in all the interior variables of each

BEST FORM OF INVESTMENT

Crosstabs

Case Processing Summary

N GENDER * SHAREMKT GENDER * BANK GENDER * POSTOFF GENDER * GOLD GENDER * MUTUAL GENDER * REALESTA GENDER * INSURANC AGE * SHAREMKT AGE * BANK AGE * POSTOFF AGE * GOLD AGE * MUTUAL AGE * REALESTA AGE * INSURANC OCCUPATI * SHAREMKT OCCUPATI * BANK OCCUPATI * POSTOFF OCCUPATI * GOLD OCCUPATI * MUTUAL OCCUPATI * REALESTA OCCUPATI * INSURANC INCOME * SHAREMKT INCOME * BANK INCOME * POSTOFF INCOME * GOLD INCOME * MUTUAL INCOME * REALESTA INCOME * INSURANC

GENDER * SHAREMKT

Valid Percent 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0%

Cases Missing N Percent 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0%

Total N 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101

Percent 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Crosstab Count 1.00 GENDER

female male

2.00 3 7 10

Total

SHAREMKT 3.00 5 18 14 17 19 35

4.00

5.00 13 13 26

Total 5 5 10

44 56 100

Chi-Square Tests Value 4.517a 4.670 100

Pearson Chi-Square Likelihood Ratio N of Valid Cases

df 4 4

Asymp. Sig. (2-sided) .341 .323

a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 4.40.

GENDER * BANK Crosstab Count 1.00 GENDER

female male

2.00 12 11 23

Total

7 16 23

BANK 3.00 23 20 43

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 7.007a 7.436 100

df 4 4

Asymp. Sig. (2-sided) .136 .115

a. 4 cells (40.0%) have expected count less than 5. The minimum expected count is 1.76.

GENDER * POSTOFF

4.00

5.00 1 6 7

Total 1 3 4

44 56 100

Crosstab Count 1.00 GENDER

female male

2.00 18 34 52

Total

14 7 21

POSTOFF 3.00 11 10 21

4.00

5.00 1 4 5

Total 1 1

44 56 100

Chi-Square Tests Value 8.791a 9.300 100

Pearson Chi-Square Likelihood Ratio N of Valid Cases

df 4 4

Asymp. Sig. (2-sided) .067 .054

a. 4 cells (40.0%) have expected count less than 5. The minimum expected count is .44.

GENDER * GOLD Crosstab Count 1.00 GENDER

female male

2.00 7 7 14

Total

13 23 36

GOLD 3.00 16 16 32

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 1.611a 1.622 100

df 4 4

Asymp. Sig. (2-sided) .807 .805

a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is .88.

GENDER * MUTUAL

4.00

5.00 7 9 16

Total 1 1 2

44 56 100

Crosstab Count 1.00 GENDER

female male

2.00 4 8 12

Total

10 9 19

MUTUAL 3.00 16 15 31

4.00

5.00 12 13 25

Total 2 11 13

44 56 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 6.340a 6.900 100

df 4 4

Asymp. Sig. (2-sided) .175 .141

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5.28.

GENDER * REALESTA Crosstab Count 1.00 GENDER

female male

Total

2.00 11 17 28

REALESTA 3.00 8 15 10 21 18 36

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 1.989a 1.980 100

df 4 4

Asymp. Sig. (2-sided) .738 .740

a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 2.20.

GENDER * INSURANC

4.00

5.00 8 5 13

Total 2 3 5

44 56 100

Crosstab Count 1.00 GENDER

female male

2.00 8 12 20

Total

INSURANC 3.00 12 18 12 17 24 35

4.00

5.00 6 12 18

Total 44 56 100

3 3

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 4.453a 5.588 100

df 4 4

Asymp. Sig. (2-sided) .348 .232

a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 1.32.

AGE * SHAREMKT Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

Total

2.00 2 3 4 1 10

SHAREMKT 3.00 1 4 10 14 3 11 1 3 4 1 2 19 35

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 15.231a 15.076 100

df 20 20

Asymp. Sig. (2-sided) .763 .772

a. 24 cells (80.0%) have expected count less than 5. The minimum expected count is .10.

4.00

5.00

Total

7 10 4

1 6 2

3 2 26

1 10

15 43 24 1 12 5 100

AGE * BANK Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

Total

BANK 3.00

2.00

4.00

5.00

Total

7 5 8 1 2

4 14 5

3 17 8

5 2

1 2 1

10 5 43

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 33.062a 38.226 100

df 20 20

Asymp. Sig. (2-sided) .033 .008

a. 22 cells (73.3%) have expected count less than 5. The minimum expected count is .04. Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

Total

AGE * POSTOFF

2.00 3 27 13 1 5 3 52

6 6 6 3 21

POSTOFF 3.00 6 8 3 3 1 21

4.00

5.00 1 2 1 1 5

Total 1

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 19.435a 21.052 100

df 20 20

Asymp. Sig. (2-sided) .494 .394

a. 22 cells (73.3%) have expected count less than 5. The minimum expected count is .01.

AGE * GOLD Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

Total

GOLD 3.00

2.00 4 8 2

5 12 17

5 14 4

1 1 36

6 3 32

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 37.116a 37.317 100

df 20 20

Asymp. Sig. (2-sided) .011 .011

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .02.

AGE * MUTUAL

4.00

5.00 1 7 1 1 5 1 16

Total 2

15 43 24 1 12 5 100

Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

Total

2.00 1 1 2

7 6 5

4 4 12

MUTUAL 3.00 4 12 9

4.00

5 1 31

5.00 3 15 6

Total

9 2 1 1

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 53.702a 43.805 100

df 20 20

Asymp. Sig. (2-sided) .000 .002

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .12.

AGE * REALESTA Crosstab Count 1.00 AGE

Total

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

2.00 6 12 5

2 9 5

4 1 28

2 18

REALESTA 3.00 7 14 8 1 4 2 36

4.00

5.00

Total

5 5

3 1

2 1 13

1 5

15 43 24 1 12 5 100

Chi-Square Tests Value 12.767a 15.934 100

Pearson Chi-Square Likelihood Ratio N of Valid Cases

df 20 20

Asymp. Sig. (2-sided) .887 .721

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .05.

AGE * INSURANC Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

Total

2.00 1 6 11 2

INSURANC 3.00 5 5 10 17 7 5 1 1 24

20 Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 28.365a 31.862 100

df 20 20

Asymp. Sig. (2-sided) .101 .045

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .03.

OCCUPATI * SHAREMKT

6 2 35

4.00

5.00 4 8 1 3 2 18

Total 2 1

15 43 24 1 12 5 100

Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

2.00 5 1 3 1

Total

10 2 3 3 1 19

SHAREMKT 3.00 20 5 6 4

4.00

5.00

Total

14 7 3 2

7 1 1 1

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 10.036a 8.660 100

df 16 16

Asymp. Sig. (2-sided) .865 .927

a. 18 cells (72.0%) have expected count less than 5. The minimum expected count is .10.

OCCUPATI * BANK Crosstab Count 1.00 OCCUPATI

Total

professional retired self employed student Student

2.00 12 7 1 2 1 23

15 3 5

BANK 3.00 21 6 7 9 43

4.00

5.00

Total

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 23.310a 26.524 100

df 16 16

Asymp. Sig. (2-sided) .106 .047

a. 20 cells (80.0%) have expected count less than 5. The minimum expected count is .04.

OCCUPATI * POSTOFF Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

Total

10 5 3 3

POSTOFF 3.00 9 5 5 2

2.00 36 5 5 5 1 52

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 18.932a 19.961 100

df 16 16

Asymp. Sig. (2-sided) .272 .222

a. 19 cells (76.0%) have expected count less than 5. The minimum expected count is .01.

OCCUPATI * GOLD

4.00

5.00

Total 1

1 3 1 5

56 16 16 11 1 100

Crosstab Count

9 4 1

21 4 10 1

GOLD 3.00 17 6 4 5

1.00 OCCUPATI

professional retired self employed student Student

Total

2.00

4.00

5.00 7 2 1 5 1 16

Total 2

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 25.021a 24.336 100

df 16 16

Asymp. Sig. (2-sided) .069 .082

a. 17 cells (68.0%) have expected count less than 5. The minimum expected count is .02.

OCCUPATI * MUTUAL Crosstab Count

3 5 4

10 7 1 1

MUTUAL 3.00 16 3 8 4

1.00 OCCUPATI

Total

professional retired self employed student Student

2.00

4.00

5.00 20 3 1 1 25

Total 10 1 1 1 13

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 44.354a 47.149 100

df 16 16

Asymp. Sig. (2-sided) .000 .000

a. 20 cells (80.0%) have expected count less than 5. The minimum expected count is .12.

OCCUPATI * REALESTA Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

Total

2.00 15 6 3 4

14 1 2 1

REALESTA 3.00 16 8 7 4 1 36

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 12.616a 14.140 100

df 16 16

Asymp. Sig. (2-sided) .701 .588

a. 19 cells (76.0%) have expected count less than 5. The minimum expected count is .05.

OCCUPATI * INSURANC

4.00

5.00

Total

8 1 2 2

56 16 16 11 1 100

Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

Total

2.00 15 4 1

11 6 6 1

INSURANC 3.00 21 7 1 6 35

4.00

5.00 7 3 4 3 1 18

Total 2 1

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 22.562a 27.091 100

df 16 16

Asymp. Sig. (2-sided) .126 .040

a. 19 cells (76.0%) have expected count less than 5. The minimum expected count is .03.

INCOME * SHAREMKT Crosstab Count 1.00 INCOME

Total

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

2.00 3 1 4 2 10

SHAREMKT 3.00 7 14 1 4 10 5 8 2 2 1 19 35

4.00

5.00

Total

6 5 2

3 4

40 1 24 26 8 1 100

Chi-Square Tests Value 13.750a 13.372 100

Pearson Chi-Square Likelihood Ratio N of Valid Cases

df 20 20

Asymp. Sig. (2-sided) .843 .861

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .10.

INCOME * BANK Crosstab Count 1.00 INCOME

2.00

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

5 1 5 7 5

BANK 3.00 15

6 5

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 49.536a 35.002 100

df 20 20

Asymp. Sig. (2-sided) .000 .020

a. 21 cells (70.0%) have expected count less than 5. The minimum expected count is .04.

INCOME * POSTOFF

4.00

5.00 6

12 14 2

Total 2

1 1 4

40 1 24 26 8 1 100

Crosstab Count 1.00 INCOME

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

2.00 21 1 13 11 6

Total

POSTOFF 3.00 9

6 5 1 21

4.00

5.00

Total 1

3 8 1

2 2 1

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 15.552a 18.838 100

df 20 20

Asymp. Sig. (2-sided) .744 .532

a. 21 cells (70.0%) have expected count less than 5. The minimum expected count is .01.

INCOME * GOLD Crosstab Count 1.00 INCOME

Total

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

2.00 10

12 10 6

GOLD 3.00 17 6 6 2 1 32

4.00

5.00

Total

4 1 5 6

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 30.075a 33.869 100

df 20 20

Asymp. Sig. (2-sided) .069 .027

a. 22 cells (73.3%) have expected count less than 5. The minimum expected count is .02.

INCOME * MUTUAL Crosstab Count 1.00 INCOME

2.00

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

8 5 6 1

5 6

MUTUAL 3.00 10

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 29.856a 34.323 100

df 20 20

Asymp. Sig. (2-sided) .072 .024

a. 22 cells (73.3%) have expected count less than 5. The minimum expected count is .12.

INCOME * REALESTA

9 7 4 1 31

4.00

5.00 15 2 5 3 25

Total 7 1 3 2

40 1 24 26 8 1 100

Crosstab Count 1.00 INCOME

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

2.00 13 6 4 4 1 28

Total

REALESTA 3.00 8 13 1 5 8 5 11 3 18

4.00

5.00

Total

4 6

1 1

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 16.693a 20.142 100

df 20 20

Asymp. Sig. (2-sided) .673 .449

a. 22 cells (73.3%) have expected count less than 5. The minimum expected count is .05.

INCOME * INSURANC Crosstab Count 1.00 INCOME

Total

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

INSURANC 2.00 3.00 10 15

6 7 1

7 5 2

8 9 3

4.00

5.00 7 1 3 5 1 1 18

Total 2

1 3

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 16.404a 14.552 100

df 20 20

Asymp. Sig. (2-sided) .691 .801

a. 21 cells (70.0%) have expected count less than 5. The minimum expected count is .03.

Factor Analysis Communalities SHAREMKT BANK POSTOFF GOLD MUTUAL REALESTA INSURANC

Initial 1.000 1.000 1.000 1.000 1.000 1.000 1.000

Extraction .878 .604 .722 .509 .782 .787 .669

Extraction Method: Principal Component Analysis.

Total Variance Explained

Component 1 2 3 4 5 6 7

Total 1.495 1.316 1.106 1.036 .828 .678 .542

Initial Eigenvalues % of Variance Cumulative % 21.352 21.352 18.794 40.146 15.800 55.946 14.794 70.739 11.828 82.567 9.689 92.256 7.744 100.000

Extraction Method: Principal Component Analysis.

Extraction Sums of Squared Loadings Total % of Variance Cumulative % 1.495 21.352 21.352 1.316 18.794 40.146 1.106 15.800 55.946 1.036 14.794 70.739

Scree Plot 1.6

1.4

1.2

1.0

Eigenvalue

.4 1

Component Number

Component Matrixa Component 1 SHAREMKT BANK POSTOFF GOLD MUTUAL REALESTA INSURANC

.145 .646 .188 -.354 -.596 .346 .649

.201 -3.97E-03 .776 .563 -.261 -.530 8.351E-02

.589 -.368 .150 8.341E-02 -.286 .620 -.357

.685 .228 -.248 .244 .526 -5.22E-02 .337

Extraction Method: Principal Component Analysis. a. 4 components extracted.

Proximities

Case Processing Summarya

Valid Percent 100 99.0%

Cases Missing N Percent 1 1.0%

a. Squared Euclidean Distance used

Cluster Ward Linkage

Total N 101

Percent 100.0%

Agglomeration Schedule

Stage 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45

Cluster Combined Cluster 1 Cluster 2 83 98 8 73 49 91 85 89 54 62 93 94 37 39 60 63 24 55 49 92 95 97 11 51 86 88 14 16 44 45 34 41 28 52 3 30 53 59 85 87 50 80 20 76 38 40 54 99 23 31 44 47 46 96 29 67 6 82 3 37 18 20 21 48 8 75 5 58 83 95 1 2 53 71 68 70 4 24 13 72 60 64 26 57 22 93 9 61 77 81

Coefficients .398 .795 1.296 1.809 2.515 3.258 4.017 4.833 5.649 6.499 7.357 8.230 9.104 10.014 11.027 12.040 13.202 14.363 15.542 16.724 17.943 19.214 20.486 21.811 23.165 24.522 25.898 27.284 28.717 30.155 31.598 33.044 34.527 36.086 37.716 39.349 41.032 42.774 44.705 46.656 48.631 50.667 52.763 54.903 57.067

Stage Cluster First Appears Cluster 1 Cluster 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 5 0 0 0 15 0 0 0 0 0 0 0 18 7 0 22 0 0 2 0 0 0 1 11 0 0 19 0 0 0 0 9 0 0 8 0 0 0 0 6 0 0 0 0

Next Stage 35 33 10 20 24 43 30 41 39 66 35 50 56 77 26 49 55 30 37 54 63 31 70 58 68 69 71 79 62 70 61 61 78 50 81 77 65 59 85 73 65 48 66 53 69

25:male 92:female 91:male 49:female 94:male 93:male 22:male 78:male 75:female 73:female 8:male 79:female 35:male 36:male 33:female 10:male 84:female 82:male 6:male 80:female 50:male 32:female 31:female 23:male 64:male 63:male 60:male 71:female 59:female 53:female 51:male 11:male 58:male 5:female 90:female 100:female 88:male 86:female

Number of clusters 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X X X

Dendrogram * * * * * * H I E R A R C H I C A L * *

C L U S T E R

A N A L Y S I S * * * *

Dendrogram using Ward Method Rescaled Distance Cluster Combine C A S E

Label +---------+ male female female male female male female male female male male male male male female male male female female male female female female

Num 83 98 95 97 44 45 47 77 81 46 96 26 57 12 15 19 17 20 76 18 21 48 14

male

female male male

68 70 69

+---------+---------+---------+---------

male

female

male

_ * * * * * * H I E R A R C H I C A L * * C A S E

25 Label +---------+

0 Num

C L U S T E R

A N A L Y S I S * * * *

+---------+---------+---------+---------

female

male

female

male

female

male

female

male

female

male

female

male female female male male female male female female female male male male female male male male female

50 80 32 11 51 5 58 53 59 71 60 63 64 85 89 87 7 86

male female female

88 100 90

* * * * * * H I E R A R C H I C A L * * C A S E

Label +---------+ female female female female female female male female male female male female female

Num 38 40 37 39 3 30 42 43 13 72 34 41 74

C L U S T E R

A N A L Y S I S * * * *

+---------+---------+---------+---------

INTEPRETATION OF SPSS OUTPUT :

BEST INSURANCE COMPANY TO INVEST

Crosstabs

Case Processing Summary

N GENDER * SBI GENDER * ICICI GENDER * LIC GENDER * BAJAJ GENDER * HDFC GENDER * RELIANCE GENDER * TATAAIG AGE * SBI AGE * ICICI AGE * LIC AGE * BAJAJ AGE * HDFC AGE * RELIANCE AGE * TATAAIG OCCUPATI * SBI OCCUPATI * ICICI OCCUPATI * LIC OCCUPATI * BAJAJ OCCUPATI * HDFC OCCUPATI * RELIANCE OCCUPATI * TATAAIG INCOME * SBI INCOME * ICICI INCOME * LIC INCOME * BAJAJ INCOME * HDFC INCOME * RELIANCE INCOME * TATAAIG

GENDER * SBI

Total N 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101

Crosstab Count 1.00 GENDER

female male

5 11 16

Total

SBI 3.00

2.00 4 12 16

4.00 23 18 41

5.00 9 11 20

Total 3 4 7

44 56 100

Chi-Square Tests Value 5.847a 6.003 100

Pearson Chi-Square Likelihood Ratio N of Valid Cases

df 4 4

Asymp. Sig. (2-sided) .211 .199

a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 3.08.

GENDER * ICICI Crosstab Count 1.00 GENDER

female male

Total

ICICI 3.00

2.00 10 11 21

7 16 23

4.00 23 21 44

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 3.606a 3.672 100

df 4 4

Asymp. Sig. (2-sided) .462 .452

a. 3 cells (30.0%) have expected count less than 5. The minimum expected count is 1.32.

GENDER * LIC

5.00 3 6 9

Total 1 2 3

44 56 100

Crosstab Count 1.00 GENDER

female male

22 37 59

Total

LIC 3.00

2.00 12 6 18

4.00 9 8 17

5.00 1 4 5

Total 1 1

44 56 100

Chi-Square Tests Value 7.338a 7.824 100

Pearson Chi-Square Likelihood Ratio N of Valid Cases

df 4 4

Asymp. Sig. (2-sided) .119 .098

a. 4 cells (40.0%) have expected count less than 5. The minimum expected count is .44.

GENDER * BAJAJ Crosstab Count 1.00 GENDER

female male

2.00 13 10 23

Total

13 23 36

BAJAJ 3.00 15 16 31

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 3.816a 3.889 100

df 4 4

Asymp. Sig. (2-sided) .431 .421

a. 4 cells (40.0%) have expected count less than 5. The minimum expected count is .88.

GENDER * HDFC

4.00

5.00 2 6 8

Total 1 1 2

44 56 100

Crosstab Count 1.00 GENDER

female male

2.00 4 7 11

Total

9 11 20

HDFC 3.00 14 14 28

4.00

5.00 12 10 22

Total 5 14 19

44 56 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 4.082a 4.206 100

df 4 4

Asymp. Sig. (2-sided) .395 .379

a. 1 cells (10.0%) have expected count less than 5. The minimum expected count is 4.84.

GENDER * RELIANCE Crosstab Count 1.00 GENDER

female male

2.00 11 17 28

Total

8 10 18

RELIANCE 3.00 14 20 34

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 1.433a 1.426 100

df 4 4

Asymp. Sig. (2-sided) .838 .840

a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 2.64.

GENDER * TATAAIG

4.00

5.00 8 6 14

Total 3 3 6

44 56 100

Crosstab Count 1.00 GENDER

female male

8 11 19

Total

TATAAIG 3.00 15 16 31

2.00 10 9 19

4.00

5.00 7 12 19

Total 4 8 12

44 56 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 1.794a 1.808 100

df 4 4

Asymp. Sig. (2-sided) .774 .771

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5.28.

AGE * SBI Crosstab Count 1.00 AGE

Total

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

SBI 3.00

2.00 1 9 5 1 16

1 6 4 1 3 1 16

4.00

5.00

8 16 11

5 7 3

4 2 41

3 2 20

Total 5 1 1 7

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 17.399a 17.846 100

df 20 20

Asymp. Sig. (2-sided) .627 .598

a. 24 cells (80.0%) have expected count less than 5. The minimum expected count is .07.

AGE * ICICI Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

Total

ICICI 3.00

2.00

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Total

4 17 8

1 6 2

2 1

10 5 44

df 20 20

Asymp. Sig. (2-sided) .047 .014

a. 22 cells (73.3%) have expected count less than 5. The minimum expected count is .03.

AGE * LIC

5.00

4 14 5

Chi-Square Tests Value 31.680a 36.394 100

4.00

6 4 8 1 2

15 43 24 1 12 5 100

Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

3 29 15 1 7 4 59

Total

LIC 3.00

2.00

4.00

5.00

4 5 6

6 8 2

1 1 1

1 1 5

Total 1

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 25.060a 24.716 100

df 20 20

Asymp. Sig. (2-sided) .199 .213

a. 24 cells (80.0%) have expected count less than 5. The minimum expected count is .01.

AGE * BAJAJ Crosstab Count 1.00 AGE

Total

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

BAJAJ 3.00

2.00 9 8 2

3 14 17

3 15 4

1 1 36

6 3 31

4.00

5.00 4 1 1 1 1 8

Total 2

15 43 24 1 12 5 100

Chi-Square Tests Value 47.349a 41.231 100

Pearson Chi-Square Likelihood Ratio N of Valid Cases

df 20 20

Asymp. Sig. (2-sided) .001 .003

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .02.

AGE * HDFC Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

Total

HDFC 3.00

2.00

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Total

4 11 7

3 12 6

4 4 11

5 1 28

12 5 1 1

df 20 20

Asymp. Sig. (2-sided) .000 .001

a. 24 cells (80.0%) have expected count less than 5. The minimum expected count is .11.

AGE * RELIANCE

5.00

7 7 5

Chi-Square Tests Value 53.326a 44.374 100

4.00

1 1 1

15 43 24 1 12 5 100

Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

Total

2.00 6 11 6

2 9 5

4 1 28

2 18

RELIANCE 3.00 7 12 8 1 4 2 34

4.00

5.00

Total

7 4

4 1

2 1 14

1 6

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 12.497a 16.453 100

df 20 20

Asymp. Sig. (2-sided) .898 .688

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .06.

AGE * TATAAIG Crosstab Count 1.00 AGE

Total

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

2.00 1 6 10

5 9 4

TATAAIG 3.00 5 15 3 6 2 31

4.00

5.00 4 8 1 1 3 2 19

Total 5 6

1 12

15 43 24 1 12 5 100

Chi-Square Tests Value 32.898a 36.422 100

Pearson Chi-Square Likelihood Ratio N of Valid Cases

df 20 20

Asymp. Sig. (2-sided) .035 .014

a. 24 cells (80.0%) have expected count less than 5. The minimum expected count is .12.

OCCUPATI * SBI Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

Total

SBI 3.00

2.00 12

7 2 3 3 1 16

3 1 16

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 15.064a 16.734 100

df 16 16

Asymp. Sig. (2-sided) .520 .403

a. 19 cells (76.0%) have expected count less than 5. The minimum expected count is .07.

OCCUPATI * ICICI

4.00

5.00

Total

22 10 5 4

10 4 4 2

1 1

56 16 16 11 1 100

Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

11 6 1 2 1 21

Total

ICICI 3.00

2.00

4.00

5.00

Total

15 3 5

21 6 8 9

7 1 1

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 18.916a 21.905 100

df 16 16

Asymp. Sig. (2-sided) .273 .146

a. 19 cells (76.0%) have expected count less than 5. The minimum expected count is .03.

OCCUPATI * LIC Crosstab Count 1.00 OCCUPATI

Total

professional retired self employed student Student

LIC 3.00

2.00 39 5 7 7 1 59

4.00

9 4 2 3

8 5 4

5.00

Total

2 2 1

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 22.509a 24.712 100

df 16 16

Asymp. Sig. (2-sided) .128 .075

a. 19 cells (76.0%) have expected count less than 5. The minimum expected count is .01.

OCCUPATI * BAJAJ Crosstab Count

9 9 1 4

23 2 10 1

BAJAJ 3.00 18 4 4 5

1.00 OCCUPATI

professional retired self employed student Student

Total

2.00

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 34.232a 28.237 100

df 16 16

Asymp. Sig. (2-sided) .005 .030

a. 20 cells (80.0%) have expected count less than 5. The minimum expected count is .02.

OCCUPATI * HDFC

4.00

5.00 4 1 1 1 1 8

Total 2

56 16 16 11 1 100

Crosstab Count

3 4 4

11 7 1 1

HDFC 3.00 15 3 6 4

1.00 OCCUPATI

professional retired self employed student Student

Total

2.00

4.00

5.00 17 3 1 1

Total 13 4 1 1 19

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 37.500a 42.808 100

df 16 16

Asymp. Sig. (2-sided) .002 .000

a. 20 cells (80.0%) have expected count less than 5. The minimum expected count is .11.

OCCUPATI * RELIANCE Crosstab Count 1.00 OCCUPATI

Total

professional retired self employed student Student

2.00 14 6 4 4

14 1 2 1

RELIANCE 3.00 14 8 7 4 1 34

4.00

5.00

Total

10 1 1 2

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 14.447a 16.578 100

df 16 16

Asymp. Sig. (2-sided) .565 .413

a. 19 cells (76.0%) have expected count less than 5. The minimum expected count is .06.

OCCUPATI * TATAAIG Crosstab Count

3 1

9 5 4 1

TATAAIG 3.00 17 7 1 6

1.00 OCCUPATI

professional retired self employed student Student

Total

2.00 15

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 23.540a 27.809 100

df 16 16

Asymp. Sig. (2-sided) .100 .033

a. 20 cells (80.0%) have expected count less than 5. The minimum expected count is .12.

INCOME * SBI

4.00

5.00 7 3 5 3 1 19

Total 8 1 3

56 16 16 11 1 100

Crosstab Count 1.00 INCOME

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

SBI 3.00

2.00

4.00

5.00

Total

4 3 2

7 1 2 4 2

12 12 2

1 3

5 4 2 1 20

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 14.652a 12.931 100

df 20 20

Asymp. Sig. (2-sided) .796 .880

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .07.

INCOME * ICICI Crosstab Count 1.00 INCOME

Total

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

ICICI 3.00

2.00

4.00

5.00

5 1 3 7 5

6 5

12 14 2 1 44

Total 2

1 9

40 1 24 26 8 1 100

Chi-Square Tests Value 28.363a 31.099 100

Pearson Chi-Square Likelihood Ratio N of Valid Cases

df 20 20

Asymp. Sig. (2-sided) .101 .054

a. 21 cells (70.0%) have expected count less than 5. The minimum expected count is .03.

INCOME * LIC Crosstab Count 1.00 INCOME

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

LIC 3.00

2.00 24 1 15 13 6 59

5 5

2 6 1

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 108.836a 23.586 100

df 20 20

Asymp. Sig. (2-sided) .000 .261

a. 25 cells (83.3%) have expected count less than 5. The minimum expected count is .01.

INCOME * BAJAJ

4.00

5.00

Total

2 2 1 5

1 1

40 1 24 26 8 1 100

Crosstab Count 1.00 INCOME

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

2.00 10

1 8 4

12 10 4

BAJAJ 3.00 17

4.00

5.00

Total 1

7 6

2 1 3 2

1 31

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 31.578a 29.943 100

df 20 20

Asymp. Sig. (2-sided) .048 .071

a. 21 cells (70.0%) have expected count less than 5. The minimum expected count is .02.

INCOME * HDFC Crosstab Count 1.00 INCOME

Total

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

HDFC 3.00

2.00

4.00

5.00

Total

5 6

4 6

3 5 3

9 7 2 1 28

10 1 3 2 3

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 28.251a 32.997 100

df 20 20

Asymp. Sig. (2-sided) .104 .034

a. 21 cells (70.0%) have expected count less than 5. The minimum expected count is .11.

INCOME * RELIANCE Crosstab Count 1.00 INCOME

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

2.00 12

7 4 4 1 28

5 5

RELIANCE 3.00 12 1 7 11 3

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 15.254a 19.139 100

df 20 20

Asymp. Sig. (2-sided) .762 .513

a. 22 cells (73.3%) have expected count less than 5. The minimum expected count is .06.

INCOME * TATAAIG

4.00

5.00

Total

3 6

2 1

40 1 24 26 8 1 100

Crosstab Count

TATAAIG 3.00 13

5 7 1

4 5 2

6 9 3

1.00 INCOME

2.00

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 15.988a 16.895 100

df 20 20

Asymp. Sig. (2-sided) .717 .660

a. 24 cells (80.0%) have expected count less than 5. The minimum expected count is .12.

4.00

5.00 7 1 4 5 1 1 19

Total 6 5 1 12

40 1 24 26 8 1 100

Communalities SBI ICICI LIC BAJAJ HDFC RELIANCE TATAAIG

Factor

Analysis

Initial 1.000 1.000 1.000 1.000 1.000 1.000 1.000

Extraction .794 .591 .630 .874 .582 .609 .541

Extraction Method: Principal Component Analysis.

Total Variance Explained

Component 1 2 3 4 5 6 7

Total 1.297 1.264 1.055 1.005 .869 .817 .694

Initial Eigenvalues % of Variance Cumulative % 18.530 18.530 18.051 36.581 15.072 51.653 14.352 66.005 12.412 78.417 11.672 90.089 9.911 100.000

Extraction Method: Principal Component Analysis. Component Matrixa Component SBI ICICI LIC BAJAJ HDFC RELIANCE TATAAIG

1 -.333 .563 -.613 .205 -.390 .537 .106

2 .409 .466 .496 .166 -.482 -.196 .578

3 .714 .223 8.268E-02 -6.49E-02 .165 .531 -.419

Extraction Method: Principal Component Analysis. a. 4 components extracted.

4 8.290E-02 -8.27E-02 -4.25E-02 .894 .412 2.015E-02 .138

Extraction Sums of Squared Loadings Total % of Variance Cumulative % 1.297 18.530 18.530 1.264 18.051 36.581 1.055 15.072 51.653 1.005 14.352 66.005

REASONS FOR PEOPLE PREFERRING INSURANCE

Crosstabs

Case Processing Summary

N GENDER * LIFECOVE GENDER * TAXBENEF GENDER * SWITCHOV GENDER * WITHDRWA GENDER * RIDERS GENDER * RETURNS AGE * LIFECOVE AGE * TAXBENEF AGE * SWITCHOV AGE * WITHDRWA AGE * RIDERS AGE * RETURNS OCCUPATI * LIFECOVE OCCUPATI * TAXBENEF OCCUPATI * SWITCHOV OCCUPATI * WITHDRWA OCCUPATI * RIDERS OCCUPATI * RETURNS INCOME * LIFECOVE INCOME * TAXBENEF INCOME * SWITCHOV INCOME * WITHDRWA INCOME * RIDERS INCOME * RETURNS PREMFLEX * LIFECOVE PREMFLEX * TAXBENEF PREMFLEX * SWITCHOV PREMFLEX * WITHDRWA PREMFLEX * RIDERS PREMFLEX * RETURNS

Total N 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101

GENDER * LIFECOVE Crosstab Count 1.00 GENDER

female male

2.00 15 15 30

Total

5 13 18

LIFECOVE 3.00 22 21 43

4.00

5.00 1 5 6

Total 1 2 3

44 56 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 5.214a 5.514 100

df 4 4

Asymp. Sig. (2-sided) .266 .239

a. 4 cells (40.0%) have expected count less than 5. The minimum expected count is 1.32.

GENDER * TAXBENEF Crosstab Count 1.00 GENDER

female male

Total

18 34 52

TAXBENEF 2.00 3.00 14 11 7 10 21 21

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 8.791a 9.300 100

df 4 4

Asymp. Sig. (2-sided) .067 .054

a. 4 cells (40.0%) have expected count less than 5. The minimum expected count is .44.

4.00

5.00 1 4 5

Total 1 1

44 56 100

GENDER * SWITCHOV Crosstab Count 1.00 GENDER

female male

4 4 8

Total

SWITCHOV 2.00 3.00 8 12 18 15 26 27

4.00

5.00 16 11 27

Total 4 8 12

44 56 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 5.072a 5.128 100

df 4 4

Asymp. Sig. (2-sided) .280 .274

a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 3.52.

GENDER * WITHDRWA Crosstab Count 1.00 GENDER Total

female male

4 8 12

WITHDRWA 2.00 3.00 10 16 9 14 19 30

4.00

5.00 12 14 26

Total 2 11 13

44 56 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 6.558a 7.115 100

df 4 4

Asymp. Sig. (2-sided) .161 .130

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5.28.

GENDER * RIDERS Crosstab Count 1.00 GENDER

female male

2.00 11 15 26

Total

6 10 16

RIDERS 3.00 13 20 33

4.00

5.00 5 4 9

Total 9 7 16

44 56 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 2.051a 2.043 100

df 4 4

Asymp. Sig. (2-sided) .726 .728

a. 1 cells (10.0%) have expected count less than 5. The minimum expected count is 3.96.

GENDER * RETURNS Crosstab Count 1.00 GENDER Total

female male

2.00 13 19 32

14 11 25

RETURNS 3.00 12 14 26

4.00

5.00 4 9 13

Total 1 3 4

44 56 100

Chi-Square Tests Value 3.168a 3.223 100

Pearson Chi-Square Likelihood Ratio N of Valid Cases

df 4 4

Asymp. Sig. (2-sided) .530 .521

a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 1.76.

AGE * LIFECOVE Crosstab Count

8 7 12 1 2

3 12 3

LIFECOVE 3.00 3 17 8

10 5 43

1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

Total

2.00

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 39.061a 43.954 100

df 20 20

Asymp. Sig. (2-sided) .007 .002

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .03.

AGE * TAXBENEF

4.00

5.00

Total

1 1 1

15 43 24 1 12 5 100

Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

2.00 3 27 13 1 5 3 52

Total

TAXBENEF 3.00 6 6 6 8 6 3 3 21

4.00

5.00 1 2

3 1 21

Total 1

1 1 5

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 19.435a 21.052 100

Asymp. Sig. (2-sided) .494 .394

df 20 20

a. 22 cells (73.3%) have expected count less than 5. The minimum expected count is .01.

AGE

SWITCHOV

Crosstab Count 1.00 AGE

Total

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

2 4 2

SWITCHOV 2.00 3.00 5 4 9 17 11 1 1

4 1 27

4.00

5.00 4 9 5 1 7 1 27

Total 4 5

3 12

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 39.246a 41.068 100

df 20 20

Asymp. Sig. (2-sided) .006 .004

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .08.

AGE

WITHDRWA Crosstab

Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

2.00 1 1 2 4 4 12

Total

WITHDRWA 3.00 7 3 6 12 5 9 1

4.00

5 1 30

5.00 4 15 6

Total

9 2 1 1

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 53.883a 44.164 100

df 20 20

Asymp. Sig. (2-sided) .000 .001

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .12.

AGE * RIDERS Crosstab Count 1.00 AGE

Total

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

2.00 6 12 4

2 9 4

3 1 26

1 16

RIDERS 3.00 7 13 7 1 3 2 33

4.00

5.00

Total

4 3

5 6

1 1 9

4 1 16

15 43 24 1 12 5 100

Chi-Square Tests Value 16.220a 20.005 100

Pearson Chi-Square Likelihood Ratio N of Valid Cases

df 20 20

Asymp. Sig. (2-sided) .703 .458

a. 24 cells (80.0%) have expected count less than 5. The minimum expected count is .09.

AGE * RETURNS Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

Total

2.00 2 13 11

4 9 7 1 3 1 25

6 32

RETURNS 3.00 3 14 5

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 23.340a 26.149 100

df 20 20

Asymp. Sig. (2-sided) .272 .161

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .04.

OCCUPATI * LIFECOVE

2 2 26

4.00

5.00 5 5

1 2 13

Total 1 2 1

15 43 24 1 12 5 100

Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

2.00 16 7 4 2 1 30

Total

12 3 3

LIFECOVE 3.00 21 6 7 9

4.00

5.00 6

Total 1 2

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 21.297a 23.401 100

df 16 16

Asymp. Sig. (2-sided) .167 .103

a. 20 cells (80.0%) have expected count less than 5. The minimum expected count is .03.

OCCUPATI * TAXBENEF Crosstab Count 1.00 OCCUPATI

Total

professional retired self employed student Student

2.00 36 5 5 5 1 52

10 5 3 3 21

TAXBENEF 3.00 9 5 5 2 21

4.00

5.00

Total 1

1 3 1 5

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 18.932a 19.961 100

df 16 16

Asymp. Sig. (2-sided) .272 .222

a. 19 cells (76.0%) have expected count less than 5. The minimum expected count is .01.

OCCUPATI * SWITCHOV Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

Total

2.00 5 2 1

13 4 8 1

SWITCHOV 3.00 18 3 3 3

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 19.429a 20.024 100

df 16 16

Asymp. Sig. (2-sided) .247 .219

a. 21 cells (84.0%) have expected count less than 5. The minimum expected count is .08.

OCCUPATI * WITHDRWA

4.00

5.00 12 5 2 7 1 27

Total 8 2 2

56 16 16 11 1 100

Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

Total

2.00 3 5 4

10 7 1 1

WITHDRWA 3.00 16 2 8 4

4.00

5.00 20 4 1 1

Total 10 1 1 1 13

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 44.924a 48.186 100

df 16 16

Asymp. Sig. (2-sided) .000 .000

a. 20 cells (80.0%) have expected count less than 5. The minimum expected count is .12.

OCCUPATI * RIDERS Crosstab Count 1.00 OCCUPATI

Total

professional retired self employed student Student

2.00 14 6 3 3

13 1 2

RIDERS 3.00 14 8 7 3 1 33

4.00

5.00

Total

5 1 2 1

2 4

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 17.014a 20.629 100

df 16 16

Asymp. Sig. (2-sided) .385 .193

a. 18 cells (72.0%) have expected count less than 5. The minimum expected count is .09.

OCCUPATI * RETURNS Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

Total

2.00 22 1 4 5

9 5 7 3 1 25

RETURNS 3.00 18 5 1 2

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 19.955a 22.183 100

df 16 16

Asymp. Sig. (2-sided) .222 .137

a. 19 cells (76.0%) have expected count less than 5. The minimum expected count is .04.

INCOME * LIFECOVE

4.00

5.00

Total

5 4 3 1

2 1 1

56 16 16 11 1 100

Crosstab Count 1.00 INCOME

2.00

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

7 1 9 8 5

LIFECOVE 3.00 15

3 4

4.00

5.00 1

1 1 3

12 14 2 43

Total

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 58.658a 36.644 100

df 20 20

Asymp. Sig. (2-sided) .000 .013

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .03.

INCOME * TAXBENEF Crosstab Count 1.00 INCOME

Total

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

21 1 13 11 6 52

TAXBENEF 2.00 3.00 9 9 6 5 1 21

4.00

5.00

Total 1

3 8 1

2 2 1

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 15.552a 18.838 100

df 20 20

Asymp. Sig. (2-sided) .744 .532

a. 21 cells (70.0%) have expected count less than 5. The minimum expected count is .01.

INCOME * SWITCHOV Crosstab Count 1.00 INCOME

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

2.00 5

SWITCHOV 3.00 6 18

10 5 5

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 36.758a 37.679 100

df 20 20

Asymp. Sig. (2-sided) .013 .010

a. 21 cells (70.0%) have expected count less than 5. The minimum expected count is .08.

INCOME * WITHDRWA

3 4 1 1 27

4.00

5.00

Total

7 1 5 12 2

6 2

40 1 24 26 8 1 100

Crosstab Count 1.00 INCOME

2.00

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

WITHDRWA 3.00 8 10

5 6 1

5 6

4.00

5.00 15

9 7 3 1 30

Total 7 1 3 2

2 5 4 26

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 30.250a 34.681 100

df 20 20

Asymp. Sig. (2-sided) .066 .022

a. 22 cells (73.3%) have expected count less than 5. The minimum expected count is .12.

INCOME * RIDERS Crosstab Count 1.00 INCOME

Total

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

2.00 12

6 3 4 1 26

5 3

RIDERS 3.00 13 1 7 9 3 33

4.00

5.00

Total

3 3

3 8 1

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 17.551a 19.078 100

df 20 20

Asymp. Sig. (2-sided) .617 .517

a. 22 cells (73.3%) have expected count less than 5. The minimum expected count is .09.

INCOME * RETURNS Crosstab Count 1.00 INCOME

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

2.00 11 8 11 2

8 1 6 8 2

RETURNS 3.00 13

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 16.091a 13.796 100

df 20 20

Asymp. Sig. (2-sided) .711 .841

a. 20 cells (66.7%) have expected count less than 5. The minimum expected count is .04.

6 5 2 26

4.00

5.00

Total

3 2 1 1 13

1 1 4

40 1 24 26 8 1 100

Communalities PREMFLEX LIFECOVE TAXBENEF SWITCHOV WITHDRWA RIDERS RETURNS

Factor

Analysis

Initial 1.000 1.000 1.000 1.000 1.000 1.000 1.000

Extraction .946 .238 .616 .724 .786 .849 .687

Extraction Method: Principal Component Analysis.

Total Variance Explained

Component 1 2 3 4 5 6 7

Total 1.476 1.236 1.122 1.013 .958 .701 .495

Initial Eigenvalues % of Variance Cumulative % 21.081 21.081 17.660 38.742 16.023 54.765 14.468 69.233 13.688 82.921 10.012 92.933 7.067 100.000

Extraction Sums of Squared Loadings Total % of Variance Cumulative % 1.476 21.081 21.081 1.236 17.660 38.742 1.122 16.023 54.765 1.013 14.468 69.233

Extraction Method: Principal Component Analysis. Component Matrixa Component 1 PREMFLEX LIFECOVE TAXBENEF SWITCHOV WITHDRWA RIDERS RETURNS

.180 .470 .631 2.851E-02 -.662 -.128 .606

2 3.948E-02 1.515E-02 -1.82E-02 .635 -.475 .658 -.415

.236 -2.42E-02 .441 .561 .263 -.589 -.374

.925 .125 -.149 -7.59E-02 .229 .230 8.572E-02

Extraction Method: Principal Component Analysis. a. 4 components extracted.

REASONS FOR PEOPLE PREFERRING MUTUAL FUNDS

Crosstabs Case Processing Summary

GENDER * RETURNS GENDER * LOWASSET GENDER * LIQUIDIT GENDER * EASEPROC GENDER * LOWCHARG AGE * RETURNS AGE * LOWASSET AGE * LIQUIDIT AGE * EASEPROC AGE * LOWCHARG OCCUPATI * RETURNS OCCUPATI * LOWASSET OCCUPATI * LIQUIDIT OCCUPATI * EASEPROC OCCUPATI * LOWCHARG INCOME * RETURNS INCOME * LOWASSET INCOME * LIQUIDIT INCOME * EASEPROC INCOME * LOWCHARG

GENDER * RETURNS

Valid N Percent 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0%

Cases Missing N Percent 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0%

Total N 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101

Percent 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Crosstab Count 1.00 GENDER

female male

2.00 9 15 24

Total

6 12 18

RETURNS 3.00 17 16 33

4.00

5.00 10 9 19

Total 2 4 6

44 56 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 2.851a 2.874 100

df 4 4

Asymp. Sig. (2-sided) .583 .579

a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 2.64.

GENDER * LOWASSET Crosstab Count 1.00 GENDER

female male

Total

2.00 3 3 6

LOWASSET 3.00 8 18 14 12 22 30

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 5.326a 5.375 100

df 4 4

Asymp. Sig. (2-sided) .255 .251

a. 3 cells (30.0%) have expected count less than 5. The minimum expected count is 2.64.

4.00

5.00 3 8 11

Total 12 19 31

44 56 100

GENDER

LIQUIDIT

Crosstab Count 1.00 GENDER

female male

2.00 18 34 52

Total

14 7 21

LIQUIDIT 3.00 11 10 21

4.00

5.00 1 4 5

Total 1 1

44 56 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 8.791a 9.300 100

df 4 4

Asymp. Sig. (2-sided) .067 .054

a. 4 cells (40.0%) have expected count less than 5. The minimum expected count is .44.

GENDER * EASEPROC Crosstab Count 1.00 GENDER

female male

Total

2.00 7 7 14

EASEPROC 3.00 12 13 23 16 35 29

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 4.681a 4.764 100

df 4 4

Asymp. Sig. (2-sided) .322 .312

a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 3.52.

4.00

5.00 6 8 14

Total 6 2 8

44 56 100

GENDER

LOWCHARG

Crosstab Count 1.00 GENDER

female male

2.00 1 3 4

Total

LOWCHARG 3.00 9 13 8 16 17 29

4.00

5.00 13 12 25

Total 8 17 25

44 56 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 3.256a 3.327 100

df 4 4

Asymp. Sig. (2-sided) .516 .505

a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 1.76.

AGE * RETURNS Crosstab Count 1.00 AGE

Total

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

1 10 3

RETURNS 3.00 3 14 10

3 1 18

4 2 33

2.00 6 9 6 1 2 24

4.00

5.00 5 7 3 2 2 19

Total 3 2 1 6

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 15.391a 17.089 100

df 20 20

Asymp. Sig. (2-sided) .754 .647

a. 24 cells (80.0%) have expected count less than 5. The minimum expected count is .06.

AGE * LOWASSET Crosstab Count LOWASSET 2.00 3.00 3 3 13 16 5 5

1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

Total

1 2 2 1

1 22

6 Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 34.390a 34.809 100

df 20 20

Asymp. Sig. (2-sided) .024 .021

a. 24 cells (80.0%) have expected count less than 5. The minimum expected count is .06.

AGE * LIQUIDIT

4 2 30

4.00

5.00 3 1 5 2 11

Total 8 9 11 1 2 31

15 43 24 1 12 5 100

Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

2.00 3 27 13 1 5 3 52

Total

6 6 6

LIQUIDIT 3.00 6 8 3

3 21

4.00

5.00 1 2

3 1 21

Total 1

1 1 5

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 19.435a 21.052 100

df 20 20

Asymp. Sig. (2-sided) .494 .394

a. 22 cells (73.3%) have expected count less than 5. The minimum expected count is .01.

AGE * EASEPROC Crosstab Count 1.00 AGE

Total

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

4 8 2

EASEPROC 2.00 3.00 5 5 12 14 16 4 1 1 35

3 3 29

4.00

5.00 1 7 1 1 3 1 14

Total 2 1 5 8

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 48.180a 41.367 100

df 20 20

Asymp. Sig. (2-sided) .000 .003

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .08.

AGE * LOWCHARG

Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

2.00 1 1

Total

LOWCHARG 3.00 7 4 4 9 5 9

4.00

5.00 3 14 6

5 2 29

Total 15 4 1 3 2 25

1 1 25

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 31.921a 33.380 100

df 20 20

Asymp. Sig. (2-sided) .044 .031

a. 23 cells (76.7%) have expected count less than 5. The minimum expected count is .04.

OCCUPATI * RETURNS Crosstab Count 1.00 OCCUPATI

Total

professional retired self employed student Student

10 2 3 3

RETURNS 3.00 20 4 5 4

2.00 13 5 4 1 1 24

4.00

5.00

Total

9 5 3 2

1 1

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 8.624a 9.320 100

df 16 16

Asymp. Sig. (2-sided) .928 .900

a. 19 cells (76.0%) have expected count less than 5. The minimum expected count is .06.

OCCUPATI * LOWASSET Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

Total

3 1 1 1

LOWASSET 2.00 3.00 13 20 3 5 6 2 3

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 23.665a 21.573 100

df 16 16

Asymp. Sig. (2-sided) .097 .158

a. 21 cells (84.0%) have expected count less than 5. The minimum expected count is .06.

OCCUPATI * LIQUIDIT

4.00

5.00 3 1 2 5 11

Total 17 6 5 2 1 31

56 16 16 11 1 100

Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

36 5 5 5 1 52

Total

10 5 3 3

LIQUIDIT 3.00 9 5 5 2

2.00

4.00

5.00

Total 1

1 3 1 5

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 18.932a 19.961 100

df 16 16

Asymp. Sig. (2-sided) .272 .222

a. 19 cells (76.0%) have expected count less than 5. The minimum expected count is .01.

OCCUPATI * EASEPROC Crosstab Count 1.00 OCCUPATI

Total

professional retired self employed student Student

2.00 9 4 1

20 4 10 1 35

EASEPROC 3.00 16 6 4 3 29

4.00

5.00 7 2 1 3 1 14

Total 4

4 8

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 32.317a 29.065 100

df 16 16

Asymp. Sig. (2-sided) .009 .024

a. 19 cells (76.0%) have expected count less than 5. The minimum expected count is .08.

OCCUPATI * LOWCHARG Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

Total

2.00 1 1 2

8 7 1 1

LOWCHARG 3.00 13 3 9 4

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 30.882a 28.524 100

df 16 16

Asymp. Sig. (2-sided) .014 .027

a. 21 cells (84.0%) have expected count less than 5. The minimum expected count is .04.

INCOME * RETURNS

4.00

5.00 19 3 2 1 25

Total 16 2 3 3 1 25

56 16 16 11 1 100

Crosstab Count 1.00 INCOME

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

2.00 11 1 3 6 3

RETURNS 3.00 13

4 6 2

4.00

10 8 1 1 33

5.00

Total

5 4 2

2 2

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 11.044a 11.787 100

df 20 20

Asymp. Sig. (2-sided) .945 .923

a. 22 cells (73.3%) have expected count less than 5. The minimum expected count is .06.

INCOME * LOWASSET Crosstab Count 1.00 INCOME

Total

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

2.00

LOWASSET 3.00 11 15

4.00

5.00 3

3 1 2

6 5

6 8 1

3 5

Total 11 1 6 7 5 1 31

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 23.939a 26.042 100

df 20 20

Asymp. Sig. (2-sided) .245 .164

a. 21 cells (70.0%) have expected count less than 5. The minimum expected count is .06.

INCOME * LIQUIDITY Crosstab Count 1.00 INCOME

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

2.00 21 1 13 11 6

LIQUIDIT 3.00 9

6 5 1 21

52 Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 15.552a 18.838 100

df 20 20

Asymp. Sig. (2-sided) .744 .532

a. 21 cells (70.0%) have expected count less than 5. The minimum expected count is .01.

INCOME * EASEPROC

4.00

5.00

Total 1

3 8 1

2 2 1

40 1 24 26 8 1 100

Crosstab Count 1.00 INCOME

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

2.00 10

Total

EASEPROC 3.00 8 16

12 9 6

4.00

6 4 2 1 29

5.00

Total

4 1 5 4

1 5

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 35.887a 37.780 100

df 20 20

Asymp. Sig. (2-sided) .016 .009

a. 22 cells (73.3%) have expected count less than 5. The minimum expected count is .08.

INCOME * LOWCHARG Crosstab Count LOWCHARG 2.00 3.00 7 7

1.00 INCOME

Total

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

4 6

10 7 4 1 29

4.00

5.00 14

Total

3 5 3

12 1 7 4 1

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 29.067a 29.769 100

df 20 20

Asymp. Sig. (2-sided) .086 .074

a. 20 cells (66.7%) have expected count less than 5. The minimum expected count is .04.

Factor Analysis Communalities RETURNS LOWASSET LIQUIDIT EASEPROC LOWCHARG

Initial 1.000 1.000 1.000 1.000 1.000

Extraction .766 .621 .733 .628 .746

Extraction Method: Principal Component Analysis. Total Variance Explained

Component 1 2 3 4 5

Total 1.362 1.107 1.025 .920 .586

Initial Eigenvalues % of Variance Cumulative % 27.240 27.240 22.143 49.383 20.499 69.882 18.394 88.276 11.724 100.000

Extraction Method: Principal Component Analysis.

Extraction Sums of Squared Loadings Total % of Variance Cumulative % 1.362 27.240 27.240 1.107 22.143 49.383 1.025 20.499 69.882

Component Matrixa

1 RETURNS LOWASSET LIQUIDIT EASEPROC LOWCHARG

.114 -.101 .831 .164 -.789

Component 2 .204 .583 .196 .765 .321

3 .843 -.521 -6.81E-02 .130 .144

Extraction Method: Principal Component Analysis. a. 3 components extracted.

REASONS FOR PEOPLE NOT PREFERING MUTUAL FUNDS

Crosstabs

Case Processing Summary

N GENDER * ABSRETUR GENDER * EXTRAFEE GENDER * TAXONPRO AGE * ABSRETUR AGE * EXTRAFEE AGE * TAXONPRO OCCUPATI * ABSRETUR OCCUPATI * EXTRAFEE OCCUPATI * TAXONPRO INCOME * ABSRETUR INCOME * EXTRAFEE INCOME * TAXONPRO

Valid Percent 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0% 100 99.0%

Cases Missing N Percent 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0% 1 1.0%

Total N 101 101 101 101 101 101 101 101 101 101 101 101

GENDER * ABSRETUR Crosstab Count 1.00 GENDER

female male

Total

14 19 33

ABSRETUR 2.00 3.00 13 17 23 13 36 30

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 3.682a 4.053 100

df 3 3

Asymp. Sig. (2-sided) .298 .256

a. 2 cells (25.0%) have expected count less than 5. The minimum expected count is .44.

GENDER * EXTRAFEE

4.00

Total 1 1

44 56 100

Percent 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Crosstab Count 1.00 GENDER

female male

3 2 5

Total

EXTRAFEE 2.00 3.00 8 33 15 38 23 71

5.00

Total 1 1

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 2.275a 2.661 100

df 3 3

Asymp. Sig. (2-sided) .517 .447

a. 4 cells (50.0%) have expected count less than 5. The minimum expected count is .44.

GENDER * TAXONPRO Crosstab Count 1.00 GENDER

female male

Total

TAXONPRO 2.00 19 19 35 14 54 33

3.00

Total 6 7 13

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 4.196a 4.207 100

df 2 2

Asymp. Sig. (2-sided) .123 .122

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5.72.

44 56 100

AGE

ABSRETUR

Crosstab Count ABSRETUR 2.00 3.00 4 2 18 11 6 10

1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

9 14 7 1 2

Total

5 3 36

4.00

Total

5 2 30

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 17.186a 18.431 100

df 15 15

Asymp. Sig. (2-sided) .308 .241

a. 17 cells (70.8%) have expected count less than 5. The minimum expected count is .01.

AGE * EXTRAFEE Crosstab Count 1.00 AGE

Total

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

1 1 2 1 5

EXTRAFEE 2.00 3.00 5 9 13 28 4 18 1 11 1 4 23 71

5.00

Total 1

15 43 24 1 12 5 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 9.643a 13.120 100

df 15 15

Asymp. Sig. (2-sided) .842 .593

a. 18 cells (75.0%) have expected count less than 5. The minimum expected count is .01.

AGE * TAXONPRO Crosstab Count 1.00 AGE

45 and above between 22 and 34 between 35 and 44 less 22 less than 22 more than 45

Total

TAXONPRO 2.00 3 8 28 12 13 8 1 5 5 4 54 33

3.00

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 13.825a 16.171 100

df 10 10

Asymp. Sig. (2-sided) .181 .095

a. 11 cells (61.1%) have expected count less than 5. The minimum expected count is .13.

OCCUPATI * ABSRETUR

Total 4 3 3 2 1 13

15 43 24 1 12 5 100

Crosstab Count ABSRETUR 2.00 3.00 21 18 5 4 5 3 5 5

1.00 OCCUPATI

professional retired self employed student Student

17 7 7 1 1 33

Total

4.00

Total

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 12.693a 11.938 100

df 12 12

Asymp. Sig. (2-sided) .392 .451

a. 13 cells (65.0%) have expected count less than 5. The minimum expected count is .01.

OCCUPATI * EXTRAFEE Crosstab Count 1.00 OCCUPATI

Total

professional retired self employed student Student

2 1 1 1 5

EXTRAFEE 2.00 3.00 13 40 5 10 5 10 10 1 23 71

5.00

Total 1

56 16 16 11 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 6.300a 9.283 100

df 12 12

Asymp. Sig. (2-sided) .900 .679

a. 15 cells (75.0%) have expected count less than 5. The minimum expected count is .01.

OCCUPATI * TAXONPRO Crosstab Count 1.00 OCCUPATI

professional retired self employed student Student

Total

37 6 5 5 1 54

TAXONPRO 2.00 14 6 9 4

3.00

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 11.411a 11.390 100

df 8 8

Asymp. Sig. (2-sided) .179 .181

a. 7 cells (46.7%) have expected count less than 5. The minimum expected count is .13.

INCOME * ABSRETUR

Total 5 4 2 2 13

56 16 16 11 1 100

Crosstab Count ABSRETUR 2.00 3.00 16 12

1.00 INCOME

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

12 1 6 10 3 1 33

Total

4.00

Total

8 8 4

9 8 1

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 10.196a 10.427 100

df 15 15

Asymp. Sig. (2-sided) .807 .792

a. 15 cells (62.5%) have expected count less than 5. The minimum expected count is .01.

INCOME * EXTRAFEE Crosstab Count 1.00 INCOME

Total

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

2 1 2 5

EXTRAFEE 2.00 3.00 10 29 1 7 15 4 21 2 4 1 23 71

5.00

Total 1

40 1 24 26 8 1 100

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 13.539a 13.265 100

df 15 15

Asymp. Sig. (2-sided) .561 .582

a. 17 cells (70.8%) have expected count less than 5. The minimum expected count is .01.

INCOME * TAXONPRO Crosstab Count 1.00 INCOME

1.5 to 3 lakh 1.5 to 3lakh 3 to 4.5 lakh less than 1.5 lakh more than 4.5 lakh more than 4.5lakh

Total

TAXONPRO 2.00 22 12 1 14 8 11 11 6 1 1 54 33

3.00

Chi-Square Tests

Pearson Chi-Square Likelihood Ratio N of Valid Cases

Value 6.736a 7.597 100

df 10 10

Asymp. Sig. (2-sided) .750 .668

a. 11 cells (61.1%) have expected count less than 5. The minimum expected count is .13.

Factor Analysis

Total 6 2 4 1 13

40 1 24 26 8 1 100

Communalities ABSRETUR EXTRAFEE TAXONPRO

Initial 1.000 1.000 1.000

Extraction .875 .582 .688

Extraction Method: Principal Component Analysis.

Total Variance Explained

Component 1 2 3

Total 1.140 1.006 .854

Initial Eigenvalues % of Variance Cumulative % 37.986 37.986 33.542 71.528 28.472 100.000

Extraction Method: Principal Component Analysis. Component Matrixa Component 1 ABSRETUR EXTRAFEE TAXONPRO

2 .370 .763 .649

.859 2.324E-02 -.517

Extraction Method: Principal Component Analysis. a. 2 components extracted.

Extraction Sums of Squared Loadings Total % of Variance Cumulative % 1.140 37.986 37.986 1.006 33.542 71.528

ANALYSIS FROM SPSS OUTPUT

CROSS TAB: The cross tab gives a relationship between the independent variables(male and females) and their preference towards dependent variables . The independent variables taken into account are •

Gender : Male , Female

•

Age: Less than 22, Between 22 and 34, Between 35 and 44, 45 and above

•

Occupation: Self employed, Professional, Retired, Students

•

Annual Income: Up to 1.5 lakh, 1.5 to 3 lakh, 3 to 4.5 lakh , more than 4.5 lakh The dependent variables taken into account are •

Best form of investment: Share market, Bank, Post Office Savings ,Gold/Ornaments, Mutual funds, Real estate,Insurance

•

Best insurance company: LIC ,ICICI, SBI,HDFC,BAJAJ,RELIANCE,TATA AIG

•

Reasons for insurance: Flexibility in premium, life cover ,tax benefit, flexibility in withdrawals, riders

•

Reasons for people preferring mutual funds: Quick return, Low cost of asset management, Liquidity, Ease of process, Low administrative charges

•

Reasons for people not preferring mutual funds: Absence of guarantee on returns, Extra fees and commission, tax on profit made

Chi square test: The Chi-Square output shows the relationship between statistics and degrees of freedom. The 1st column shows a significant level of 4.517 for 3 degrees of freedom. In the 1sttest the value of .21 shows that value of .457 or greater occurs only for 21% of sample. The chi square test takes the independent variable in the column and dependent variable in the row and finds the responses of independent variable over the dependent variable

FACTOR ANALYSIS: Suppose if the company wants to identify specific factors which makes the people to prefer insurance rather than mutual funds factor analysis could be used .The factors that favours insurance are listed out and depending upon the people responses factor analysis is done. The various reasons for people to go for insurance are as follows •

Flexibility in premium

•

Life cover

•

Tax benefit

•

No entry/exit load

•

Flexibility in withdrawals

•

Additional riders The various reasons for people to go for mutual funds are as follows •

Quick return

•

Low cost of Asset Management

•

Liquidity

•

Ease of process

•

Low administrative charges The various reasons for the people to avoid mutual funds are as follows •

Absence of guarantee on returns

•

Extra fees and commission made

•

Tax on profit made

CORRELATION MATRIX: Correlation matrix is a matrix that shows the relationship between various variables like age, income , occupation, gender etc. In this matrix you will observe that relationship between two similar variables such as (age – age, income-income, occupationoccupation, gender-gender) (i.e) In all n*n cells the value is found to be 1 and in other cells the value is found to vary depending upon the result of the research KMO AND BARTLETT’S TEST: From the result of KMO and Bartlett’s test it is very clear that we have to accept the null Hypothesis since the significance level is 0. It is lesser than 0.5

Communalities: In communalities there are column .The first column initial gives the initial correlation of the variable over the buying behavior of western wear. The second column extract gives the influence of these variables over the western wear after the research being done. After the research it is found that there is .518 extraction of income over buying behavior of insurance. The extraction method could be explained by the principal of component analysis. TOTAL VARIANCE Explained: In total variance explained there are 3 columns namely initial eigen values, extraction of sum of of squared loadings and rotation sum of squared loadings. It gives the percentage of variance and cumulative percentage of variance. The eigen values whose variance is greater than 1 is taken to the next column of being extracted and taking the 2nd column as reference rotation sum of squared loadings is calculated in the third column SCREE PLOT: The scree plot is the graphical representation showing the relationship between eigen values and component number COMPONENT MATRIX:The component matrix shows the classification of variables into 3 components and shows the extraction level of variables in each component Reproduced correlations: The reproduced correlations are correlations that is made after the final research being done and is computed on the basis of final decision made by the research

Residual correlations: Residual correlations are those correlations that is made between the observed and reproduced correlations 80% of non redundant residuals have an absolute value of greater than 0.05 Component transformation matrix: At last we have the component transformation matrix which shows the loading of variables in 3

extracted factors. Loading less than 0.5 are not shown as the â&#x20AC;&#x153;surpress loading less than 0.5â&#x20AC;? value was entered in factor analysis options dialog box

CLUSTER ANAYSIS: Suppose if we want to analyze the group of people who go for mutual funds or insurance cluster analysis could be done. The clusters could be made among the people of the same kind and be done .For eg analysis could be done by all male professionals within the age group from 22 to 34

AGGLOMERATION SCHEDULE: The Agglomeration schedule defines the order in which the variable combines with each other. It tells the maximum difference between coefficient at each stage.

DENDOGRAM: The dendogram shows clusters in graphical way. It resembles a fork that sub divides in different way. It splits the different types of clusters for easy analysis.

DATA ANALYSIS:

1) Reasons for people preferring insurance

PARTICULARS

FLEXIBILITY PREMIUM

No of respondents rated % OF TOTAL the best SAMPLE

IN 6

LIFE COVER

48%

NO ENTRY/EXIT LOAD

TAX BENEFIT

34%

FLEXIBILITY WITHDRAWALS

IN 3

PROTECTION AGAINST 3 CRITICAL ILLNESS

2) Reasons for people preferring mutual funds PARTICULARS Quick return Low cost management Liquidity Low

No of respondents rated % OF TOTAL SAMPLE the best 52 52% asset 14

14%

14.%

administrative 20

20%

charges 3) Best form of investment

PARTICULARS

No of respondents rated % OF TOTAL SAMPLE the best SHARE MARKET 6 6% BANK 14 14% POST OFFICE 40 40% SAVINGS GOLD/ORNAMENTS 9 9% MUTUAL FUNDS 14 14% REAL ESTATE 5 6% INSURANCE 12 12%

FINDINGS : •

When taking survey I found that 60% of self employed people prefer real estate

•

I also found that 75% of the male between the age group 16 to 34 prefer mutual funds than insurance

•

I found that 60% of female between age group 16 to 34 prefer mutual funds than insurance

•

I found that 20% of male of age group greater than 35 prefer insurance

•

I found that 74% of the people with annual income greater than 3 lakhs prefer insurance than mutual funds

•

I found that 15% of the people with income greater than 3 lakhs prefer mutual funds than insurance

LIMITATIONS :

•

Surveys restricted to only those people who know about insurance and mutual funds

•

Surveys taken only from the people who are willing to disclose their annual income and age

•

Surveys are taken only from the people who are interested Surveys are not taken from the people in slum areas and to the people below the poverty line

RECOMMENDATIONS:

•

SBI Life insurance should give a lot of training to their advisors and encourage the advisors to work as an team to increase their productivity.

•

SBI Life insurance company should recruit a lot of youngsters for promoting their products

•

SBI Life insurance company should do an blue ocean strategy (Targeting those who were unaware about insurance industry ).By this method mass marketing could be done and it will help SBI to increase its customers.

•

Should increase the no of advertisements in T .V, News papers etc and increase people awareness about the additional benefits given by SBI life insurance products

•

SBI Life insurance company should make a best use of this report and the company must analyze the people to be targeted for business and advisors in improving its productivity

QUESTIONNAIRE:

I V.NIRANJAN , a student pursuing MBA programme at IBS Chennai is conducting a study about “ CONSUMER PREFERENCE OF MUTUAL FUNDS VS INSURANCE” The following questions seeks connection with this project.Please fill up this questionnaire with your responses. Any information provided by you will be treated in strict confidence and will not be treated for any other purpose other than the above study V.NIRANJAN

1) Name

2) ADDRESS: 3) GENDER :

4) Age Less than 22 Between 22 and 34 Between 35 and 44 45 and above

Male

Female

5) Occupation:

Self employed Professional Retired Students Any other

6) MOBILE NO: 7) E-mail id: 8) Annual income: Self Upto 1.5 lakh

1.5-3 lakh

3-4.5lakh than

more 4.

5 Spouse Children Total

9) According to you which one is the best for investment? Rate them? 1-5 (1highest 5 lowest) A) Share market B) Bank C) Post office savings D) Gold/Ornaments E) Mutual funds F) Real Estate G) Insurance

10)Please state the percentage of savings investments in the following?

A. Share market B. Bank C. Post office savings D. Gold/Ornaments E. Mutual funds F. Real Estate G. Insurance TOTAL

100%

11) In insurance companies which company do you prefer? Rate them? 1-5 (1highest 5 lowest)

A. LIC B. ICICI C. SBI D. HDFC E. BAJAJ F. Any other

12)Why do you prefer insurance? Rate them? 1-5 (1-highest 5 lowest)

A. Flexibility in premium B. Life cover C. No entry/ exit load D. Tax Benefit E. Flexibility in withdrawals F. Protection against critical illness/accidental benefit

13)Are you aware of mutual funds?

Yes/No

14)If you prefer mutual funds why do you prefer? Rate the reasons? 1-5 (1highest 5 lowest)

A. Quick return B. Low cost of Asset management C. Liquidity D. Ease of process (By internet, phone ) E. Low administrative charges

15)If you donâ&#x20AC;&#x2122;t prefer mutual funds why? Rate the reasons? 1-5 (1-highest 5 lowest)

A. Absence of guarantee on returns B. Extra fees and commission (Entry / exit loads ) C. Tax on profit made

16)Please state your investment for the next one year? A. Share market B. Bank C. Post office savings D. Gold/Ornaments E. Mutual funds F. Real Estate G. Insurance

17)Reasons for the above investment plans? Rate them from (1-5)(1 highest 5 lowest)

A) FLEXIBILITY IN PREMIUM B) LIFE COVER C) TAX BENEFITS D) PROTECTION AGAINST CRITICAL ILLNESS /ACCIDENTAL DEATH E) QUICK RETURN

F) LIQUIDITY G)FREE ENTRY/EXIT LOAD h) LOW ADMINISTRATIVE CHARGES

BIBLIOGRAPHY

www.google.com www.progressive.com www.wikepedia.org/wiki/insurance www.mutualfundsindia.com Business Research Methods, ICFAI Naresh K.Malhotra .Marketing Research An Applied Orientation Insurance for Practice: Moorthy Business Research Methodology, K.Ashwathapa