Ranjan Jaykant Sabhaya 1 and Manisha M. Panwala

Research paper. Sabhaya and Panwala, 2011. Pp. 6-10. A STUDY ON FACTORS AFFECTING TO BUYING DECISION OF LIFE INSURANCE POLICY (With special reference to Surat City of Gujarat in India) Ranjan Jaykant Sabhaya 1 and Manisha M. Panwala 1 SRLIM, VNSGU, Surat. 2 DBIM, VNSGU, Surat. Corresponding Author: mrsrjsabhaya@yahoo.co.in ABSTRACT Aim: To analyse the factor affecting to buying decision of life insurance policy. Methodology: This research is based on the primary data collection method, Hypothesis and some statistical tools to be applied. Results: With a huge population base and large untapped market, insurance industry is a big opportunity area in different cities of India like Surat for national as well as foreign investors. India is the fifth largest life insurance market in the emerging insurance economies globally and is growing at 32-34% annually. Personal Factors and Product factors considered for buying the Life Insurance Policy for Surat Population. Based on this analysis, the paper gives idea to the Insurance Player for consumers preferred factors for buying life insurance policy and a future forecast of the market in India that is intended as a rough guide to the direction in which the market is likely to move. Keywords: Insurance, liberalization, consumers and product factors. INTRODUCTION Insurance in India has its history dating back till 1818, when Oriental Life Insurance Company was started by Europeans in Kolkata to cater to the needs of European community. Pre-independent era in India saw discrimination among the life of foreigners and Indians with higher premiums being charged for the latter. It was only in the year 1870, Bombay Mutual Life Assurance Society, the first Indian insurance company covered Indian lives at normal rates (1). At the dawn of the twentieth century, and insurance companies started mushrooming up. In the year 1912, the Life Insurance Companies Act, and the Provident Fund Act were passed to regulate the insurance business. The Life Insurance Companies Act, 1912 made it necessary that the premium rate tables and periodical valuations of companies should be certified by an actuary. However, the disparage still existed as discrimination between Indian and foreign companies. The oldest existing insurance company in India is National Insurance Company Ltd, which was founded in 1906 and is doing business even today. The Insurance industry earlier consisted of only two state insurers: Life Insurers i.e. Life Insurance Corporation (LIC) and General Insurers i.e. General Insurance Corporation of India (GIC). GIC had four subsidiary companies. With effect from December 2000, these subsidiaries have been de-linked from parent company and made as independent insurance companies: Oriental Insurance Company Limited, New India Assurance Company Limited, National Insurance Company Limited and United India Insurance Company Limited. There are 13 private players in Life Insurance area and 9 Private Players in Non-life Insurance area (2-3). Insurance Regulatory and Development Authority (IRDA) Act, 1999: Till 1999, there were not any private insurance companies in Indian insurance sector. The Govt. of India then introduced the Insurance Regulatory and Development Authority Act in 1999, thereby de-regulating the insurance sector and allowing private companies into the insurance. Further, foreign investment was also allowed and capped at 26% holding in the Indian insurance companies. In recent years many private players entered in the Insurance sector of India. Companies with equal strength are competing in the Indian insurance market. Currently, in India only 2 million people (0.2 % of total population of 1 billion), are covered under Mediclaim, whereas in developed nations like USA about 75 % of the total population are covered under some insurance scheme. With more and more private players in the sector this scenario may change at a rapid pace. However, the studies on factor affecting in Surat are scanty. Generally, it is assumed that other cities factors affecting to buy life insurance policy will affect to Surat city s population. However, it is hypothesized that factors affecting to buy life insurance policy could be different from other cities purchase decision (4-5). RESEARCH OBJECTIVES The objective of this research work is to find out: - Factors affecting to buying decision of Life insurance Policy in Surat city of Gujarat, India. Rising Research Journal Publications 6

- Correlation between Demographical Factors and Life Insurance Policy Investors in Surat City. - Preference to buy of LIC Life Insurance Policy or of Private Players Life Policy. HYPOTHESIS OF THE STUDY Type of Insurance Players and Life Insurance Policy buying Decision. Demographic Factors (Like Age, Gender, Family Income, Occupation and Education Level) and Life Insurance Policy buying Decision. Personal Factors (like Life Style, Policy User Status, Loyalty Status, Attitude towards Life Insurance) and Life Insurance Policy buying Decision. Product Factors (Like Awareness of Policy, Type of Policy, Premium of Policy, No. of Agents and Branches in Surat City) and Life Insurance Policy buying Decision. - There is significance relationship among the all factors. DATA COLLECTION We have collected primary date by using Questionnaire Method and surveyed the Life Insurance Investors in Surat City of Gujarat in India. This included data on different demographic variables like income, gender, education, occupation etc. Other important parameters on which we gathered information is related to Personal Factors like Life Style, Policy User Status, Loyalty Status, Attitude towards Life Insurance and Product Factors like Awareness of Policy, Type of Policy, Premium of Policy, No. of Agents and Branches in Surat City. Some questions related to people s perception about buying health insurance on interval scale data has been used in the questionnaire. These factors were identified during our interview and discussion with policyholders. Customer satisfaction was measured in terms of two variables indicating experience from insurer and experience from the provider. METHODOLOGY We have used statistical technique to find the factors affecting to buy Life insurance policy Decision for Surat Population. This method has been used to take care of the sample selection problem. The results did not suggest sample selection bias in this case. Therefore, random selection model was used in this study. We used demographic variables as independent and personal factor & product variable as dependent variable to take decision.as discussed above we have identified thirteen factors, which effect life insurance purchase decision. Respondents were asked to rate these variables on the scale of one to three where one indicates highest significant importance. These variables have been used as interval variable. TESTING OF HYPOTHESIS, DATA ANALYSIS AND RESULTS 1. H0; There is significant Relationship between Type of Insurance Players and Life Insurance Policy buying Decision. Out of 60 respondents, 53 respondents prefer LIC Policy other than Private Insurance Players Policy in Surat City. Since the difference is 1.81, which is less than 1.96 at 5% level of significance, hence the hypothesis is accepted. So it is interpreted that type of insurance player is important factor for buying decision of Life Insurance Policy in Surat City. 2. H0; There is significant Relationship between Demographic Factors (Like Age, Gender, Family Income, Occupation and Education Level) and Life Insurance Policy buying Decision. For of 60 respondents from the survey, average age was found 32.33 years and standard deviation was of 9.68 years. Can we assume that population average age is 35 years for buying Life insurance policy in Surat city? Since the S.E is 1.25 and difference is 2.136 which is less than 2.58 S.E at 1% significant level, hence hypothesis is accepted and interpreted that there is relationship between demographic factors and buying decision of Life insurance policy. 3. In a sample of 60 life insurance investors, 39 are male and out of that 32 are saying that income has effect on life insurance policy buying decision. From female respondents, 16 respondents have accepted that effect. By using Chi-square Test, it will be stated that whether there is any significance difference between male and female for stating the effect of income on life insurance policy buying decision for Surat City Population (Table 1-3). Table value of Chi-Square at 1 degree of freedom at 1% level is 2.706 and calculated value is 0.293, which is less than table value. So null hypothesis is accepted and states that income has significant Rising Research Journal Publications 7

impact on buying decision of life insurance policy in Surat City (Table 4). 4. Correlation between Age and Income Level for buying Life insurance Policy. By using correlation of grouped bi-variate data method: So it is indicating that age group and level of income have positive strong correlation for taking buying decision for Life Insurance Policy for Surat City Population. 5. Some facts and figures from the survey in Surat for Life Insurance Policy. From the survey, table 5 and 6 are found. Interpretation of these: - 78% of respondents saying that risk covered in a particular scheme is important to buy life insurance policy, 12% of respondents are disagree with this variable and 10% respondents are neutral about this variable. - 67% respondents are accepting that no. of branches in city is important to buy once life insurance policy. 29% respondents are saying that it is not important because of online facility. - 52% respondents said that no. agents of company are important to buy and understand a particular scheme in life insurance policy. 43% respondents disagree with this because of internet facility and company s bulletin. - 86% respondents are saying that income level is important to buy life insurance policy and to select a particular scheme. - 81% respondents are saying that education is important to take decision about purchase life insurance policy, because it helps to understand the policy in detail. - 90% respondents say that to know about the company is vital to take decision for purchasing of life insurance policy. That means awareness plays important role to increase the market share. - 81% respondents attitude toward the Life Insurance is positive for investing in this avenue. - Type of insurance player is very important to take buying decision from respondent point of view. Majority prefers LIC and followed by ICICI Prudential, Bajaj Allianz, TATA AIG, and HDFC Life Insurance. - Majority, 65%, respondents are male and remaining are female as a life insurance policy user. CONCLUSION Life insurance policies are long-term policies and they are purchased by considering many factors. Both Public and Private Insurance players are growing in the market but Public sector is more preferred as compare to private sectors insurance. We find the factors affecting to buying decision of life insurance policy are age, income, education, awareness about insurer, attitude towards life insurance, occupation gender etc. among this all age, income level, awareness about the insurer and type of insurer most affecting factors to buying decision of life insurance policy for Surat city s population. The results also suggest customer satisfaction and attitude toward life insurance are significant factor in influencing the market share of life insurance players. This includes good experience to the customer during the period of the policy. BIBLIOGRAPHY 1. Namasivyam N, Ganesan S and S Rajendran. 2006. Socioeconomic Factors Influencing the Decision in Taking Life Insurance Policies, Insurance Chronicle August, the Icfai University Press, pp 65-70. 2. Philip Kotlar. 2008. Marketing Management. 12 th Ed (Singapore; Pearson Education Pvt. Ltd.), pp: 278-308. 3. Sunayana Khurana. 2008, Customer Preferences in Life Insurance Industry in India The Icfai University Journal of Services Marketing, Vol. VI, No. 3, 2008, pp 61-68. 4. Bhat, Ramesh and Nishant Jain. 2006. Analysis of public and private healthcare expenditures. Economic and Political Weekly Vol 41 No 1 January 7, 2006. 5. ICMR. 2005. Case Studies in Insurance, ICFAI Center of Management Research. IRDA. Rising Research Journal Publications 8

Table: 1. Analysis of Life Insurance Investors of Surat City Variable Targeted Population Age Risk factor No. of Branches in Surat No. of Agents in Surat Income level of policy holder Education level of policy buyer Awareness about the company Loyalty Status Attitude toward Life insurance Premium Pattern Type of Insurance Players Life Style of policy user Gender Definition Life Insurance Investors of Surat City This variable divided into four groups: Group 1 : 15years 24 years Group 2 : 25years 34 years Group 3 : 35years 44 years Group 4 : 45years 54 years Risk covered in a particular scheme Branches available in Surat city. Number of agents available in Surat City. Annual Personal Income. Divided in six groups in the study: Group 1 : Income Less than Rs. 100,000 Group 2 : Rs.100,000 Rs. 200,000 Group 3 : Rs.200,000 Rs. 300,000 Group 4 : Rs.300,000 Rs. 400,000 Group 5 : Rs.400,000 Rs. 500,000 Group 6 : Income more than Rs. 500,000 Education level divided in four groups: School, Graduate, Post Graduate and other It includes LIC and some major private players in the field of life insurance like ICICI prudential, Bajaj Allianz, TATA AIG, and HDFC Life Insurance. Loyalty status states about first time user or regular user. Attitude is measured with the help of many factors like necessity of life insurance, complexity in understanding and for claim settlement, rate of return, premium burden, etc. It states about premium as per sum assured amount for life insurance policy. It includes Public Sector Unit Players and Private Sector unit players in the field of Life Insurance in Surat City. It state about Hi-Fi, Middle or Lower life style of policy user It states about gender of respondent. Table: 2. Income affects significantly to the life insurance policy buying decision Gender\Income Effect Yes No Total Male 32 7 39 Female 16 5 21 Total 48 12 60 Rising Research Journal Publications 9

Table: 3. Expected frequencies of Income affects significantly to the life insurance policy buying decision Gender\Income Effect Yes No Total Male 31.2 7.8 39 Female 16.8 4.2 21 Total 48 12 60 Table: 4 Calculation of Chi-Square at 1% significance level O E O-E (O-E) 2 (O-E) 2 /E 32 31.2 0.8 0.64 0.021 16 16.8-0.8 0.64 0.038 7 7.8 0.8 0.64 0.082 5 4.2-0.8 0.64 0.152 0.293 Table: 5. Income affects significantly to the life insurance policy buying decision at different ages. Age\Income <1 1-2 2-3 3-4 4-5 >5 Total (Yrs)\(Rs.lacs) 15-24 3 7 3 2 0 0 15 25-34 1 2 6 4 4 3 20 35-44 0 3 3 4 3 5 18 45-54 0 1 1 1 2 2 7 Total 4 13 13 11 9 10 60 r = 0.693 Table: 6 Income affects significantly to the life insurance policy buying decision by different factors. Affecting Factors Yes (%) No (%) Neutral (%) Risk factor 78 12 10 No. of Branches in Surat 67 29 4 No. of Agents in Surat 52 43 5 Income level of policy holder 86 9 5 Education level of policy buyer 81 14 5 Awareness about the company 90 6 4 Loyalty Status 98 2 - Attitude toward Life insurance 81 0 19 Premium Pattern 89 10 1 Type of Insurance Players 87 11 2 Life Style of policy user 58 35 7 Gender 65 34 1 ****************************************** Rising Research Journal Publications 10