AN ASSESSMENT OF DEMOGRAPHIC PROFILE AND CUSTOMERS ATTITUDE TOWARDS GENERAL INSURANCE INDUSTRY DR.SONIA CHAWLA Professor & Head, Department of Business Administration, DAV Institute of Engineering & Technology, Kabir Nagar, Jalandhar POOJA SHARMA Research Scholar, Punjab Technical University ABSTRACT The paper tried to analyze the policyholders of different gender, age group, educational background and income level. The data of the study has been obtained through well structured questionnaire filled by 250 policyholders of general insurance plans of the state of Punjab. Convenient sampling along with judgment sampling has been used in the data collection. The policyholders have been divided into two categories i.e. public sector respondents and private sector respondents. A cross category comparison has also been done so as to assess the differences in the attitude of the respondents towards the various aspects relating to general insurance industry. The present study is also trying to uncover customer s feelings and attitudes towards phenomenon of privatization and consequent changes brought in the general insurance industry in India. Key words --- General Insurance, Policyholders, Respondents, Service Quality. INTRODUCTION Insurance is a mechanism which apart from providing social security also plays a significant role in allocation function, improving capital market and providing worldwide support to the global companies. The growing importance of the insurance industry has led to its internationalization which involves deregulation and liberalization of the insurance market. Insurance business is basically divided into two broad segments i.e. Life Insurance and General Insurance. General Insurance includes insurance of property, personal insurance such as accident and health insurance and liability insurance which covers legal liabilities. Some other types of insurance such as errors and omissions insurance for professionals, credit insurance are also part of general insurance. Tracing the developments in the Indian insurance sector reveals the 360-degree turn witnessed over a period of almost 190 years. The new economic policy and liberalization process followed by government of India since 1991 paved the way for privatization of insurance sector in country. The growth of insurance industry is associated with the general growth of industry, trade and commerce. The general insurance industry grew (in terms of gross direct premium) at Compounded Annual Growth Rate (CAGR) of 17.16% from the year 2005-06 to 2014-15. However, the insurance penetration and insurance density levels are significantly lower than the developed as well as comparable developing countries. REVIEW OF LITERATURE Review of literature is conducted to have an in depth idea related to the field of study. It also enhances the knowledge base of the researcher and provides direction for further study. Some relevant studies which are crucial in the understanding of the current topic are as follows: 1
Dean (2002) explored the absolute and relative levels of customer expectation of the service quality of a call centre and assessed the relationship between expectations and perceived customer orientation. The study collected the data from 289 customers of large insurance providers. The relevant scales of this paper were customer orientation, service quality predictions and adequate level of service expectation. The result of this study showed that customers had very high levels of adequate (minimum) expectations and that adequate expectations behaved independently from predicted (forecast) expectations: customer orientation was associated with predicted expectation but not adequate expectations. Reddy and Spandana (2002) concluded that liberalization of insurance sector is both a challenge and an opportunity. They emphasized that to really make a dent in the insurance industry the entry of private companies should ensure new policies, reduction in premium rates, radical expansion in distribution and sales channels, more efficient allocation of policy funds and improved customer service. They suggested that industry should adopt three pronged regulatory framework comprising internal control system, external statutory auditors and a supervisory regulatory body. They also emphasized that IRDA must be allowed to function autonomously with minimal government interference. Choudhary et al., (2007) measured the customer s expectations and gaps in service quality. They surveyed 450 customers, out of which 416 customers were analyzed who had insurance policies in private or public insurance companies. They used F-Test, T-Test, Chi-Square Values Cramers V and P to analyze the data. The results suggested that companies have to take steps to eliminate hurdle in way of customers getting payment of claims after any incident, public insurance companies pay more attention to understand the problems of clients. Sandhu and Bala (2011) tried to analyze the customers perception towards service quality of Life Insurance Corporation(LIC) of India and also identified the relationship between each of generated service quality dimension and customers overall evaluation of service quality of LIC. They surveyed 450 customers, out of which 337 customers were analyzed. They collected the data by using nonprobabilistic convenience sampling technique. After that they took seven factor structures such as proficiency, media and presentations, physical and ethical excellence, service delivery process and purpose, security and dynamic operations, credibility and functionality. The study suggested that among seven factors three factors namely had significant impact on the overall service quality of Life Insurance Corporation of India such as proficiency, physical and ethical excellence and functionality. Sharma et al., (2011) focused on insurance companies of economies of Asia i.e. India and Chinese, tried to develop a reliable instrument to measure customer perceived quality. A pilot study was conducted to investigate service quality structure, performance and expectations, different dimensions on service quality offered and assess service quality in insurance as perceived. The result of this study showed that both the countries are operating in similar environment but the response regarding service quality differs from users of one country to another. Dash and Pany (2012) made an attempt to show that service quality, customer satisfaction and customer value had main concern of service organization in the increasingly intensified competition for the customers. The study revealed that in pricing decisions, service quality and cost of service is also important element apart from competitor s prices. Singhal and Gupta (2013) made attempt to measure the gaps between expectations of customers and services perceived by them from insuring companies. This paper used SERVQUAL model using five parameters: tangibility, reliability, responsiveness, assurance and empathy. This paper covered seven district of Haryana for their survey. The study found that customers showed negative response regarding their insuring companies and were not satisfied with service quality level. 2
Ahmed and Kwatra (2014) tried to examine importance given by customers of insurance companies to measuring quality, which is the most important element in their decision to get an insurance policy or renewal of same. The self administered questionnaire was used to collect the data. The result of study revealed that customer focus on claim settlement and measurement of the quality of the policies they were holding. OBJECTIVES OF THE STUDY a) Investigate and analyze the demographic profile (age, gender, qualification and income level) of the policyholders; b) Examine the awareness level of the policyholders towards changes brought in general insurance industry due to privatization. RESEARCH METHODOLOGY Data has been collected from the seven cities of Punjab. A sample size of 250 policyholders has been taken for the purpose of the study. Convenient sampling along with judgment sampling has been used in the study because only those respondents had to be selected for the study who possessed insurance policy at the time of survey and who were willing to fill up the questionnaire/schedule. The demographic profile of the respondents has been analyzed by using Chi square method. DATA ANALYSIS Graph 1 describes the nature of insurance company. Graph depicts that 53% of the respondents have purchased the policy from public sector insurance company while 47% of them have chosen private insurance company. Among the public sector the majority of the respondents were from New India Assurance Company Limited followed by National Insurance Company Limited and United India Insurance Company Limited. Among the private players most of the respondents were from Bajaj Allianz General Insurance Company Limited, ICICI Lombard General Insurance Company Limited and Reliance General Insurance Company Limited. Graph 1: Graphical Presentation of Type of Company Graph 2 shows presentation of respondents according to kind of insurance policies. Graph depicts that 52% of the total number of respondents had motor insurance plans/policies, 32% of the total number of respondents had health insurance plans/policies and 16% respondents had other types of plans/policies. 3
Graph 2: Graphical Presentation of Respondents According to Kind of Insurance Policies Table 1 depicts the demographic profile of the respondents. Out of the total number of respondents 86.40% are males, whereas remaining 13.60% are females. An analysis done on the basis of age group shows that out of the total number of respondents, 56.80% respondents are from the age group of 36-45 followed by age groups of 26-35 and 46 or above with the percentage of the two groups being 28.40% and 14%, respectively. Table 1 also depicts analysis based on the educational background. In both public and private sector maximum numbers of respondents are having an education level of bachelor degree followed by the education level of master degree. Overall results also follow the same pattern as 66.8% of the total numbers of respondents are having the bachelor degree and 16.4% of the total numbers of respondents are having high school degree, 15% of the total numbers of respondents are having master degree. An analysis on the basis of income groups shows that in case of public sector respondents and private sector respondent s income group of Rs.200000-500000 is dominating followed by income group of Rs.500000-800000. However, the overall results show that income group of Rs.200000-500000 is the most dominating group with 68.40% of the respondents followed by the income group of Rs.500000-800000 with 21.60% of the respondents and income group of less than Rs.200000 with 8% of the respondents. Table 1: Category Wise Demographic Profile of the Respondents Respondents Public Sector Companies 4 Private Sector Companies Total Sex a. Male 114 (45.60%) 102 (40.80%) 132 (86.40%) b. Female 18 (7.20% ) 16 (6.40%) 118 (13.60%) Current Age ( Years) a. Less than 25 0 (0%) 2 (0.8%) 2 (0.8%) b.26-35 30 (12%) 41 (16%) 71 (28.40%) c.36-45 82 (32.8%) 60 (24%) 142 (56.8%) d.46-above 20 (8%) 15 (6%) 35 (14%) Educational Background High school 19 (7.60%) 22 (8.80%) 41 (16.4%) Bachelor s degree 92 (36.80%) 75 (30%) 167 (66.8%) Master degree 18 (7.20%) 21 (8.40%) 39 (15.6%) Doctorate degree 3 (1.20%) 0 (0%) 3 (1.20%) Other 0 (0%) 0 (0%) 0 (0%)
Income Income Less than 200000 9 (3.60%) 11 (4.40%) 20 (8%) Between 200000-500000 87 (34.80%) 84 (33.60%) 171 (68.40%) Between 500000-800000 32 (12.80%) 22 (8.80%) 54 (21.60%) More than 800000 4 (1.60%) 1 (0.40%) 5 (2%) Chi square test applied to check the level of association between public/private sector and gender shows a significance level of 0.986 and Contingency coefficient of 0.001which means that Chi square test is not showing significant association between two variable public/private sector and gender (male/female) as level of significance is much above significance level of 0.1. Contingency coefficient of 0.001 reveals that the association between the dependent and independent variable is not strong as well, as the value.001 is closer than 0 to 1. Table 2: Demographic Profile of Respondents Based on Age Wise Chi square Value DF Significance Pearson 7.065a 3 0.070 Likelihood Ratio 7.838 3 0.049 a. 2 cells (25.0%) have expected count less than 5. The minimum expected count is 0.94. Contingency Coefficient 0.166 Table 2 depicts chi square analysis on the basis of age. Chi square test applied to test the level of association between age and category of respondents shows a significance level of 0.070 at 93% (100-7) confidence level. The above result shows that at significance level of 0.07 (which is less than 0.1); there is significance relationship between two variables. This means the chi square test is showing a significant association between variable public/private sector and age group at 90% confidence level. However, Contingency coefficient of 0.166 reveals that the association between the dependent and independent variable is not strong, as the value 0.166 is closer to 0 than 1. Table 3: Demographic Profile of Respondents Based on Educational Background Chi square Value DF Significance Pearson 4.795a 3 0.187 Likelihood Ratio 5.942 3 0.114 a. 2 cells (25.0%) have expected count less than 5. The minimum expected count is 1.42. Contingency Coefficient 0.137 Table 3 depicts that Chi square test does not demonstrates significant relationship between two variables at significant level of 0.1.This means the Chi-Square test is not showing a significant association between variable public/private sector and educational background at 90% confidence level. Contingency coefficient of 0.137 also reveals that the association between the dependent and independent variable is not strong as well, as the value 0.137 is closer to 0 than 1. Table 4: Demographic Profile of Respondent Based on Income Chi square Value DF Significance Pearson 3.130a 3 0.371 Likelihood Ratio 3.259 3 0.353 a. 2 cells (25.0%) have expected count less than 5. The minimum expected count is 2.36. 5
Contingency Coefficient 0.111 Table 4 depicts chi square analysis on the basis of income groups. Chi square shows a significance level of 0.371 at 62.9% (100-37.1) confidence level. So, chi test carried out at significant level of 0.1 shows that there is not significance relationship between two variables. This means the Chi-Square test is not showing a significant association between variable public/private sector and income group at 90% confidence level. In the same way contingency coefficient of 0.111 also reveals that the association between the dependent and independent variable is not strong, as the value 0.111 is closer to 0 than 1. Policyholders were also asked certain questions as to the source of information at the time of purchase of policy, frequency of purchase of insurance plan from the same player, frequency and purpose of visit to branch, awareness about grievance redressal mechanism and Insurance Regulatory and Development Authority of India. An analysis of the responses has been elaborated as below: Graph 3 reveals that in the public sector about 56% of the respondents relied on the insurance agents/ development officer (D.O), 18% respondents relied on the relative /friends and 14% on tax consultant. In private sector the proportion of agents as a source of information has been 47%, proportion of relative/friends has been 23%, proportion of tax consultant, proportion of advertisement has been 11%. On the overall basis it was found that source of information while purchasing the general insurance policy, agent/development officer (D.O) has been the most dominating source (52%). This has been followed by information available from friends/relatives (20%) and tax consultants (14 %). The dependability on other sources including advertisement (through print and electronic media) (8%), internet, consumer meets, pamphlets and leaflets (5%) has been very low. Graph 3: Graphical Presentation of Sources of Information for Purchase of Insurance Policy Graph 4 demonstrates the frequency of purchase of insurance policy among the surveyed respondents. The graph shows that 8% of the respondents of public sector were first time buyers while 23% were second time buyers and 27% are third time buyers and 42% had bought the policy for fourth time. The graph also shows that 5% of the respondents of private sector were first time buyers while 15% were second time buyers and 21% are third time buyers and 58% had bought the policy for fourth time. The analysis also reveals that majority of the respondents of both the sectors public sector as well as private sector repurchase had renewed policy from the same insurance company fourth time or above. 6
Graph 4: Graphical Presentation of Respondents According to Frequency Purchase of Insurance Plan Graph 5 shows the frequency of visit of the respondents to the insurance company branch office, it has been observed that both public sector as well as private sector, respondents prefer yearly visit followed by half yearly, monthly and weekly. On overall basis, it has been found that 76% of the respondents visited yearly and 14% of respondents visited half yearly, 9% of the respondents visited monthly and 1% of the respondents visited weekly. Graph 5: Graphical Presentation of Respondents Frequency of Visit Respondents were also asked about the purpose of their visit. Graph 6 depicts that majority of the respondents of public sector visited to branch office to pay premium (47%) followed by to seek information (39%) and to settle claim (10%), to register complaints (4%). In case of private sector, respondents visited to branch office to pay premium followed by to seek information (36%), to make complaints (55%) and to settle claims (10%). On overall basis, it has been found that 51% of the respondents visited branch office to pay premium, 38% of respondents visited to seek information, 7% of the respondents visited to settle claim and 4% of the respondents visited to make complaints. 7
Graph 6: Graphical Presentation of Respondents According- Purpose of Visit Respondents were also asked that whether the purpose of visit addressed adequately. As shown in Graph 7 in private sector 95% of the respondents and 93% of the respondents in public sector said that their concerns were adequately addressed. On the overall basis 94% of the total number of respondents stated that that their concerns were adequately addressed while 6% of the respondents said that their purpose of visit was not addressed adequately. Graph 7: Graphical Presentation of Respondents Purpose of Visit Addressed Adequately Graph 8 shows the awareness of the respondents about the claims grievance redressal mechanism. Awareness level is quite high in public sector where 92% of the respondents are aware about the grievance redressal mechanism. In private sector 82% of the respondents are aware about the grievance redressal mechanism. An evaluation on an overall basis shows that 87% of the respondents are aware and 13% of respondents are not aware of the grievance redressal mechanism which indicates poor dissemination of information to the policyholders. Graph 8: Graphical Presentation of Awareness about Grievance Redressal Mechanism Results of the survey highlighted the fact that 74% of the public sector respondents are aware of the Insurance Regulatory and Development Authority of India followed by 73% respondents being aware of 8
the same in case of the private sector. On an overall basis Graph 9 it has been found that 74% of the respondents are aware of IRDA while 26% of the respondents are not aware of IRDA. Graph 9: Graphical Presentation of Awareness about IRDA CONCLUSION The scrutiny done on the basis of age group shows that majority of the respondents was in the age group of 36-45 years (56.8%) in both the sectors of insurance companies. Education wise analysis shows that maximum number of respondents were having an education level of Bachelor s degree (66.8%) followed by High School (16.4%), Masters degree (15.6%) and Doctorate degree (1.20%). An analysis based on income groups reveals that the dominating group belongs to the income group of Rs.2-5 lakh (68.40%). Although agent continues to be the most important source of information in public sector/private sector insurance industry, yet there are other emerging sources such as tax consultants, advertisement, customer meets, leaflets etc in the private sector. It has been found that majority of the respondents prefer annual premium payment, followed by half-yearly tenure, monthly tenure and weekly tenure of premium payment. It has been observed that majority of respondents visit to insurance company to pay premium. It has been found 94% of the total number of respondents stated that that their concerns were adequately addressed, wherever they visited the branch office. The study revealed that overall 87% of the respondents are aware of the grievance redressal mechanism while 74% of the respondents are aware about IRDA. Efforts should also be taken by the IRDA or private players so as to make the policyholders aware of the grievance redressal mechanism and Insurance Regulatory and Development Authority of India (IRDA). REFERENCES Ahmed, A., and Kwatra. N (2014), Level of Customer Satisfaction with their Perception on the Quality of Insurance Services, Glaxy International Interdisciplinary Research Journal GIRIJ Volume 2(3) March, 2014 Chaudhary.K, Singla.J, Chaudhary.N(2014), Examining Expected and Perceived Service Quality in Life Insurance Corporation of India International Journal of Application or Innovation In Engineering & Management(IJAIEM) Volume 3,Issue1, January 2014 Dash, S.K and Pany, T.K (2012), Service Quality and Customer Satisfaction in Insurance Sector An Indian Perspective Asian Journal of Multidimensional Research Volume 1 issue 4, Sept.2012 Dean Alison M. (2002), Re-Thinking Customer Expectations of Service Quality: Are Call Centers Different? Monash University, Working Paper No.53\02 Reddy K.R. and Spandana K., (2002), Opening up of the Indian Insurance Sector: A Challenge and an Opportunity, Prestige Journal of Management and Research, Volume 6, No.1-2, April-October, pp 23-29. 9
Sandhu and Bala (2011), Customers Perception towards Service Quality of Life Insurance of India: A Factor Analytic Approach Volume 2 No.18, Oct.2011 Sharma R, Goyal R, Bansal M.N (2011), Service Quality Assessment in Insurance Sector: A Comparative Study between Indian and Chinese, Volume 2, No.5 2011 Singhal P., Gupta M.S (2013), Assessment of Service Quality in Insurance Sector (Haryana) Volume 3, Issue March 2013 10