THE IMPACT OF LIFE INSURANCE PRODUCT PRICING ON CUSTOMERS BUYING BEHAVIOUR

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1 26 ABSTRACT THE IMPACT OF LIFE INSURANCE PRODUCT PRICING ON CUSTOMERS BUYING BEHAVIOUR GANESH DASH* *Research Scholar, Department of Management Studies, School of Management, Pondicherry University, Kalapet, Puducherry This study has tried to assess the assumed differences in the perceptions of the customers and the executives of the life insurance product regarding the impact of policy pricing on the final policy buying decisions of the potential policy holders. The various elements involved in the life insurance policy pricing can be outlined as: Price level, Terms of payments, Customer s own anticipated value, Policy quality and price comparison, Differentiation, Flexibility, Clearly laid price structure and Incentives and discounts. This study relies on assumption that both the customers and the executives (of both urban and rural area) have the similar perceptions regarding the impact life insurance product pricing on the customers buying decisions. Various statistical tools such as arithmetic mean and standard deviation were used to find out any possible differences in the perceptions among the various categories of respondents, especially to assess the impact of their respective localities on their perceptions. Further, to find out significant variation among these particular categories, t-test was applied. Finally, it was found that almost all the categories of respondents have similar perceptions except executives of urban area and rural area differing in their opinions about its impact on customers buying decision. This study will go a long way in helping the life insurers to formulate a good pricing strategy to influence the customers purchasing behaviours. KEYWORDS: Behaviour, Customer, Life Insurance, Pricing. INTRODUCTION Life Insurance is a contract for payment of a sum of money to the person assured, or failing him/her, to the person entitled to receive the same, on the happening of the event insured by the contract (Huebner & Black,1969) According to them, the peculiar nature of Life Assurance is that the contracted event is bound to happen and the insurer has to perform the contract; Life insurance covers death due to natural causes as well as due to accidents; Life insurance contract is a long term contract having all essential features of a valid contract; Life insurance is contract of assurance and not indemnity; A warranty in a life insurance policy is not collateral but basis to the contract.

2 27 Life insurance is a financial instrument used for providing support for survivors, paying estate obligations arising after death, adjusting business losses because of a top personnel s death, accumulating funds for retirement, emergencies and other future uses and also solving income tax problems (Mehr, 1986). Life insurance is a legal agreement between one and the Insurance Company to secure the Family s future in case of untimely demise. It provides with a predetermined amount to the beneficiary during the contract period. The primary purpose of Life Insurance is the protection of the entire family in case of death. Nowadays, Life insurance also acts as a tool to plan effectively about one s future Savings, his child s education needs etc. So apart from covering his life, it is an effective tool to enhance his wealth. In an economically evolving country like India where the disposable income in the hands of prospects is low, the pricing decision also governs the transformation of potential policyholders into actual policyholders. The strategies may be high or low pricing keeping in view the level or standard of customers or the policyholders. Life insurance policy pricing deals with proper management of the expenditures incurred by the customers in obtaining benefits from the relevant life insurance product. In the case of life insurance, premium is the price which the person seeking insurance pays to the concerned life insurer to purchase a life insurance product. In the insurance business, the pricing decisions involve some factors such as: the premium charged against the policies; interest charged for defaulting in the payment of premium and credit facility; and commission charged for underwriting and consultancy activities. With a view of influencing the target market or prospects the formulation of pricing strategy becomes significant. The pricing in insurance is in the form of premium rates. The three main factors used for determining the premium rates under a life insurance plan are mortality (deaths in a particular area), expense (cost of processing, commission to agents, reinsurance companies as well as registration) and interest (people would not be willing to invest in insurance business if the interest rates provided by other financial institutions are much greater than the perceived returns from the insurance premiums) (Dash & Khan, 2011). The premium rates are revised if there are any significant changes in any of these factors. Pricing is a powerful element in the life insurance marketing strategy which hugely affects the final sale of the product. Price is the valuation placed upon the product by the life insurer. The management must take decisions regarding pricing (premium), investment return, premium level, premium mode, commission rate, insured sum amount, life covered, pricing strategy, under writing and price related contingencies. Cost driver is the factor whose change causes incurring of costs, i.e., the number of times the cost has been incurred. Activity-based costing is a very useful tool when competition is very stiff between life insurance companies and various types of products. It helps cut costs for unused resources and finds potential resources. The insurers earn their income through: premiums, profit/ loss on sale/ redemption of investments and interests and dividends on premiums on these investments. But, out of the income generated by the insurers, there is some expenditure to be met such as: agent commissions, employee salaries, administrative expenses, claims, policy benefits to insured, banking costs and legal and professional fees. BRIEF REVIEW OF EXISTING STUDIES In Booms and Bitner (1981) s framework, the human touch is introduced to deal with the service delivery, namely the firm s personnel and other customers. In services such as life insurance, the

3 28 firm s personnel highly influence customer perceptions of the product. Berry (1984) further opined that the firm people are part of the product and hence product quality is inseparable from the quality of the service provider. After the 7P s concept came to the limelight, all the elements of traditional marketing mix got a new meaning incorporating human element for service products (Rafiq and Ahmed, 1995). Life insurance has become a prominent service product in this century. They compared the Kotler (1976) s 4P s model with the new 7P s model to analyse the variations developed in the elements. The pricing element in old mix involved only three subelements, namely, price level, discounts/ allowances and terms of payments. But, the pricing element in the new mix added three more sub-elements to the existing sub-elements, namely, customer s own perceived value, quality/price interaction and price differentiation. These new variables along with the existing variables were used as the items under policy pricing scale in this study. Mukherjee (2005) has mentioned about product pricing in Indian life insurance sector. In the insurance industry, with the entry of private players, advancement of technology and speed in communication, communicating with the remotest customers also became very easy. Pricing of life insurance products plays a major role in marketing them. In this study, he has explained extensively the pricing methodology of insurance companies. Low pricing attracts the customers whereas high pricing drives them away. Therefore, competitive pricing which takes care of the interests of both the insurer and the insured should be implemented. Dash & Khan (2011) tried to assess the perception of the executives about the various life insurance policy pricing attributes through a detailed empirical analysis. The various elements involved in the policy pricing are outlined as: affordability of the price level, flexibility of terms and conditions, worth of its value (as anticipated by the customer), uniqueness and better than alternate policies, simple and clear price structure and discounts/incentives. This study assumed that age, gender, education, experience and organization have no effect on the perception (of the policy pricing elements) of the executives. After a thorough investigation and statistical analysis, they found that age, experience and organisation have no significant impact on the executives perception of the pricing attributes. But, the study has shown that gender and education have an impact on the seller s perception of the pricing variables. The executives have a positive perception (agree) about all the pricing attributes except worth of its value. This study helps in understanding the seller s view point of the various elements associated with policy pricing which will give a chance to the insurers to make a better pricing policy. MAJOR OBJECTIVES The first objective of this study was to examine the perceptions of both the customers (buyer) and the executives (sellers) with respect to the impact of life insurance policy pricing on the customers buying behaviour. Then, the second objective was to find out the extent of differences in their respective perceptions. The third and ultimate objective was to assess the impact of their residing locality (urban vs. rural) on their respective perceptions regarding the impact of policy pricing on the customers final buying decision, i.e. to compare the perceptions of both the customers/ the executives of urban area with those staying in rural area.

4 29 METHODOLOGY FORMULATING NULL HYPOTHESES As per the objectives outlined in this study, the following hypotheses were drawn to be tested: H 0 1: There is no significant difference in the perceptions of the customers and the executives with respect to the impact of policy pricing on the customers buying decision. H 0 2: There is no significant diffrence in the perceptions of the customers of the urban area and the customers of the rural area regarding the impact of policy pricing on the customers buying decision. H 0 3: There is no significant difference in the perceptions of the executives of the urban area and the executives of the rural area about the impact of policy pricing on the customers buying decision. H 0 4: There is no significant difference in the perceptions of the customers of the urban area and the executives of the urban area regarding the impact of policy pricing on the customers buying decision. H 0 5: There is no significant difference in the perceptions of the customers of the rural area and the executives of the rural area with respect to the impact of policy pricing on the customers buying decision. DATA COLLECTION The data for this study was collected from primary sources which consisted of both the customers and the executives involved in life insurance marketing process. The area chosen for this above said sample population covered the southern districts of Odisha. The period of data collection was last two quarters of life insurance customers and 207 life insurance executives were interviewed in this process. These respondents were selected from both urban and rural area in order to assess the impact of residing locality on their perceptions. A well structured questionnaire was framed with questions on their perceptions of the various subelements involved in the life insurance policy pricing. For this purpose, a five-point scale (from 1 to 5) has been adopted with 1 being Strongly disagree and 5 being Strongly Agree. MEASURES FOR THIS STUDY This study covers the aspect of life insurance policy pricing in the Indian life insurance sector and its impact on the buying decision of the customers. Price level, Terms of payments, Customer s own anticipated value, Policy quality and price comparison, Differentiation, Flexibility, Clearly laid price structure, Incentives and discounts are the various items of this scale. The scales and various items under these scales (from both the customers and the

5 30 executives viewpoints) are illustrated below: Scale: Policy Pricing (customers) Items: 6 [Strongly Disagree -1, Strongly Agree -5] ITEMS The price level of the policy is affordable for me The terms of payment is flexible and convenient for me The price of the policy is as per my anticipation regarding its worth The pricing is unique and better compared to other alternate policies The price structure is simple and clearly laid This price level provides good amount of discounts /and incentives Scale: Policy Pricing (executives) Items: 6 [Strongly Disagree -1, Strongly Agree -5] ITEMS The price level of the policy is affordable to the customer The terms of payment is flexible and convenient for the customer The price of the policy does not exceed the anticipation of the customer regarding its worth The pricing is unique and better compared to other alternate policies The price structure is simple and clearly laid This price level provides good amount of discounts /and incentives to the customer SAMPLE DETAILS The study area in question consists of two towns with more than one hundred thousand populations and rest of the area is semi-urban and rural. The population is defined as follows: customer means people who have bought a policy in the last quarter (3 months) and executive means people who have sold a policy in the last quarter (3 months). It was found that more than people have bought life insurance policiees in the last quarter whereas more than 900 executives have sold at least one policy. An item-respondent ratio of 1:6 and 1:5 respectively were recommended by Hinkin (1995) and Heir et al (2006). Though, the worlwide standard ratio is 1:10, an item:respondent ratio of more than 1:10 was adopted for this study. Due to time constraint, the sample size for the customers was restricted to 405. The details of sampling is given as below:

6 31 Total customers = Sample customers = 405, Urban (163) and Rural (242) Total executives = 900+ (active) Sample executives = 207, Urban (92) and Rural (115) DATA RELIABILITY WITH VALIDITY Reliability can be defined as the degree to which consistent results are produced by the prepared scale (with repeated measures). It sees that the measures are free from random error. Churchill (1979) has suggested coefficient alpha to check the internal consistency of items placed under a factor. Further, Heir et al (2006) have also suggested the alpha value to be 0.6 and above. For both the customers and the executives, cronbach s α were found to be and respectively which are more than 0.6. Again, all the items under both the scales were found to be having a loading of more than 0.5 (see table-1). TABLE-1 RELIABILITY ESTIMATES WITH FACTOR LOADINGS FOR POLICY PRICING Factors Scale Items Factor Loadings 1 P P2.799 No. of Items Cronbach s α Policy Pricing (Customers) Policy Pricing (Executives) 3 P P P P P P P P P P6.625 Note- Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Rotation converged in 3 iterations. Source: Primary Data

7 32 RESULTS AND DISCUSSION If the perceptions of all the 612 respondents are taken in to consideration, the impact of life insurance policy pricing on the customers buying behaviour was found to be highly positive. As per these respondents perceptions, the pricing strategies of Indian life insurers positively influence the customers decision to buy a life insurance policy (see table-2). Coming to the perceptions of the individual categories of respondents, executives of urban area have highest perception (positive) of the policy pricing closely followed by the executives taken as a whole who also have a positive opinion. But, executives of rural area have the least perception (positive) of its impact on the customers buying behaviour. This study shows that both the customers and the executives have positive perceptions regarding this factor s impact on customers buying decision. But, the executives are more positive about its impact then the customers (See table- 2). Hence, it can be inferred that the sellers think more positively about the impact of policy pricing on the buyers purchasing decision whereas the buyers, themselves, also think positively about its impact on their behaviour. TABLE-2 PERCEPTIONS OF THE IMPACT OF POLICY PRICING ON THE CUSTOMERS BUYING DECISION Source: Primary Data Types of Respondents N Mean Rank All (customers +executives) Customers Customers (Urban) Customers (Rural) Executives Executives (Urban) Executives (Rural) From table-2, it can be seen that there is a difference in the perceptions of the buyers and the sellers of life insurance products regarding the influence of policy pricing on the policy holders buying behaviour. Especially, the executives of urban area have significantly higher perceptions than the executives working in rural area. To assess the extent of these differences (significant or not), these perceptions were compared using t-test. As per the hypotheses set in this study, five tests were conducted among the various categories of respondents involving both the customers and the executives mentioned earlier. TESTING OF NULL HYPOTHESES As it can be seen from table-3, there is a negligible difference in the perceptions of the customers and the executives as the significance level (0.74) was found to be more than the given level of Hence, the first null hypothesis, H 0 1, was accepted. Similarly, the customers of both the urban and rural area possess almost similar perceptions with the significance level (0.81) exceeding the given level of 0.05 by a huge margin. Hence, the second null hypothesis, H 0 2, was

8 33 also accepted. But, the third null hypothsis, H 0 3, was rejected as the level of significance (0.04*) was found to be less than Again, customers and executives of urban area had differences in their perceptions, though not so significant as the significance level (0.15) is more than Hence, the fourth null hypothesis, H 0 4, was accepted. Similarly, the last hypothesis, H 0 5, was also accepted as the significance level was more than the given level. Though the various categories of respondents had differences in their perceptions, the difference was not so huge to affect the results except between executives of urban area and executives of rural area. TABLE-3 TESTING OF HYPOTHESES (T-TEST) Factor Null Hypotheses Comparison of Respondents t- value Difference (significance) Results H 0 1 Customers and Executives Accepted H 0 2 Customers (Urban) and Customers (Rural) Accepted Policy Pricing H 0 3 Executives (Urban) and Executives (Rural) * Rejected H 0 4 Customers (Urban) and Executives (Urban) Accepted H 0 5 Customers (Rural) and Executives (Rural) Accepted *significant at 5% level **significant at 1% level Source: Primary Data/ SPSS output DISCUSSIONS This is a general assumption that the sellers have a more positive perception regarding the product compared to the same of the customers. This study also supports this theory. Though both of them have positive perception about the impact of policy pricing on the customers buying behaviour, the executives have an edge over the customers. Generally the executives were more educated than the average customers (some of them were illiterate). The level of education along with awareness and understanding of the marketing process made the executives perceptions more positive than the customers. There was no earlier study available to test these findings. Further, the sellers operating in the urban area within the data collection zone differed significantly from their colleagues working in rural belts. This difference can be attributed to better education and awareness among the urban executives. The same is not true in case of the customers. Both the urban and rural customers have a similar perception. Though the urban customers were more developed (both economically and educationally) than the rural customers, they had no differences in their perceptions. This aspect has to be explored further.

9 34 THE LAST NOTE Based on this study, a few suggestions for the life insurance industry in India regarding their policy pricing strategies can be made. The price level should be well within the affordability level of the customer. Flexibility and convenience of terms of payment must be followed as per the requirements of the potential customer. The life insurance companies must ensure that the price of the policy should not exceed its worth as anticipated by the buyer. Again, a transparent comparison with the price levels of similar policies provided by the rival companies should be made before the prospective buyers. A clear and simple price structure should be provided by the selling companies to the customer that can be understood easily by a lay man. Further, discounts and incentives should be included in the pricing structure in order to attract buyers. There should not be any hidden cost which is most rampant in India. Now, almost all the life insurance companies are inching towards a low-premium policy era making the poorer rural sections eligible to possess the most elusive life insurance cover. They are providing the costs and benefits of the policies and proper justification for the relevant pricing. They are renovating the products to become worthy of their buying price. They are also adding lot of add-on benefits to the products to attract the recession-hit cash-strapped customers. Life insurance policy pricing strategy adopted by the insurers must incorporate the customers expectations along with their apprehensions in order to influence their buying behaviour. REFERENCES Berry, L.L. (1984), Services marketing is different, in Lovelock, C.H. (Ed.), Services Marketing, Prentice-Hall, Englewood Cliffs, NJ, pp Booms, B.H. and Bitner, M.J. (1981), Marketing strategies and organization structures for service firms, in Donnelly, J.H. and George, W.R. (Eds), Marketing of Services, American Marketing Association, Chicago, IL, pp Chiu, H.Z. (2003), Multivariate Statistical Analysis: SAS/ STAT Application Method (1 st ed.), Taipei, Chi-Bon Culture Press. Churchill, Jr., G.A. (1979), A Paradigm for Developing Better Measures of Marketing Constructs, Journal of Marketing Research, Vol. 16 No.1, 1979, pp Dash, Ganesh. and Khan, M. Basheer Ahmed. (2011), Life Insurance Product Pricing in Rural Odisha: An Empirical Study, Journal of Empirical Research in Management, Vol. 1, Issue-1, July 2011, pp Heir, Anderson, Tatham & Black (2006), Multivariate Data Analysis, Pearson Education, New Delhi, India Hinkin, T. R. (1995). A review of scale development practices in the study of organizations. Journal of Management, 21(5),

10 35 Huebner, S S. and Black Jr., Kenneth (1973), Life insurance (8 th ed.), Appleton-Century- Crofts, New York. Kotler, P. (1976), Marketing Management, 3rd ed., Prentice-Hall, Englewood Cliffs, NJ, p. 60. Mehr Robert I. (1986), Fundamentals of Insurance. Illinois, Irwin Mukherjee, Debkumar (2005), Pricing Of Life Insurance Products, The Accounting World, February 2005 Rafiq, Mohammed and Ahmed, Pervaiz K. (1995), Using the 7Ps as a Generic Marketing Mix: An Exploratory Survey of UK and European Marketing Academics, Marketing Intelligence & Planning, Vol. 13 No. 9, 1995, pp. 4-15