Consumer Behavior in the Insurance Market - Example

Research on Consumer Behavior in the Insurance Market Name: Institutional Affiliation: Executive Summary The paper familiarizes with the goals and aims mapping out the behavior of consumers of insurance choices against death. The risk insurance is chosen because most of the product offering insurers provides cover for the risk since that occurs in a high competitive bid environment. Specification of consumer behavior is taken into account by classification that influence potential irrational elements of behavior that provide clarity to the dilemmas studied that include age, income bracket as well as other informational demography. The extent of insurance coverage (for what is insured and what not exclusions from insurance), the amount of insurance coverage (the maximum monetary amount provided by an insurer when the insured event), Price (the amount of cash given by a consumer to an insurer to create insurance technical reserves). Rationally behaving consumer chooses a bid, which ensures transfer of a full range risk to an insurer. For instance, the extent of insurance coverage closely resembles an insurer against risk. Option C provides 100% coverage range for both men and women. Option B offers a range of 34% coverage for men and 17% for women. Option A offers a range of 32% coverage for men and 15% for women, chooses a level of insurance performance, which is sufficient to eliminate results from the realized risk, takes into account cost factors for comparison of the advantages of offers from various insurers. In this research, which offered insurance against death, it was the offer of one insurer and the consumer had a choice of three possible variants of this offer. Price does not give any effect for the case of rational behaviors. Voted for the option C, which offered the widest range of insurance coverage, would not vote for option B, which offered twice of the performance compared to variant C, since the scope of insurance coverage would be significantly reduced and insurance would not fulfill its intended fiction. Results from the study will help in enriching the theory of decision-making on the segment given. In broad practice, the findings will be useful to co-operative institutions that are aiming at optimizing their products to prevent decline in their contracts and expand their permanent clientele. The results indicate that most of the consumer who are influenced by a given factors show irrational acts. Some of these factors include the causes of claim discount of media coverage and extension offer of the insurance cover. TABLE OF CONTENTS Executive summary Introduction Background information Methodology Respondent analysis Factors affecting consumer behaviors Summary and conclusion Appendixes Research on Consumer Behavior in the Insurance Market Introduction The globalization degree of markets, competition increase and information asymmetry has resulted into challenges for market participation insurance market included. The side of the insurance market supply is under pressure for the high commissions charged by the intermediaries of insurance and lower margins calculations for the products. The quality requirements and levels of service provision increase on the demand side; because of the emerging new trends, the investment requires capital knowledge acquisition in the increased behavior of consumers treated with the importance it deserves. This project report is aimed at analyzing the behaviors of the consumer in choosing insurance covers against death. Creation and innovation of products by most of the insurers are based on the modern mindset of consumers, which are clearly structured in some cases. It is assumed by modernism that the models of rational economy characterize the systems of autonomy. One of the assumed factors affecting the demands for insurance products is the irrational consumer behavior; this is difficult for the insurer to contend. The key factor in achieving profits is the knowledge e of price identification and identification of right clients to offer the right products. Rational people need to behave in an effective way in the order of satisfy their target: consumers have to maximize their benefits that come from consumption especially the services (Thaler, 2000). The rational behavior assumption can be challenged by reasons that include: Informatics asymmetric Advertisement Group reference Age, sex, income and education group Given the aforementioned potentials for distortion of rational behavior of consumers, a research conducted in collaboration with one of the most influential players on the Czech insurance market was done in 2010. The research project was aimed at exploring the consumer behavior in the assumption of the offer from one form of insurance coverage like life assurance in case of death in three variants. Insurance against death was selected since it is the product portfolio for most insurers as one of the key insurance cover. The main research question that is to be answered by the research is, whether, the behavior of consumers in the insurance market is rational or not about the perfect information. In addition, what factors significantly influence the decisions of consumers? Background Information Making of decisions by the consumers has been an attraction to many researchers. From about 300 years ago, economists in the early days, who included Nicholas Bernoulli, John von Neumann and Oskar Morgenstern began examining the basis of consumer decision-making (Richarme, 2005). These early examinations approached the topic from an economic perspective and focused solely on the purchasing acts (Loudon, 1993). One of the prevalent models from this perspective is Utility Theory, which stated that consumers make choices basing on the expected outcomes of their decisions. Consumers are rational decision makers who are only concerned with self-interest (Schiffman, 2007; Zinkhan, Human, 1992). When theory of utility has a view of consumers to be rational economic people (Zinkhan, Human, 1992), researches done on Consumer Behavior put into consideration wide range of factors that influence the consumers, and highlights a broad range of activities of consumption beyond purchasing. The activities include recognition of the needs, information search, alternative evaluation, intension purchase building, and the purchasing acts, consumption and disposal. A complete view of consumer behavior has undergone through a number of stages from the past century in the light of new research methodologies and paradigmatic approaches adopted. With the evolution being continuous, the 1950s that the consumer behavior notion responds to the conception and growth of modern marketing to constitute more significant range of activities that have influence on the consumer decision (Blackwell, 2001). This is described in contemporary definitions of consumer behavior: includes studies of the processes involving individuals or groups in their selection, purchasing, use, or disposing products and services to satisfy their needs and desires (Solomon, 2006). In a further development of this issue, models of consumer behavior have been created like a model of rational, sociological, or frame model (Koudelka, 2006). The available information within the decision-making of consumers is particularly beneficial. This is because the asymmetric information influences the decisions in the sides of demand and supply. The asymmetric information is whereby the economic entities of one of the markets have more information than the other side. These entities can put into use or misuse the better information that may result into the damage of the market to the participants. It is expedient for the entities that interest in concluding the insurance being aware of the situations better than he insurance companies, which may prompt them to give false information on situations. On the other hand, the insurance may be the one having the better information due to their large number of clients and claims they undertake. The advantage of the demand side is the advantage of the client of the insurance company. The advantage lies in the fact that one’s situation is unknown like health condition, technical condition of assets, financial situation, better than the clients themselves who want to be insured. Therefore, such a client should logically conclude insurance whenever they think its worthy like the rate of their future benefit would be higher than if they did not conclude insurance. The client uses their dominance in the information assuming that the insurance company will pay them more than they pay the insurance company (Marešová, Drahokoupil, 2001). Analogy of an individual economic decision-making entity, whether to get insured or not, is the decision-making of the insurance company regarding the insurance premium. However, while for an individual economic entity as it has been said. This is a subjective matter in the case of insurance company given the large number of clients and claims; it is rather a mathematical problem solving through exploration of the collective phenomena. In this case, an informational advantage can be seen on the insurance company side. When the insurance company may use the historic and statistical ensemble of clients, insurance claims and events, they can guess the future development of currently concluded insurances in its deliberations. Because of the size of the statistical ensemble, it is obvious and possible to use the law of averages for the mutual balancing of risks, as well as other work with risk. Insurance companies based on historical data and other information obtained to create a calculating model of insurance premium, which they adjust at the time. According to Daňhel (2006), thanks to the above-mentioned, there is clear information prevalence on the insurance company side. In the decision-making field, a large number of studies have been implemented. These include, for example, consumer behavior in the selection of banking products in Pakistan. Table below shows the results of research objective two and three with the help of Marginal effect of sensitivity analysis. This is a 0.05 level of significance the seven influencing factors are rank from the factor analysis, and the logistic regression model is ranked as follows: Ranking Factor Name Marginal Effect 1 Price 0.16398341 2 Distance 0.10936621 3 Switching Cost -0.10567336 4 Service Quality 0.07095342 5 Reputation 0.06339969 6 Involuntary Switching -0.05280674 7 Effective Advertising Competition 0.04025589 This table of the marginal effect shows that the price factor makes a maximum impact of switching behaviors of consumers in retail banking in Pakistan on consumer bank. The unit increase of prices results into a probability of 16.4 percent for the consumer to have a switch on banks. Therefore, it is necessary to note that prices have a significant impact on the switching behaviors in consumer bank. Further research in the field of banking analyzed the decision-making of clients with regard to the quality of services provided (Ravichandran, Bhargavi, Kumar, 2010). The above equation shows the impact of the variables of service quality aspects such as convenient operating hours, modern equipments, and bank understand the precise needs of customer, and banks frontline employees being neat. On an average if the modern looking buildings and amenities change by one unit, there will be 0.135 units increase in the overall behavioral intention when other variables are kept constant. A similar analysis of consumer behavior, focusing on financial services, has been implemented in Portugal. There have also been investigated and identified the factors determining the choice of a product (Proença, Rodriguez, Amorim, 2009). Methodology For the analysis, the test of independence contingency table method was used. In the method, the considered file was divided into groups according to the character. The groups were named r according to the first character and p according to the second character. For the random selection, the independence of n sizes of the two characters of statistics was tested. The independence of the hypothesis validity, and the frequency of the variants nij, where i= (1, 2…r) and j= (1, 2…p), corresponded to the expected frequency values calculated in accordance to relation (Bohumil et al, 2010). This test of independence in the contingency table can be considered liable when the expected occurrence frequency of the nij is above the value of 5 in not less than 80% for each group, and that the expected frequency is more than 1 (Bohumil et al, 2010). The hypotheses tested were as below: Where i= (1, 2…r) Where j= (1, 2…p) The expected frequency for i, j is given by: The criteria of testing involved the statistics as below: The G statistic has X2 distribution with a degree of freedom of df= (r-1) (p-1). The critical value is calculated by an excel spreadsheet, meaning, a statistical function of CHIINV (α, df) is used. Therefore, the critical value formula X21-α, df. There is no refusing of the Null hypothesis in the condition given as below: In determining, the existent of nonrandom associations two categories of variables, a Fisher’s exact test of statistical method is employed (Weinstein, 2012). In this way, we let the two variable X and Y to exist, with observed states of n and m. A matrix of nXm is formed where the aij entries represent the observations number for x=i and y=1. The sums of the rows Ri and columns Ci are the calculated respectively then the sum of the matrix. Then the conditional probability is calculated to get the actual matrix for the given sums of the rows and columns, and this is done by: This is a multivariate generalization of a hyper-geometric function of the probability. The possible matrices for the nonnegative integers that are consistent with the sums of columns and rows are determined. The associated conditional probability is determined, and their sum to add up to 1 using the probability functions. While computing the P-value in the test, the tables must be organized in criteria that measure dependency, and the tables whose probabilities are added together are those that show equal or greater deviation from the independent table than those observed. For P-values Read More