Knowledge by the consumer of the way in which insurance advisors are remunerated may influence the choice of distribution channel. Possibly, consumers will be more inclined to purchase products through direct writing if they know insurance advisors receive a considerable amount of money if they sell a product. We measure the level of remuneration awareness by asking consumers whether they know in what way a insurance advisor is remunerated. If the question is answered correctly, remuneration awareness is set to ‘high’, otherwise it is set to ‘low’.
A second variable which might influence the choice of distribution channel is consumers’ stated knowledge of financial products. Consumers who think they have a high level of financial expertise will think they can compare financial product themselves, without the help of an insurance advisor. Consumers with a high stated level of financial expertise might be more inclined to purchase insurance products directly.35
A third variable influencing the use of distribution channel might be age (at the time of purchase of the product). Elderly people might be less able to compare complex financial products. Also, the Internet is an important tool in searching for a financial product. Elderly people might be less inclined to use Internet, especially for such purposes.
In addition, income might influence choice of distribution channel because the opportunity costs of searching for a financial product might be bigger, the higher one’s income. People with a higher level of income might be less willing to spend leisure time in searching for products themselves. Because the effect of additional income will presumably be less strong the higher
34
To make sure that the estimated endogenous quantity can indeed be interpreted as a probability, this function cannot be linear. Its value has to be limited between zero and one. A common choice for such a function is the logistic distribution. This results in a so-called Logit model. We have used the Logit model in our estimation. Choosing a different distribution results in a different binary choice model (probit). This does not yield qualitatively different results for our estimations.
35
We measure a respondents stated level of knowledge by asking whether she considers herself an expert in financial matters on a scale of 1 to 4. Respondents who answer 3 or higher are classified as having a ‘high’ stated level of expertise.
the level of income, we take the natural logarithm of income as the appropriate explanatory variable.
Also, the level of education might be important. Respondents with a high level of education might be more able to search for the best offer than people with a low level of education. We distinguish between respondent with a ‘low’ and a ‘high’ (HBO/WO) level of education.
Finally, gender might influence the use of distribution channel. For example, men might be more interested in financial products and might therefore be willing to invest more time in searching for an offer from a direct writer. The relevant factors influencing the choice of distribution channel are therefore:
• Stated level of expertise • Age
• Income
• Level of education • Gender
5.4.1 Results
To identify which parameters influence a consumer’s choice of distribution channel, we estimated the probability of purchasing an insurance product through an insurance advisor as a function of transparency, stated expertise, age, income, educational level and gender.
P(Insurance broker │β . xi) = F(β . xi)
β . xi = β0 + β1 remuneration awarenessi + β2 stated expertisei + β3 agei + β4 log(income)i + β5
education leveli + β6genderi
Table 5.2 Choice of distribution channel: logit estimates (financial advisor=1, direct channel=0) (number of observations=270) Estimate T-value Constant 1.157 0.45 Commission awareness − 1.977 − 6.53 Stated expertise − 0.346 − 1.11 Age − 0.050 − 3.37 In(come) 0.323 1.01 Education level − 0.658 − 2.12 Gender 0.273 0.74
The results in Table 5.2 show that age, education level and commission awareness are
significant in determining which distribution channel has been chosen.36 The higher someone’s age, the less probable it becomes that this person will buy products from an insurance advisor. Whether or not this result is in agreement with our intuition is unclear. On the one hand one might expect elderly people to have more difficulties searching for insurance products
themselves. On the other hand, elderly people might be used to purchase directly from a bank or an insurance advisor. The higher the education level of a consumers, the lower the probability that he or she will buy insurance products through an insurance advisor. For respondents with a higher level of education, it might be easier to search for products themselves. Finally, the more consumers know about remuneration (commission awareness), the more probable it is that they will buy products directly from an insurer instead of through an insurance advisor.
The effect of commission awareness is the most important effect of these three significant variables. If people are aware they actually pay for the advice they receive, they will search for an insurance product themselves more often. If consumers know how insurance advisors were remunerated, the probability of purchasing directly from an insurer increases with no less than 40%. The most straightforward explanation for this result is that consumers are not willing to pay for financial advice if the cost structure of advice is made explicit.