The bank switching behaviour of Singapore’s graduates: CONCLUSIONS AND RECOMMENDATIONS

This study has established that a six- incident model can be used to describe bank switching among Singapore’s graduates. It has been seen that ‘inconvenience’ and ‘service failures’ were by far the greatest causes of bank switching. ‘Pricing’ was found to have caused some switching, although the ‘strength’ of this reason was well below that of the two major causes. The lowest of the six ranked incidents was attraction by competitors. The findings suggest that push factors (such as being subject to high service charges and/or being served by impolite staff) are stronger influences on bank switching than pull factors (such as being attracted by a very appealing mortgage package or a high value property being offered in a lucky draw). It would be inappropriate, though, to say that pull factors never have an influence on a switching decision. They are influential, but with a minority of consumers who switch bank.

The narrow range of demographics (ie gender, race, income and age) that were used in this study was not successful at distinguishing switchers from non- switchers. Different types of consumer characteristics may be capable of making this distinction and further comments on this matter are made below.

Recommendations for further studies

Switching, as established in the present study, in the banking study of Stewart (1998) and the general services industry study of Keaveney (1995), may be caused by a single incident or more than one incident. This finding is worthy of further investigation in a number of ways. First, which single incidents are more prevalent and why? Secondly, in those switches that involve more than one incident, what is the normal combination of patterns and why? In such combinations, which is the more likely first incident and why? There is also the issue of what weight should be given to each incident in a complex switch. In the present study, a simplistic system was used in order to establish the relative importance the respondents placed on the various reasons. There is an argument that respondents should be given the opportunity personally to weight their reasons, as happened in one of the developments of the SERVQUAL model. Finally, it may be that some people switch when faced with certain types of negative incident while others, faced with exactly the same types of incident, do not switch. What reasons cause consumers to behave differently when exposed to the same negative experiences?

The study established that the stronger influences of bank switching were negative experiences. The investigation stopped at this point. In the time after the decision to switch has been made, it would be of interest to establish the behavioural pattern of consumers when selecting their new bank. How do consumers seek to establish which of the various banks in the market place would be least likely to cause the same or other problems if a banker— customer relationship were to be commenced? And, which bank would be most likely to give the highest level of satisfaction? In other words, exactly what pulls a consumer towards a certain bank, once the decision to switch has been made? The results of an investigation into this matter would be one that would shed more light on the overall switching process.

The present study suggests that demographic characteristics are unable to distinguish switchers from their counterparts. Not only could further investigations be conducted using the same demographic characteristics to validate or otherwise the findings of the present study, but also appropriate psychographic or behavioural characteristics could be identified and tested in an attempt to distinguish bank switchers from their counterparts.

The six types of incident that were found to influence a switching decision could be tested on a variety of financial service providers (investment advisers, trustees, etc) or even within the various divisions of a banking group (credit card division, international division, etc). This would establish if the financial services sector has or has not a common switching model to explain it.

The lowest ranked switching incident was ‘attraction by competitors’. Given that local banks offer high value prizes in lucky draws, consumer feedback could be sought to establish why such inducements do not cause them to switch in large numbers; and what would be sufficiently attractive to make higher numbers switch.

Finally, there is a need to consider if there are certain types of incident in the current model that would be better divided up under a number of incident headings. This consideration is best directed at the incident entitled ‘service failures’. This incident seems to be wide ranging and the various reasons, which are presently caught by it, may be better classified under more than a single heading.