RDP 2018-11: Consumer Credit Card Choice: Costs, Benefits and Behavioural Biases 7. Barriers to Switching

While my estimates of consumers' net monetary benefits under an ‘optimal’ card choice (Section 5.3) suggest that most cardholders would be better off if they held a different credit card, only a relatively small number of cardholders switch cards. Around 7½ per cent of cardholders in the Consumer Payments Survey reported having switched their main credit card in the year prior to the survey. This share was marginally higher (9 per cent) for those who I estimate to be making a loss on their card, but the difference is not statistically significant.

These patterns suggest that cardholders may face some barriers to switching cards.[44] These barriers might be less binding for those who break even or receive a net monetary benefit from their card; they may feel no impetus to switch cards, even if they could receive a larger net monetary benefit if they did so. But we might expect that more than 9 per cent of those who make a loss – most of whom were aware they were making a loss – would want to switch to a lower-cost alternative. Respondents' stated preference to hold a credit card with their main or preferred bank (see Figure 2) may explain part of this reluctance to switch, though most banks offer a range of options, meaning that cardholders are able to switch to a lower-cost card issued by the same bank.

There are a number of possible reasons that respondents who make a loss might not switch cards. First, while I estimate that most cardholders would benefit from switching, for some, these benefits could be modest. For instance, cardholders who are paying interest and already have a relatively low-rate card may consider that any gain from switching cards could be outweighed by the time costs involved. In addition, a small number of cardholders state that they receive non-monetary benefits that they believe outweigh the monetary costs of their card (survey respondents were not asked to specify the nature of these benefits, see Appendix A). Collectively, these reasons appear to apply to just under 30 per cent of loss-making cardholders (Table 8).

A second explanation is that respondents may consider switching cards, but run into practical barriers and decide not to follow through. For instance, they may have found that they were ineligible for a lower-cost card, or may have investigated their options and decided that the cost of switching, in terms of the administrative burden and time involved, potentially including establishing a relationship with a new bank or card issuer, was too high.[45] This appears to be the case for a relatively small share of respondents (Table 8). Overall, around one in five cardholders had considered switching cards in the past year but had not followed through. Subtracting the respondents who already held a lower-rate card and who value the non-monetary benefits of their current card from this share, I estimate that these practical barriers could apply to up to 16 per cent of loss-making respondents.[46]

Table 8: Loss-making Respondents
2016
  Share of loss-making cardholders (%) Net monetary loss ($) Share who considered switching (%) Median annual fee ($) Median interest rate (if paid interest) (%)
Median Interquartile range
Switched card(a) 9 209 324 to 89 100 99 14
Already holds suitable card
Pays interest, has a lower-rate card 25 224 862 to 81 36 59 13
Values non-monetary card features 3 284 284 to 85 63 95 20
Not holding suitable card and
Considered switching 16 170 369 to 87 100 95 20
Did not consider switching – potential behavioural reasons 47 170 341 to 82 0 95 20

Note: (a) Net monetary loss figures shown relate to the respondent's new card, which was their main credit card at the time of the survey

Source: Author's calculations, based on data from Ipsos and RBA

The above reasons appear to collectively apply to around half of loss-making respondents. The remaining half, therefore, appear more likely to face behavioural, rather than practical, barriers to switching. These consumers held cards with above-average fees or interest rates and they did not report that non-monetary features outweigh the monetary costs of their card, but they had not considered switching cards in the past year (Table 8). On average, these respondents made a median net monetary loss of $170, but with a wide range around that average. Their median loss would have been $230 lower had they chosen their ‘optimal’ card (as defined in Section 5.3).

There could be a range of reasons why respondents who did not appear to be holding a suitable card did not consider switching. It may be that these consumers were not aware of, or underestimated, the potential benefits from switching. Alternatively, they may have been aware of the potential benefits of switching, but faced behavioural barriers, such as status quo bias, present bias or cognitive scarcity, that prevented them from following through with researching and switching.

The survey data do not allow for identification of which, if any, of these potential behavioural explanations was the most important reason that these respondents did not consider switching cards. However, I find that the respondents who were more likely to consider switching (and more likely to actually switch) cards were those with higher incomes and higher levels of education.[47]

As may be expected, respondents who perceived that they were making a loss were more likely to consider switching cards than those who were not aware that they were making a loss (Table E1). While the estimates are imprecise, the effect of making a perceived loss appears to increase with income, with higher-income respondents who perceived they were making a loss being more likely to consider switching cards (Figure 13; see Appendix E for full regression results).[48] This difference across income levels may reflect differing options available to these different types of respondents; perhaps some low-income respondents do not consider switching because they do not believe it will be possible to find a card with lower costs. It may also reflect levels of financial literacy, or it may reflect behavioural biases, whose negative impact may be largest for consumers who use their card to borrow money (typically lower-income, liquidity-constrained individuals).

As noted in Section 2.2, one potential behavioural barrier to switching cards may be cognitive scarcity due to stress, which can impair consumers' ability to make optimal choices. Cognitive scarcity, or limited mental ‘bandwidth’, may lead consumers with pre-existing stressors to choose, and retain, cards that are inappropriate for their needs. For a small number of respondents, the stress itself may be caused by credit card debt, which may lead them to focus narrowly on repaying current debts, rather than taking steps – such as switching cards – to reduce future interest charges. Literature seeking to identify the effect of cognitive scarcity due to stress has generally focused on low-income consumers, who are most likely to face financial stress (Mullainathan and Shafir 2013). This effect may therefore help to explain why higher-income cardholders were more likely to devote time and mental bandwidth to considering switching cards.

Figure 13: Effect of Perceived Loss on Probability of Considering Switching – By Income
Marginal effect of perceived monetary loss from credit card, 2016
Figure 13: Effect of Perceived Loss on Probability of Considering Switching

Notes: Probit model, includes demographic controls; bands show 95 per cent confidence intervals

Source: Author's calculations, based on data from Ipsos and RBA

Footnotes

Similar observations have been made about bank account switching more broadly. For a recent discussion of account switching arrangements and the potential barriers to switching in Australia, see Fraser (2011). [44]

These costs may include searching for and identifying a new card, applying for the card (for which some consumers may need to provide documentation or visit a branch), switching any direct debits or other automatic payments to the new card, and closing the previous card's account. [45]

Some of these respondents may have considered switching cards, but not followed through for ‘behavioural’, not practical, reasons – potentially due to cognitive scarcity, present bias or status quo bias. I am unable to separate out these reasons in the survey data. [46]

These observations are based on a probit model of the probability of considering switching on a range of demographic factors (see Appendix E). The unconditional effect of income is significant and large, but this effect declines in both significance and magnitude after adding controls. Results are similar when the probability of considering switching is modelled as a two-stage process (accounting for self-selection into holding a credit card using a Heckman sample selection model, see Table D2). This finding suggests that the relationship between switching behaviour and income may be due to both observed and unobserved characteristics of high-income cardholders. [47]

This finding relates to the relationship between income and switching behaviour within the sample of credit card holders. In this regression I do not use the Heckman selection model mentioned above. [48]