RDP 2018-11: Consumer Credit Card Choice: Costs, Benefits and Behavioural Biases 2. Literature

This paper estimates the net monetary value that consumers gain from holding their credit card, and assesses the potential effect of behavioural biases on this value. There are two streams of literature that are relevant to this analysis. First, literature relating specifically to consumer payments, and second, the behavioural science literature, particularly as it relates to consumers' financial decisions.

2.1 What Do We Already Know about Consumer Card Use?

Credit cards provide two distinct functions to consumers – they are both a means of payment and a source of credit. In addition, many credit cards also offer rewards programs, which provide rewards points or rebates that usually increase in proportion to the amount spent on the card. Both the credit function^[4] and the offer of rewards points provide monetary incentives for consumers to use credit cards instead of alternative payment methods, such as debit cards or cash; in most other respects, credit cards provide very similar functionality to debit cards.

Previous empirical research has confirmed that, as may be expected, these monetary features do encourage consumers to use credit cards over other payment methods.^[5] But they do not fully explain consumers' choice of payment method, and their importance varies across countries. For instance, Carbó-Valverde and Liñares-Zegarra (2011) find that credit card rewards programs have a smaller impact on credit card use in Spain than in Australia (Simon et al 2010) or the United States (Ching and Hayashi 2010).

In Australia, Simon et al (2010) use transaction-level data to estimate that, after holding merchant type, size of transaction and demographic characteristics constant, the presence of a loyalty or rewards program increased the probability of credit card use for a given transaction by 23 percentage points, while access to an interest-free period increased the probability by 16 percentage points.^[6]

More recently, Lam and Ossolinski (2015) estimate consumers' willingness to pay a surcharge to use their card, as a measure of the consumer surplus from card use. This method captures both consumers' estimate of the net monetary benefit from using their card for a given transaction (e.g. rewards points, interest-free period), and the net non-monetary benefit (e.g. convenience, widespread acceptance). They find that respondents vary widely in the value they place on using their card, but in general, those with rewards cards had a higher willingness to pay a surcharge, and this preference persists after controlling for demographic characteristics and stated preferences.^[7]

These findings suggest that the standard rational choice model does help to predict consumers' payment method choices at the point of sale. For instance, when a consumer is faced with the choice of using a credit card, from which they can earn rewards points and receive an interest-free period, or a debit card from which they earn no benefit, consumers are more likely to choose their credit card after controlling for other factors. It is probable that a similar decision process applies to consumers' choice of which type of credit card to hold. That is, we would expect consumers to choose a card that maximises their net monetary benefit.

But while monetary factors help to predict payment choices, they may not be perfect predictors. For instance, consumers may derive non-monetary benefits from their choices. This might mean that even if consumers appear to face net monetary costs from their credit card, they may receive a non-monetary benefit which outweighs these costs.^[8] An additional possibility is that some consumers' decisions are influenced by principles of behavioural economics. Growing academic evidence suggests that consumers may be particularly susceptible to these biases at the time they choose which credit card to hold.

2.2 What Are the Potential Behavioural Biases?

The monetary benefit that consumers receive from their credit card depends both on the way they use their card and on the particular card they choose. To make an optimal card choice, consumers must first accurately estimate their own expected card use. Then, based on that expectation, consumers can choose the card that best suits their needs. Existing evidence suggests consumers' actual choices can systematically deviate from this optimal decision process.

First, consumers may have difficulty accurately estimating their expected card use. Some evidence suggests that consumers possess an ‘optimism bias’, systematically underestimating their likely card expenditure and their probability of incurring interest charges.^[9] If, at the time of choosing their card, cardholders do not expect to incur interest charges (e.g. by underestimating their likely spending, or overestimating their future income and ability to repay), the interest rate is unlikely to factor into their decision and they may choose a high-rate credit card (Ausubel 1991; Calem and Mester 1995; Yang, Markoczy and Qi 2007). If that expectation turns out to be a systematic underestimation, these consumers will face substantially higher interest charges than if they had chosen a lower-rate card.

Second, identifying an appropriate card, given expected card use, can be a complex decision. Cards vary in their annual fees, interest rates, generosity of their rewards program, the number of interest-free days they offer, and the size of ad hoc fees – for example, late payment fees (Brainard 2017). This complexity can make the card choice computationally difficult. Consumers may be subject to ‘bounded rationality’, and may rely on heuristics (or simple rules of thumb) instead of attempting to compare their options across all dimensions. For instance, if consumers focus on some of the more salient or more widely-advertised features of the product (such as rewards points), bounded rationality may lead them to overweight the value of rewards points relative to the card's annual fee.

Consumers have been found to display bounded rationality in making these types of complex choices; for instance, in recent research on mobile phone plan choice in Australia. Using experimental data, Friesen and Earl (2015) find that consumers make significantly worse decisions when faced with complex tiered pricing schemes; for instance, where the included dollar value in the plan is different from the amount paid (e.g. a $30 monthly fee with $300 ‘included value’). But they also find that performance depends on consumers' level of expertise, with those who were already knowledgeable about phone plans making better choices. If extrapolated to the credit card market, we may expect a similar dynamic, especially in cardholders' estimates of the value of rewards programs. Rewards programs often reflect a similar multi-tier pricing structure, with no direct comparison between the number of rewards points and their dollar value.

Third, consumers' choice of credit card may also be affected by sign-up offers. If consumers are ‘present-biased’, they may respond to short-term sign-up offers of balance transfer deals, bonus rewards points, or discounted annual fees to choose a card that is relatively costly after those offers expire, leading to higher long-term costs.^[10] Present-biased preferences are different from a standard economic model of exponential discounting because they imply some form of dynamic inconsistency – that is, if asked to choose a card for immediate use, present-biased consumers would be more likely to choose a card that has near-term benefits and longer-term costs. But if they were choosing a card today that they would start using in one year's time, they would choose differently.

Evidence of present bias in responding to credit card sign-up offers has been found in the US market. In an experiment, a credit card issuer sent card solicitations with varying introductory interest rate offers to 600,000 consumers (Shui and Ausubel 2005). They found that consumers were significantly more likely to respond to offers with a lower-rate introductory offer lasting just a few months than to offers of a slightly higher introductory rate that lasted longer. This led to higher long-term costs for many of those responding to the short-term offer, who continued to use their card to borrow at the higher interest rate long after the introductory offer had expired. Relatedly, descriptive evidence from Australia suggests that, between 2012 and 2017, around one-third of cardholders who responded to balance transfer deals had higher levels of debt after the offer had expired, suggesting some may have fallen into a ‘debt trap’ (ASIC 2018).

Of course, the effects of the three potential behavioural factors outlined above would only be noteworthy in the presence of substantial cognitive or practical barriers to switching cards. In the absence of any barriers, consumers would realise that they are making an avoidable loss, and switch to a lower-cost card.

In addition to potential practical barriers to switching cards (e.g. search costs, time spent applying for a new card and transferring any direct debits), there may also be behavioural barriers. Consumers may face similar behavioural barriers as with their initial card choice: optimism bias may lead consumers to believe that they will reduce their spending and eliminate interest charges in future, even if they systematically fail to do so; bounded rationality may limit their awareness of better deals and their ability to estimate the potential gain from switching. In addition, particularly if there is some uncertainty over the costs of switching and the value of alternatives, cardholders may exhibit a status quo bias towards their current card, even if it is not an optimal choice (Samuelson and Zeckhauser 1988; Kahneman, Knetsch and Thaler 1991).

A further possibility is that consumers who already experience significant financial stress could be more likely to make sub-optimal financial choices because of this stress (Kell 2016). This tendency is known as ‘cognitive scarcity’. A negative impact of cognitive scarcity due to financial stress has been found in other contexts; for instance, Mani et al (2013) found that low-income consumers, who are more likely to face financial stress, performed similarly to high-income consumers on a cognitive test in normal conditions. But their performance was significantly worse if they were ‘primed’ to think about financial stressors before taking the test, while high-income consumers were unaffected by the priming. If a similar effect is present for some credit card holders, it may help to explain continued use of cards with high net costs, even if lower-cost alternatives are available.

Footnotes

On most cards, consumers may borrow for up to two months interest free; during this period, consumers receive a monetary benefit from the interest-free loan, for instance, by earning interest on their savings or paying down higher-interest debts, rather than paying for their purchases upfront. [4]

In addition, but outside of the scope of this paper, some evidence suggests that using a credit card can lead consumers to increase their total spending. This effect may be driven by an alleviation of liquidity constraints, or by behavioural factors (Thomas, Desai and Seenivasan 2011; Chatterjee and Rose 2012). [5]

Simon et al (2010) explore the possibility of endogeneity, noting that consumers self-select into holding a rewards card, potentially based on unobserved preferences to use credit, and this self-selection may upwardly bias their estimates. They conclude this is less of a concern in their case. [6]

Adding stated preferences to the regression helps to control for potential unobserved factors relating to self-selection into holding a rewards credit card (Ching and Hayashi 2010). [7]

However, our survey data suggest that most respondents place a very small value on non-monetary benefits and are primarily motivated by monetary features when they choose their card (see Appendix A). [8]

Similarly, cardholders may be myopic and fail to consider the possibility of interest payments at all. The effects would be the same. [9]

Some consumers may also sign up expecting to review their choice when the offer expires, but subsequently forget, or delay doing so. [10]