Information accessibility and disclosure design 80

Research into decision heuristics has found that people’s judgements are often

particular task (Kahneman, 2003; Koriat, 1993; Kusev & Van Schaik, 2011; Tulving

& Pearlstone, 1966). How easily a cue may be retrieved or calculated (its

accessibility) therefore determines, at least in part, how heavily decision-makers

weight it when forming a judgement (Tversky & Kahneman, 1973). This has two

key implications for prescribed disclosure. First, when considering a disclosure

document, decision-makers are more likely to focus on familiar information, or

information which draws their attention, over more valid information. Where this

occurs, the bias is referred to as ‘availability bias’ (Tversky & Kahneman, 1973,

1974). This forms the focus of the first stage of this thesis which investigates how

the design of KFS affects the information borrowers consider when presented with

home loan disclosure (Hoek, Gendall, Rapson, & Louviere, 2011; Söllner et al.,

2013). How availability bias affects which information a decision-maker considers

when examining a disclosure document is discussed below. More broadly, when

searching for information, decision-makers often rely on more accessible

information sources even where they are aware of and have access to more reliable

information (Menzel & Katz, 1955; O'Reilly, 1982). This is considered in the second

stage of the research and discussed in Section 3.2.

As heuristics form judgements based on limited information, the accuracy of

their judgements depends largely on the information borrowers choose to consider.

Prior research shows that the information borrowers focus on is largely affected by

the decision-making task and environment (Todd & Gigerenzer, 2012). Research has

found that heuristics often provide better decisions (in terms of a trade-off between

time and effort and accuracy) than more complex decision processes when there is

(a) a moderate-to-high level of uncertainty surrounding the attributes of an

2007)), and (b) a moderate-to-high correlation between attributes (Dieckmann &

Rieskamp, 2007; Naylor & Schenck, 1968). In particular, positive correlation

between attributes means that the comparison of these attributes will lead to the same

or similar indication of an alternative’s quality. Such correlation may coexist

between multiple attributes, or one attribute in particular may share correlation with

several others (which do not necessarily have to correlate with one another).

Considering attributes which share strong positive correlations with others

allows decision-makers to indirectly incorporate the effect (or part of the effect) the

correlated attributes have on the quality of an alternative without increasing their

cognitive load. This is termed cue redundancy, and occurs where multiple attributes provide overlapping indications about an alternative’s quality, thus reducing or

eliminating the benefit of (and need for) comparing each item individually (Naylor &

Dickinson, 1969). Cue redundancy increases the quality of judgements based on

incomplete information (Bröder, Newell, & Platzer, 2010; Newell & Lee, 2011;

Söllner et al., 2013). The greater the overlap in attributes, the greater the redundancy

in comparing additional correlated attributes. Thus, a product with many highly

correlated attributes (or one attribute that correlates with many others) may be easier

to compare than a product with fewer attributes that do not overlap if the decision-

maker concentrates on the key correlated attribute(s).

Therefore, providing targeted information in a cleaner format significantly

helps borrowers identify and comprehend loan costs (Furletti, 2005, June; Keller &

Staelin, 1987; Lacko & Pappalardo, 2007; Macro International, 2007; O'Shea, 2010)

and improves users’ understanding of the loan agreement (Day & Brandt, 1974;

as using dot points or tables as opposed to text (Hoek et al., 2011; Söllner et al.,

2013), or framing information in a particular way can influence a decision-maker’s

perception of the importance of information, costs or risks (e.g. Bettman, Payne, &

Staelin, 1986; Fischhoff, Slovic, Lichtenstein, Read, & Combs, 1978; Hutton &

Wilkie, 1980). Where applied correctly, formatting can therefore be used to draw

users’ attention to attributes which better represent the overall quality of the

alternative. This, in turn, increases consideration, retention and comprehension of

key information, enhancing decision accuracy without increasing cognitive costs

(Hoek et al., 2011; Malbon, 1999; O'Shea, 2010; Söllner et al., 2013). Careless use

of formatting, however, by making poor quality or decision-irrelevant information

more prominent, may reduce decision accuracy, because decision-makers do not

ignore prominent information even where it forms a poor base for a particular

decision (Platzer & Bröder, 2012).

Studies of Australian consumers clearly demonstrate the impact information

formatting has on the attention they pay to certain attributes. Studies in the health

industry have shown that headlining or outlining structures around key information

is of critical importance because a substantial majority of prescribed drug users were

found to ignore – or, at best, skim read – warning labels (Aiken, Swasy, & Braman,

2004). In finance, excessive or lengthy information, high-level language and poor

formatting of credit disclosure lead to poor understanding of its content (D. G.

Wood, 2006).

Credit cards and home loans industries similarly reflect these results. After

interviewing both lenders and borrowers, (Malbon, 1999) concluded that borrowers

comprehend key costs and features of a loan. Rather than estimating total costs,

borrowers truncate their calculations by basing forecast costs on individual pricing

variables, such as interest rates (Ewing, 2006). O’Shea (2010), who conducted the

formative study for the Commonwealth Treasury White Paper from which the

National Consumer Credit Protection Amendment (Home Loans and Credit Cards)

Bill 2011 is largely derived, similarly noted that several respondents, in the absence

of total cost estimates, gravitated to an offer which emphasised no upfront fees

although it carried higher costs overall.

O’Shea’s study (2010) further emphasised the importance of reframing

disparate loan costs as a single figure for a loan. When the tested disclosure

combined the multiple fees, charges and interest repayments into a single figure,

borrowers were more likely to understand the loan’s cost and avoid bias. Even when

the additional disclosure did not provide the decision-makers with any information

that was not already available to them, its presence enhanced decision-making under

the experimental conditions.

Notably however, O’Shea examines the information which is produced after

the application of the home loan. As noted by the Australian Government, this

information is aimed at helping borrowers to assess their rights and obligations under

the credit contract, not to compare individual loan offers (Australian Government,

2010). Consequently the primary focus of O’Shea’s research, and prior research into

home loan decision-making (e.g. Malbon, 1999; O’Shea & Finn, 2005), has been the

comprehension of the loan costs and other obligations a borrower will face under the

conducted by O’Shea (2010) by examining the quality of information available to

borrowers during the window when they are comparing loans.

The use of information available prior to a formal application for a loan has

two key benefits, in particular. First, it tests the quality of borrowers’ decision-

making based on the information available to borrowers at the time they are

comparing loan offers as opposed to the information available post-application. Here

there is a difference in both the purpose and quality of the information. Therefore, it

is possible that even where borrowers have the same or even lower-quality

information, they may still be able to accurately compare the cost of different home

loan products (e.g. by comparing interest rates). At the same time, however, the pre-

contractual disclosure provided post-application is subject to heavier regulation than

that provided to borrowers during the shopping process. As such, the information

available to borrowers for comparing loans is often more inconsistent in terms of

format, content and terminology, which also stands to reduce borrowers’ ability to

accurately access loan information and select the most cost-effective loan.

Second, the experimental design in Stage 1 adds to the literature by examining

whether the increased comprehension discovered in previous studies applies to KFS.

In doing so, the research looks to determine whether the key principles in effective

disclosure literature have been correctly applied to KFS. This is important because

even slight differences in format and content, such as the inclusion of an irrelevant

photo (Bertrand, Karlan, Mullainathan, Shafir, & Zinman, 2010), can significantly

influence borrowers’ reactions to a disclosure document.

The above literature has informed the research conducted in Chapter 4 which

accuracy of borrowers’ decisions. In doing so it has built primarily towards

informing the first research question:

RQ1: Do KFS help people identify the most cost-effective loan from among a

number of alternatives?

The following sections now turn to the literature surrounding home loan

borrowers’ decision processes to determine the use and role of KFS in practice. In

the process the following section shifts the focus towards understanding the broader

effectiveness of the regulatory approach adopted to enhance borrower decision-

making.

In document The impact of home loan key facts sheets on borrowers' comparisons of loan costs (Page 98-104)