Evaluation Paper 18/1: An
evaluation of our guaranteed
asset protection insurance
intervention
July 2018
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
We welcome views on this Evaluation Paper.
You can send them to us by email at evalu[email protected] or in writing to:
Economic and Financial Analysis Department, Strategy & Competition Division, Financial
Conduct Authority, 12 Endeavour Square, London, E20 1JN.
Authors
Jennifer Brauner, Lawrence Charles, Jasjit Sansoye and Lachlan Vass.
The authors work in the Economic and Financial Analysis Department at the FCA.
Acknowledgements
We are grateful to Sumit Agarwal for his academic peer review, advice, and guidance. We
would like to thank PwC Research for conducting the consumer survey.
All our publications are available to download from www.fca.org.uk. If you would like to
receive this paper in an alternative format, please call 020 7066 9644 or email
publications_graphics @fca.org.uk or write to Editorial and Digital team, Financial
Conduct Authority, 12 Endeavour Square, London, E20 1JN.
FCA Evaluation Papers
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
Executive summary 1
1 Why we are evaluating our guaranteed asset protection insurance
intervention 6
2 Our evaluation approach 10
3 Results: Market context analysis 17
4 Results: Sales analysis 22
5 Results: Price analysis 30
6 Results: Consumer survey findings 38
7 Results: Overall effects 49
8 Lessons learned 55
Contents
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
1
Evaluating the impact of our add-on guaranteed asset protection
(GAP) insurance market intervention
Evaluations inform our decision-making
Evaluation is part of our Mission’s decision-making framework. Testing the effectiveness
of our remedies helps us make better decisions.
In April 2018, we published Discussion Paper 18/3 on our proposed framework for post-
intervention impact evaluations. This is one of the ways we assess the impact of our
interventions. Post-intervention impact evaluations differ from other approaches as they
focus on quantifying the impact of our intervention.
1
In our 2018/19 Business Plan and the proposed evaluation framework, we said that we
would conduct 3 pilot evaluations to measure the impact of past interventions in a way
that controls for factors that may have influenced the market.
An evaluation of our September 2015 add-on
2
GAP insurance intervention is part of this
pilot.
What is GAP insurance?
GAP insurance is predominantly sold as an add-on when someone buys a vehicle. It
provides cover for a financial shortfall that can happen when:
• a customer’s vehicle is written off or stolen
• the motor insurance pay-out does not pay back its original value at purchase or the
remaining finance value (if the vehicle was bought on finance)
Our 2014 market study highlighted concerns about add-on GAP
insurance
In July 2014, we published the final report from our general insurance add-on products
market study. The study found consumer harm in the add-on GAP insurance market.
It
estimated total consumer overpayment for add-on GAP insurance of around £76 million
to £121 million a year (out of an estimated market size of £152 million).
We found that:
• vehicle sellers enjoyed a strong point-of-sale competitive advantage, meaning that
there was little or no pressure on sellers to lower the price
• a lack of information, including about alternative providers, prevented consumers
from being able to compare products
• many consumers did not know that they could buy GAP insurance separately
(‘standalone’) elsewhere, often at a lower price
1
The proposed framework sets out how we intend to use ex post impact evaluation (EPIEs), or post-
intervention impact evaluations, to assess the impact our interventions have had on consumers, firms and
markets. Evaluations feed back into our decision-making and how best to use our diagnostic and remedy tools.
2
Consumers can buy GAP insurance when buying a vehicle (add-on) or separately (standalone).
Executive summary
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
2
• as with other add-on products, consumers’ focus on the main product (in this case,
the vehicle) led to many buying add-on GAP insurance when they may not have
wanted and/or needed it
We introduced measures to deal with these concerns
To address this, we intervened in 2015 by:
• making it mandatory for vehicle sellers to provide sufficient information to consumers
• requiring a pause in the sale (‘deferred opt-in’), meaning that vehicle sellers can start
the sales process but cannot conclude the GAP insurance sale for 2 clear days
We believed that having both time and information would enable consumers to decide
whether they need GAP insurance, and to shop around if they do.
We expected:
• improved competition between add-on and standalone sellers
• better consumer outcomes during the purchasing process, including:
– an overall decrease in add-on GAP insurance sales, given our concern about
consumers buying, potentially, unsuitable add-on products
– more consumers shopping around and buying GAP insurance from standalone
providers
Evaluation relies on a range of evidence
Our evaluation follows the post-intervention impact evaluation framework’s high-level
approach and focusses on quantifying the impact of our intervention. We do this with
reference to our pre-intervention expectations, which are based on the cost benefit
analysis (CBA) in the GAP insurance Consultation Paper (CP14/29).
3
Figure 1 summarises our evaluation approach. We use a mix of transaction-level data,
consumer survey insights, other publicly available data, and insight from firms and trade
bodies to evaluate the impact of our intervention. To understand these data, we conduct
descriptive statistical and econometric analysis.
4
3
A post-intervention impact evaluation does not consider all aspects of the intervention or re-run a CBA.
For example, compliance costs are not a central focus of our analysis, though we do present some high-level
figures as provided to us by the National Franchised Dealers Association (NFDA).
4
We do this to diagnose the relationship between: a data series of interest (eg sales volumes); and a
range of factors that affect these data series at the same time. This approach helps us to isolate, given a level of
statistical confidence, the underlying correlation between many variables and the one of interest.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
3
Figure 1: Our evaluation approach
Source: FCA
Our intervention has had a positive impact, but less than we
expected before intervening
Overall, we find that our GAP insurance intervention has had a positive impact. We
summarise our main findings in Figure 2.
After our intervention, consumers are more engaged decision-makers and shopping
around has more than doubled. Add-on GAP insurance sales are 16% to 23% lower than
they would have been without our intervention. Some of the reduction in add-on sales is
accounted for by higher standalone sales, which have increased from 6% to 8% of all
GAP insurance sales. The evidence suggests that some consumers decide, on reflection,
not to go ahead with the purchase.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
4
Figure 2: Our main results
Source: FCA
Our intervention has helped to reduce considerable harm in the market. We estimate that
there are around £26 million to £28 million of ongoing consumer benefits a year after our
intervention. This exceeds firms’ total costs of implementing our intervention, including a
one-off cost of £5 million to £8 million and an ongoing cost of £1 million a year.
Our intervention has achieved its objectives, although not by as much as we expected.
Due to our intervention, we expected that:
• add-on sales would be up to 32.5% lower
• the share of sales of standalone would increase to up to 40%
• add-on prices would be up to 17% lower, with the price differential between add-on
and standalone narrowing
In particular, the impact on the standalone’s share of total sales and on add-on prices
has been much less pronounced than we expected.
Our findings are consistent with recent academic literature on demand-side interventions.
The literature indicates that although well-designed demand-side remedies can be
effective, their impacts tend to be modest. That said, even modest impacts can represent
significant gains for consumers.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
5
Lessons learned
We view evaluations as an opportunity to learn from previous interventions and to feed
any insights into our current and future work.
The main lessons we learned from this evaluation are:
• This intervention had a far greater impact on sales than prices:
– In the case of sold products (goods or services a consumer was unaware of before
the seller introduced them) with a point-of-sale advantage, we are likely to reduce
total purchases, rather than diverting consumers to the non-point-of-sale market,
if we try to break the point-of-sale advantage
– Add-on sellers play an important role in introducing the product to buyers, so the
standalone market might be smaller in their absence
• Pre-intervention expectations should be based on a range of evidence. Our consumer
survey overstated the impact of the intervention on switching to the standalone
market, and underestimated the number of consumers who would make a more
considered purchase given the information and time to do so. This evaluation will
help to provide useful evidence when thinking about similar future interventions.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
6
This section provides an overview of the intervention that we evaluate in this report. We
also set out the report’s scope and structure.
What is guaranteed asset protection (GAP) insurance?
GAP insurance is predominantly sold as an add-on when someone buys a vehicle. It
provides cover for a financial shortfall that can happen when:
• a customer’s vehicle is written off or stolen
• the motor insurance pay-out does not pay back its original value at purchase or the
remaining finance value (if the vehicle is bought on finance)
Figure 1.1 gives an example of how this might work.
Figure 1.1: How GAP insurance works
Source: FCA
GAP insurance is available for new, used, leased, business-owned and privately-bought
vehicles. Consumers can buy GAP insurance in connection with buying the vehicle (an
add-on buy) or separately (a standalone buy).
1 Why we are evaluating our
guaranteed asset protection
insurance intervention
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
7
Our concerns about add-on GAP insurance
In July 2014, we published our general insurance add-on products market study final
report, examining how selling general insurance products as an add-on to a primary
product affects competition.
The study found significant consumer harm in the add-on GAP insurance market.
We
concluded that consumers received poor value for money from this product.
We found that:
• on average, only £10 in every £100 paid in add-on GAP insurance premiums was paid
out in claims (ie an average ‘claims ratio’ of 10%, which was much lower than other
general insurance products
5
) between 2008-2012
6
,
• of the 5 add-on products considered, GAP insurance accounted for over half of the
estimated overpayment of add-on premiums
7
• consumers often bought add-on GAP insurance without having previously thought
about the product or shopped around for alternatives
8
We set out the following reasons for these findings:
• vehicle sellers enjoyed a strong point-of-sale competitive advantage, meaning that
there was little or no pressure on them to lower the price
• a lack of information, including about alternative providers, prevented consumers
from being able to compare products
• many consumers did not know that they could buy GAP insurance separately (as a
standalone), often at a significantly lower price, elsewhere
• similar to other add-on products, consumers’ focus on the main product (in this case,
the vehicle) led to many buying add-on GAP insurance when they may not have
wanted and/or needed it, with the add-on mechanism weakening consumers’
decision-making and engagement
9
We introduced measures to deal with these concerns
In 2015, we proposed 2 measures for add-on GAP insurance sellers to address the
identified harm:
1. Providing written information on GAP insurance (‘prescribed information’). This means
that add-on GAP insurance sellers (also known as distributors) must provide
information to potential buyers. This should encourage consumers to shop around,
including by advising them that they can buy the product elsewhere.
5
We used a conservative estimate of a competitive baseline using other general insurance products of
30% to 50% for a claims ratio. This was based on the 2012 average claims ratio for general insurance products
of 64%. Guaranteed Asset Protection insurance: a competition remedy, CP14/29, page 5
6
General insurance add-ons: Provisional findings of market study and proposed remedies, MS14/1, Table
5.1
7
£76 million to £121 million a year of the estimated total overpayment across five add-on insurance
products – travel, personal accident, home emergency, GAP, and gadget – of £108 million to £216 million a year).
GAP insurance was c.30% of the estimated add-on market size of the five products considered. General insurance
add-ons: Provisional findings of market study and proposed remedies, MS14/1, Table 6.1
8
General insurance add-ons: Provisional findings of market study and proposed remedies, MS14/1, page
56
9
General Insurance add-ons: Final report – confirmed findings of the market study, MS14/1
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
8
2. A pause in the sale (‘deferred opt-in’). This means that add-on GAP insurance sellers
can start the sales process but cannot conclude the GAP insurance sale for a set
amount of time (2 clear days)
10
. This gives consumers time to consider whether they
need the product at all and to shop around if they do.
These measures came into force on 1 September 2015. We believed that these tools
(time and information) would enable consumers to better assess whether they needed
GAP insurance and to shop around if they did.
As a result of our intervention, we expected:
• improved competition between add-on and standalone sellers of GAP insurance, with
standalone sales increasing relative to add-on sales
• better consumer outcomes, namely better-informed and more active decision-making
during the purchasing process
Assessing the impact of our GAP insurance intervention
As stated in our Mission, evaluation is a critical part of getting our interventions right.
Finding out what impact past interventions have had helps develop a strong evidence
base to guide our decisions.
11
These decisions can include which issues to prioritise and
how best to intervene to tackle harm.
We published a proposed framework outlining the way we measure the causal impact of
our interventions in April 2018. The framework explains:
• why we do post-intervention impact evaluations
12
• how we choose specific interventions to study
• how we ensure that our evaluations are robust, impartial, and, therefore, credible
This report follows the proposed approach to post-intervention impact evaluations, and is
one of three pilot evaluations. We chose it, in part, because the deferred opt-in element
was a novel measure to address the harm found in the FCA’s first market study.
The aim of this work is to understand:
1. the impact of the 2 measures
2. whether the intervention met its objectives
3. whether our pre-intervention cost benefit analysis (CBA) was able to accurately
capture the scale of the intervention’s impact
We focus on the main expected changes after our intervention. As set out in the
proposed evaluation framework, we do not re-run our pre-intervention CBA.
10
Consumers can make contact with the vehicle seller to complete the GAP insurance sale the day after it
is introduced.
11
We note that: i) FSMA requires us to have regard to the FCA exercising its functions as transparently as
possible when making policy; and ii) the principles for regulators under Legislative and Regulatory Reform Act
refer to regulators being both transparent and accountable.
12
We refer to post-intervention impact evaluations, or ex post impact evaluations, as ‘evaluations’ in this
report.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
9
Report structure
We structure this report as follows:
• Section 2 sets out an economic framework for this evaluation
• Section 3 summarises the market context
• Sections 4 and 5 show what has happened to GAP insurance sales and prices,
respectively, before and after our intervention (with further details of the analysis set
out in the Technical Annex)
• Section 6 looks at possible explanations behind our findings through a consumer
survey (with further details of the analysis set out in Annex 2 and Annex 3)
• Section 7 comments on how overall outcomes have changed in the market after our
intervention
• Section 8 concludes with the main lessons that we have learned from this evaluation
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
10
This section sets out how we evaluate our GAP insurance intervention, including:
• how we expected our intervention to work
• the available evidence on compliance
• the pre-intervention expectations we tested to see how well our intervention has
worked
• the methods and data that we used to test these pre-intervention expectations
How we expect our intervention to work
Figure 2.1 below sets out a causal chain of our GAP insurance intervention. A causal
chain, pathway, or logic model in this context describes the way that an intervention
addresses the identified market failure and reduces harm, leading to costs and benefits.
It does this by linking the intended intermediate and final outcomes with the intervention
inputs, activities, processes, and theoretical assumptions.
Figure 2.1 shows how our 2 measures achieve the intervention’s intended objectives.
2 Our evaluation approach
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
11
Figure 2.1: Causal chain of our 2015 GAP insurance intervention
Source: FCA
We have developed the evaluation approach, set out in this section, with reference to
Figure 2.1.
Evidence suggests that firms have implemented the measures
The first stage in Figure 2.1 is to consider the evidence on how far firms have broadly
complied with our intervention (process evaluation).
Evidence on compliance is important for supporting the causality in our analysis. But we
need to be careful how we interpret any lack of evidence or widespread non-compliance:
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
12
1. No knowledge about compliance: If we had no information on compliance and our
intervention appeared to have had no impact, it might be that nobody complied with
our intervention. Our conclusion about the intervention’s efficacy would then be based
on an incomplete evidence base and could be wrong.
2. Evidence of widespread non-compliance: Our estimates may understate
13
the
intervention’s potential impact, which could have been greater if more firms had
complied.
Our focus has been on establishing an evidence base on compliance so we can conclude
whether there is widespread non-compliance. We do not need to know whether there is
100% compliance to draw valid conclusions.
For the GAP insurance measures, we have considered a range of evidence, including:
• transaction-level data from firms, capturing dates to understand the deferred opt-in
measure’s implementation
• consumer survey insights, capturing both measures (see Section 6)
• existing work and knowledge within the FCA’s Supervision division
• informal engagement with firms and trade associations
Based on the available evidence, there does not appear to be widespread non-compliance
with our intervention. We are confident that our findings are not influenced, at least to a
material extent, by a lack of compliance.
We test our intervention against our expectations
To see how well our intervention has worked, we begin by testing outcomes against our
pre-intervention expectations (see Table 2.1). These are based on Figure 2.1.
But this analysis would not isolate the impact of the intervention. This is because we
need to assess how well our intervention has worked relative to what would have
happened without it. This is our counterfactual. For many reasons, it can be hard to
identify a counterfactual so we highlight these instances throughout the report. In these
cases, we provide reasons why we cannot establish a counterfactual, and an analysis of
how the market has changed over time (ie a non-causal analysis).
Having considered the effects above, we assess the benefits of our intervention and
compare them to the costs.
There are many other ways to measure the impact of an intervention beyond expressing
the costs and benefits in monetary terms. We base the pre-intervention expectations in
Table 2.1 on a series of measurable metrics, such as sales volumes, prices, and
consumers’ survey responses.
These metrics are helpful in assessing our intervention’s impact. But they should be
considered with this market in mind. If, for example, consumers are shopping around
more after our intervention, then this is likely to be a positive development. This does
not mean that, to its extreme, we think that all consumers should shop around in this
market (or any market). Throughout the report, we present our view of what has
13
It could overstate the intervention’s impact if the analytical approach did not control for other market-
wide changes that may have influenced, for example, add-on GAP insurance sales. We use econometric
techniques to isolate the impact of the intervention from other changes. Hence, we do not consider that this is a
likely outcome.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
13
happened to these metrics. We do this to show whether observed changes after our
intervention are, in our view, positive or negative outcomes.
Table 2.1 sets out these pre-intervention expectations. Each row in Table 2.1 sets out:
• a question that, when answered, will help understand the extent to which our
intervention has worked
• our pre-intervention expectation, as informed by the CBA
• where, in this report, we present findings from our analysis to address the question
Table 2.1: Questions to answer and pre-intervention expectations to test
#
Question to
answer
Pre-intervention expectation
Report
section
where we
present
findings
1
Has the share of
add-on GAP
insurance sales to
total GAP insurance
sales decreased?
For a given number of GAP insurance sales (which was
based on the total number of car sales), the share of
add-on GAP insurance sales to total GAP insurance
sales falls.
This means that the share of standalone GAP insurance
sales increases.
4
2
Has the share of
add-on GAP
insurance sales to
car sales decreased?
Our pre-intervention CBA assumed, implicitly, that car
sales would remain constant.
Our intervention reduces add-on GAP insurance sales
(all other things being equal).
It does this in two ways:
• some people choose not to buy the product
• some people switch to standalone GAP insurance
14
Hence, the share of add-on GAP insurance sales to car
sales falls.
4
3
What has happened
to add-on and
standalone GAP
insurance prices?
The price of add-on GAP insurance either:
• does not change, or
• falls
15
because of lower demand after our
intervention, partly due to increased competition
from the standalone market
16
We set no pre-intervention expectation about the price
of standalone GAP insurance. Hence, it stays the same.
5
4
What has happened
to the average
17
GAP
insurance market
price?
This depends on what has happened to:
• the share of sales between add-on and standalone
GAP insurance
• prices in the individual segments
Based on pre-intervention expectations 1-3, the
average market price falls.
5
14
There were 600,000 add-on GAP insurance sales a year in our pre-intervention CBA. We estimated that:
i) 10% (60,000) sales would be lost due to add-on consumers no longer buying GAP insurance at all; and ii)
22.5% (135,000) add-on sales would move to the standalone market (under the ‘no price change’ scenario).
Hence, we estimated that 32.5% of add-on GAP insurance sales would no longer take place owing to our
intervention.
15
Our pre-intervention CBA set out two scenarios for add-on GAP insurance prices: i) no price change; and
ii) a fall in price of 16.7%.
16
Even if there are factors such as adverse selection that might lead to, on average, riskier purchasers
buying the product following our intervention.
17
In this report, we use the mean as our average measure unless we state otherwise.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
14
5
What has happened
to consumers’
likelihood of
shopping around?
More people shop around (our pre-intervention CBA
estimated this at around 25% of add-on GAP insurance
consumers).
As a result, more people buy the cheaper standalone
GAP insurance.
6
6
What has happened
to consumer
engagement and
awareness of GAP
insurance after our
intervention?
Consumers are more aware of the product and engage
more with the purchasing process than they did
before.
18
6
7
What has happened
to consumer
understanding of the
add-on GAP
insurance product?
This was not explicit in the pre-intervention CBA. But it
is a matter of interest for the post-intervention analysis.
Add-on GAP insurance consumers understand the
product better than before. Product understanding no
longer differs materially between add-on and
standalone GAP insurance consumers.
6
8
What has happened
to consumer surplus
after our
intervention?
Consumer surplus
19
increases after our intervention,
relative to a ‘no intervention’ scenario.
In the pre-intervention CBA, we estimated this to be in
the region of £31 million to £54 million a year.
7
9
What has happened
to the average add-
on GAP insurance
claims ratio?
This was not explicit in the pre-intervention CBA. But it
is a matter of interest for the post-intervention analysis.
The add-on GAP insurance claims ratio increases.
This assumes that, all other things being equal, add-on
GAP insurance prices have fallen.
7
10
What were the costs
of complying with
the intervention?
Our pre-intervention CBA estimated the one-off
compliance costs to be between £2 million and £5
million. This was revised upwards after consultation to
fall between £5 million and £20 million, with minimal
ongoing compliance costs.
One-off compliance costs are in line with this revised
figure. Ongoing compliance costs are minimal.
7
Source: FCA
We use various methods and data to test these pre-intervention
expectations
The rest of this section sets out the different methods and data used to test the pre-
intervention expectations in Table 2.1.
Table 2.2 summarises the analytical methods we used for each pre-intervention
expectation (ticks indicate method used). We also use qualitative insights from
stakeholder (eg firms, trade bodies) engagement across most of the pre-intervention
expectations. This helps us understand the impact of our intervention from firms’
perspective and provides a valuable sense-check of our data analysis.
18
In our pre-intervention CBA, we considered that around 30% of add-on GAP insurance consumers who
did not shop around pre-intervention would do so post-intervention (based on their answers to a consumer
survey).
19
Consumer surplus is an economic measure of consumer benefit. It is the difference between the highest
price that a consumer is willing to pay and the price set by a firm for a good or service.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
15
Table 2.2: How we address each pre-intervention expectation
Pre-
intervention
expectation
#
a) Descriptive
statistics
b) Econometric
analysis of firms’
data
c) Consumer survey
insights
1
✔
✔
2
✔
✔
3
✔
✔
4
✔
✔
5
✔
6
✔
7
✔
8
✔
9
✔
10
✔
Source: FCA
We explain these methods in further detail below.
a) Descriptive statistics
Descriptive statistics provide context on what has happened in the market. They set out
overall trends and changes after our intervention. We can, therefore, see whether our
intervention is associated with changes in the market.
We collected GAP insurance transaction-level data from 41 firms (underwriters
20
and
distributors
21
) operating in the GAP insurance market.
22
These data covered the period
between September 2013 and August 2017 (ie two years either side of the intervention
date).
We also requested data on complete wheel protection (CWP) from firms selling
23
GAP
insurance. CWP is an add-on product that covers tyre and alloy wheel repair costs. We
did this to help build our counterfactual.
Our Technical Annex sets out further details about the data that we collected from firms
and how we have used them.
We summarise these data using summary statistics, charts, and tables throughout the
report. When doing this, we present any currency-based data (eg prices, economic
variables such as income) following an adjustment for inflation (ie in real terms).
24
20
Underwriters take on the insurance risk and meet the obligations of paying out if a consumer makes a
successful GAP insurance claim.
21
Distributors provide GAP insurance either directly to consumers (ie standalone) or to the final retail seller
(eg a vehicle dealership).
22
We did not request data from vehicle dealers, but we know which dealers sold GAP insurance in our
data. The Technical Annex outlines our approach in further detail.
23
Firms distributing or underwriting CWP policies.
24
When diagnosing how changes in price levels affect the consumption of a product or service, it is common
practice to strip out the effects of general inflation and express price changes in ‘real terms’. That is, changes in
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
16
b) Econometric analysis of firms’ data
Econometric analysis helps us diagnose whether there is evidence that our intervention
has led to changes in the market.
We use a specific type of regression model to help identify our intervention’s causal
impact on sales and prices. A difference-in-difference (‘DiD’) model compares how trends
in outcomes change between ‘treated’ (ie affected by an intervention) and ‘untreated’ (ie
unaffected by an intervention) groups over a period relevant to the intervention.
Unobserved factors might affect the outcome. But, if they do not affect trends in the
outcome, then the trends for both groups in the absence of a policy will be the same. It
is a well-known, often-used econometric approach when evaluating policy
interventions.
25
We use CWP as our untreated product to compare to add-on GAP insurance, which is the
treated product. CWP was not affected by our intervention (see further explanation in the
Technical Annex).
c) Insights from consumer surveys
The results from consumer surveys help us to understand why we see the outcomes from
the analytical approaches set out in a) and b).
We build on answers to GAP insurance-specific questions in our 2017 Financial Lives
Survey by presenting findings from a consumer survey that we commissioned as part of
this evaluation. The survey focused on consumers’ experience of our intervention and the
extent to which it affected behaviours and outcomes in line with the intervention’s
objectives.
PwC Research conducted the survey of 1,000 consumers in February 2018. Details of the
survey are summarised in Section 6 and presented in full in Annex 2.
prices over and above the general effects of inflation. We present these figures in April 2018 prices, unless stated
otherwise. By doing this, the data may appear to be different to other publications. The difference is due our real
terms adjustment.
25
‘Untreated’ is also called ‘control’. Examples of DiD approaches include: Ashenfelter & Card, 1985, Using
the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs; Meyer, Viscusi & Durbin, 1990,
Workers' Compensation and Injury Duration: Evidence from a Natural Experiment; and Card, 1994, Minimum
Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
17
Section summary
Our analysis shows that the various factors that might influence GAP insurance sales –
household disposable income, access to finance and new vehicle sales – have all moved
in such a way that we would expect GAP insurance demand to have increased. Access to
finance is most likely to have had the most significant impact on demand.
This section sets out the wider context to the GAP insurance market. We provide an
overview of the market’s demand drivers, describe the recent trends of these drivers,
and discuss what impact they are likely to have had on GAP insurance demand.
The main drivers of GAP insurance demand
Vehicle ownership is the main demand driver for GAP insurance. In turn, vehicle
purchases depend upon consumers’ ability to afford a vehicle, due to their disposable
income and access to finance among other things.
Household disposable income and access to finance
Figure 3.1 shows that median disposable household income increased over the period
before and after our intervention. This was a total increase of around 12% from 2013 to
2017 (£25,700 to £28,600). This might lead to a rise in demand for vehicles
26
, as
consumers have more money to afford them.
26
Assuming vehicle prices have not increased by proportionately more than incomes.
3 Results: Market context analysis
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
18
Figure 3.1: Median real household disposable income
Source: Office for National Statistics (ONS) data, FCA analysis
The new car
27
finance market has more than doubled during the past 7 years. The value
of point-of-sale new car finance increased from £7.8 billion in 2010 to £19.1 billion in
2017 (Figure 3.2). Over the same period, the number of new cars bought using point-of-
sale finance almost doubled from 517,000 to 990,000 a year. Many firms thought that
increasing access to car finance has significantly increased car sales and GAP insurance
sales in recent years.
27
Throughout the report, we focus our analysis, where possible, on vehicle sales. We do this because GAP
insurance can be purchased on a range of vehicle types, not just cars. However, finance data are only available
on car sales. We therefore analyse financing against car sales. We note that vehicle and car sales trends track
extremely closely.
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
2010 2011 2012 2013 2014 2015 2016 2017
Median real equivalised disposable income (£, 2018 prices)
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
19
Figure 3.2: New point-of-sale finance by product
Source: ONS data, Finance & Leasing Association data, FCA analysis
Note: PCP refers to personal contract purchase; HP refers to hire purchase.
Vehicle sales have increased since our intervention
Figure 3.3 shows that new vehicles sales grew, on average, by around 5% a year
between 2010 and 2016, and fell by nearly 6% between 2016 and 2017.
Figure 3.3: Yearly new vehicle sales
Source: Driver and Vehicle Licensing Agency (DVLA) data, FCA analysis
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
0
5,000
10,000
15,000
20,000
25,000
2010 2011 2012 2013 2014 2015 2016 2017
Number of new cars financed (yearly)
New finance value for new car sales (£m, 2018 prices)
PCP (LHS) HP (LHS) Leasing (LHS) Personal loans (LHS) New cars financed (RHS)
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
4,000,000
Jan-10 Jul-10 Jan-11 Jul-11 Jan-12 Jul-12 Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Jan-17 Jul-17
New vehicle sales over preceding 12 months
Period of interest
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
20
Consumers’ ability and willingness to pay for GAP insurance
Figure 3.1 and Figure 3.2, respectively, show that:
• disposable household income has increased
• consumers’ ability to buy a vehicle (and, by implication, GAP insurance at point-of-
sale) on finance has increased significantly
These factors together increase consumers’ ability to afford and need to buy GAP
insurance. Higher income may, however, reduce GAP insurance demand through an
increased ability to self-insure. That said, given the relatively small income increase, we
expect that this impact is limited. We do not expect that it is large enough to outweigh
any GAP insurance demand increases caused by consumers having more income.
Table 3.1 sets out factors affecting consumers’ willingness to pay for GAP insurance.
Table 3.1: Consumers' willingness to pay for GAP insurance
Factors affecting
consumers’
willingness to pay
Available evidence and likely impact on GAP insurance sales
through impact on consumers’ willingness to pay
The likelihood of
the vehicle being
written off or stolen
We have no evidence to suggest that this has changed in recent years.
Whether the vehicle
is new/high value
and the vehicle’s
depreciation
28
rate
New vehicles, typically, face the fastest depreciation rates. The
depreciation rate slows as the vehicle ages. So, GAP insurance is most
valuable to those buying new vehicles. Figure 3.3 shows that new vehicle
sales have increased in recent times (though it slowed in 2017).
Hence, we expect consumers’ willingness to pay for GAP insurance to
have increased overall.
The amount and
form of financing
taken
Figure 3.2 shows that:
• buying vehicles on finance has increased significantly in recent years
• the growth has been driven, almost entirely, by personal contract
purchase (PCP) agreements
29
PCPs are typically designed to minimise consumers’ vehicle loan
repayments during the term of the loan agreement. This leaves a ‘balloon
payment’ at the agreement’s end (ie a large sum of money owed on a
consumer’s finance agreement when new vehicles depreciate the fastest).
As such, we expect PCP’s high share of finance to increase consumers’
benefits from holding GAP insurance further, and, therefore, increase
their willingness to pay for it.
Consumers’
aversion to risk
30
We have no evidence to suggest that this has changed in recent years.
Source: FCA analysis
28
Depreciation captures the vehicle’s loss in value due to general ageing and ‘wear and tear’. It is the
difference between a vehicle’s value when it is bought and when it is sold.
29
PCP is a form of finance where, at the end of an agreed term, the consumer has the option to buy the
car at a predetermined value or return it.
30
This is a function of loss aversion. This is when people strongly prefer to avoid losses than receive gains
because of hard-wired emotions (fear of losses). The degree of loss aversion varies across people and situations.
It can lead to distorted attitudes to risk (eg to avoid risk from the fear of loss, consumers may pay for ‘peace of
mind’, even if the negative outcome has a very low probability).
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
21
GAP insurance demand drivers indicate that total sales would
likely have increased without our intervention
Table 3.2 summarises the changes to the market-level demand drivers (direct and
indirect) of GAP insurance.
We expect that these factors would have increased consumers’ demand for GAP
insurance without our intervention. We expect that this would have raised total GAP
insurance sales and/or prices over the evaluation period.
This informs our wider analysis of our intervention’s impact. We could, potentially,
misinterpret its true impact if we do not control for these underlying market changes (in
particular, the significant increase in consumers’ access to finance and the type of finance
that they are using). This is why we use econometric analysis to complement other
methods (as set out in Section 2).
Table 3.2: Changes to the demand drivers for GAP insurance
Demand driver
Impact on demand
Household disposable income
✓
Marginal increase
Access to finance
✓✓
Significant increase
New vehicle sales
✓
Marginal increase
Source: FCA analysis
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
22
Section summary
Add-on GAP insurance sales are 16% to 23% lower because of our intervention.
Competition between add-on and standalone GAP insurance markets, as measured by
standalone’s share of total sales, has improved, albeit only marginally.
This section summarises our analysis of how GAP insurance sales (total, add-on and
standalone) have changed after our intervention. First, we set out our pre-intervention
expectations for GAP insurance sales. Next, we present evidence on how total, add-on
and standalone GAP insurance sales trends have changed after our intervention. We
conclude with our analysis of what would have happened to add-on GAP insurance sales
had we not intervened.
We expected total GAP insurance sales to increase
Table 2.1 gives an overview of our pre-intervention expectations. Table 4.1 sets out
further details of our sales-based pre-intervention expectations.
Table 4.1: Our pre-intervention expectations for GAP insurance sales
Metric
Pre-intervention expectation
Total GAP insurance sales
Increase by between 12.5% (no add-on price change scenario) to
35% (add-on price fall scenario).
Add-on GAP insurance
sales
Fall by 32.5% (no add-on price change scenario). This is the sum
of:
• 22.5% of sales moving to the standalone GAP insurance market
• 10% of sales lost (ie consumers no longer buy GAP insurance)
Fall by 10% in the add-on price fall scenario.
Add-on GAP insurance
sales share of total GAP
insurance sales
Make up 60% (no add-on price change scenario) to 67% (add-on
price fall scenario) of the total GAP insurance market.
Standalone GAP
insurance sales share of
total GAP insurance sales
Make up 33% (add-on price fall scenario) to 40% (no add-on price
change scenario) of the total GAP insurance market.
Source: CP14/29
4 Results: Sales analysis
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
23
Total GAP insurance sales after our intervention
Figure 4.1 shows that total GAP insurance sales have been relatively constant after our
intervention.
31
Total GAP insurance sales fell from just under 1.1 million a year
32
before
our intervention to just over 1.0 million a year
33
after our intervention. This is a fall of
around 4%. Total GAP insurance sales returned to just under 1.1 million a year in the 12
months leading up to August 2017.
Figure 4.1: Monthly total GAP insurance sales
Source: FCA analysis of firms’ GAP insurance transaction data
Total GAP insurance sales as a percentage of vehicle sales
Figure 4.2 shows the monthly total GAP insurance penetration rate (ie GAP insurance
sales as a percentage of total new vehicle sales).
34
After our intervention, the GAP
insurance penetration rate (total and add-on) appears to dip noticeably in the months
when new vehicle registration plates are released (March and September). Given what
we know about vehicle sales (Figure 3.3), it looks like GAP insurance sales, in these
months, have been unable to keep up.
Table 4.2 summarises the monthly movements by taking the average across 12-month
intervals before and after our intervention.
31
GAP insurance sales display seasonal sales patterns. Sales spike in March and September in line with
new vehicle sales. This spike occurs in the months that the latest number plate variations are released.
32
Total of GAP insurance sales in the 12 months before our intervention.
33
Total of GAP insurance sales in the 12 months after our intervention.
34
The penetration rate measures the proportion of total GAP insurance sales (both for new and used vehicle
sales) relative to the number of total new vehicle registrations. Used vehicle sales data were not available for the
full period (September 2013 to August 2017). The trends in the chart were similar to those for new car sales
only, which, on average, made up 81% of all new vehicle registrations over the period.
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
Sep-13 Dec-13 Mar-14 Jun-14 Sep-14 Dec-14 Mar-15 Jun-15 Sep-15 Dec-15 Mar-16 Jun-16 Sep-16 Dec-16 Mar-17 Jun-17
Monthly total GAP insurance sales
Total GAP insurance sales
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
24
Based on Table 4.2, we see that:
• The total GAP insurance penetration rate fell after our intervention. This was due to a
small fall in total GAP insurance sales, as well as higher car sales (Figure 4.2). It has
recovered subsequently. This has happened due to a small increase in total GAP
insurance sales, as well as a slight drop in vehicle sales.
• The add-on GAP insurance penetration rate, similarly, fell after intervention. Although
it has recovered since then, it has not returned to its pre-intervention level.
The lower add-on GAP insurance penetration rate is consistent with our expectation in
Table 2.1.
Figure 4.2: Seasonally-adjusted monthly total and add-on GAP insurance sales
penetration rate
35
Source: FCA analysis of firms’ GAP insurance transaction data and DVLA vehicle registration data
Table 4.2: Average GAP insurance penetration rates
GAP
insurance
market
12 months before
intervention
(September 2014 –
August 2015)
12 months after
intervention
(September 2015 –
August 2016)
12 months to August
2017
(September 2016 –
August 2017)
Total
38%
35%
37%
Add-on
36%
32%
34%
Source: FCA analysis of firms’ GAP insurance transaction data and DVLA vehicle registration data
35
We adjust the monthly data to remove sales’ seasonality (eg the sales spikes in March and September).
0%
10%
20%
30%
40%
50%
60%
Sep-13 Dec-13 Mar-14 Jun-14 Sep-14 Dec-14 Mar-15 Jun-15 Sep-15 Dec-15 Mar-16 Jun-16 Sep-16 Dec-16 Mar-17 Jun-17
GAP insurance penetration rate (deseasonalised)
Total GAP insurance penetration rate for new vehicles Add-on GAP insurance penetration rate for new vehicles
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
25
Standalone GAP insurance sales after our intervention
Although total GAP insurance sales have been constant, the trends in add-on and
standalone GAP insurance sales have differed after our intervention.
Figure 4.3 shows monthly add-on and standalone GAP insurance sales figures. Table 4.3
presents the annual data before and after our intervention.
Table 4.3 highlights that post-intervention add-on GAP insurance sales are similar to
those pre-intervention. Add-on GAP insurance sales fell, initially, by around 6%. They
have recovered to be 2% lower than before our intervention. Our analysis and
discussions with firms suggest that this is not due to our intervention causing firms not to
offer add-on GAP insurance. Figure 4.3 shows that add-on GAP insurance sales display
the same monthly fluctuations across the pre- and post-intervention periods, with spikes
in March and September.
Standalone GAP insurance sales have increased significantly after our intervention,
starting from a relatively low base. Hence, the percentage changes in Table 4.3 are
relatively large. Figure 4.3 shows that standalone GAP insurance sales have developed a
seasonal sales pattern similar to add-on GAP insurance sales after our intervention.
There was no clear seasonality for standalone GAP insurance sales before our
intervention.
Figure 4.3: Monthly standalone and add-on GAP insurance sales
Source: FCA analysis of GAP insurance transaction data provided by firms
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
Sep-13 Mar-14 Sep-14 Mar-15 Sep-15 Mar-16 Sep-16 Mar-17
Monthly standalone GAP insurance sales
Monthly add
-on GAP insurance sales
Add-on GAP insurance sales (LHS) Standalone GAP insurance sales (RHS)
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
26
Table 4.3: GAP insurance sales volumes
GAP
insurance
market
12 months before
intervention
(September 2014 –
August 2015)
12 months after
intervention
(September 2015 –
August 2016)
12 months to August
2017
(September 2016 –
August 2017)
Add-on
1,012,000
946,000
(-6%)
996,000
(-2%)
Standalone
61,000
85,000
(39%)
96,000
(57%)
Source: FCA analysis of GAP insurance transaction data provided by firms
Note: Figures rounded to the nearest thousand; percentage changes are relative to the pre-
intervention sales figures.
Figure 4.4 shows the split of half-yearly total GAP insurance sales between add-on and
standalone sellers. It shows that standalone’s share of total sales has increased from
around 6% in the 2 years before our intervention to around 9% in the 2 years after.
Higher standalone GAP insurance sales (absolute and as a percentage of total GAP
insurance sales) explain the difference in total and add-on GAP insurance penetration
rates in Figure 4.2.
Figure 4.4: Half-yearly shares of standalone and add-on GAP insurance sales as
a proportion of total GAP insurance sales
Source: FCA analysis of GAP insurance transaction data provided by firms
95%
94%
94%
94%
92%
91%
91%
91%
5%
6%
6%
6%
8%
9%
9%
9%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
H1 2013/14 H2 2013/14 H1 2014/15 H2 2014/15 H1 2015/16 H2 2015/16 H1 2016/17 H2 2016/17
Market share of total GAP insurance sales
Add-on GAP insurance sales Standalone GAP insurance sales
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
27
Our intervention’s impact on add-on sales
We use econometric analysis to estimate our intervention’s causal
impact
Econometric analysis isolates our intervention’s impact from other factors
36
that may
have also influenced add-on GAP insurance sales. Full details of our analysis are available
in the Technical Annex. Our analysis shows that sales of add-on GAP insurance and CWP
followed similar trends before our intervention. We use this to assume that add-on GAP
insurance sales would have followed a similar trend to CWP sales had we not intervened.
The intervention’s impact is the difference between our estimate of what would have
happened had we not intervened and what actually happened.
Add-on GAP insurance sales are 16% to 23% lower than they would
have been without our intervention
Table 4.4 summarises the results of our econometric analysis. We estimate that add-on
GAP insurance sales are between 16% and 23% lower due to our intervention.
37
Our pre-
intervention expectation was that, all other things being equal, add-on GAP insurance
sales would fall by between 10% and 32.5%.
Table 4.4: Our intervention’s estimated impact on add-on GAP insurance sales
38
Estimate
Estimated impact on add-on
GAP insurance sales
Pre-intervention estimated
impact on add-on GAP
insurance sales
Lower bound estimate
-16%
-10% to -32.5%
Central estimate
-19%
Upper bound estimate
-23%
Source: FCA analysis of transaction data provided by firms; CP14/29
The results also indicate that, all else being equal, the add-on share of total GAP
insurance sales would have been higher had we not intervened. We are unable to
estimate by how much because some of these add-on GAP insurance sales could have
been:
• substituted to the standalone GAP insurance market
• lost altogether (ie consumers choose not to buy GAP insurance)
We do not know the precise split between these two groups.
Consumer switching to the standalone market
Table 4.3 suggests that the substitution effect from add-on to standalone GAP insurance
sales has been small.
36
These factors may be observable (eg changes in car sales) or unobservable (eg consumer risk
preferences or dealers’ commercial incentives).
37
The econometric analysis estimates a statistically significant point estimate of a 19% reduction in add-
on GAP insurance sales relative to the comparator product CWP. The range quoted is the 95% confidence interval
around this point estimate.
38
See Technical Annex for details of how we test our econometric analysis. Overall, these checks indicate
that the size and direction of our intervention’s estimated impact are stable and statistically robust.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
28
Even if all the increase in standalone GAP insurance sales is due to substitution alone,
this would account for only 8% to 13% of the estimated fall in add-on GAP insurance
sales. This is much lower than the fall in add-on GAP insurance sales that we estimated
would move to the standalone market as part of our pre-intervention CBA (ie 70%, which
is 22.5% divided by 32.5% in Table 4.1).
Our range of 8% to 13% is likely to be the upper threshold. This is because some
standalone GAP insurance sales may have been to consumers new to the market (ie
consumers that did not move over from the add-on GAP insurance market).
Add-on GAP insurance sales that did not happen due to our intervention
The results indicate that our intervention had a notable effect on add-on GAP insurance
sales. This appears to be due to consumers not buying GAP insurance at all, rather than,
as we had expected, buying standalone GAP insurance instead. Figure 4.2 shows that the
GAP insurance sales penetration rate dipped in the months where vehicle sales are
normally highest. This also suggests that our intervention may have reduced GAP
insurance sales that might otherwise have happened.
The analysis does not capture which of the intervention’s policy measures had the
greater relative impact (see Section 6).
We estimate that add-on GAP insurance sales are 16% to 23% lower due to our
intervention. This causal impact is likely to have affected the following consumer groups:
1. Consumers for whom buying GAP insurance is an unsuitable product choice: our
intervention has caused these people not to buy add-on GAP insurance
2. Consumers for whom buying add-on GAP insurance is an unsuitable purchase, but
buying standalone GAP insurance is a more appropriate choice: our intervention, it
appears, caused only a relatively small number of these people to buy standalone
GAP insurance
3. Consumers for whom buying add-on GAP insurance is an appropriate product
purchase: we felt, before intervening, that there were very few of these people in the
market. But, our intervention may have caused this group of people not to buy
something that they valued correctly. Although it might appear that add-on GAP
insurance is never a suitable purchase (eg because it can be bought elsewhere for a
much cheaper price), it might be appropriate for consumers who value:
– convenience
– not searching for a standalone policy
– the peace of mind in knowing that they are covered
– being able to buy GAP insurance in person (rather than on the phone or online)
The largest positive impact of our intervention happens if the causal impact is
predominantly among the first consumer group. In contrast, the most negative impact of
our intervention occurs if the causal impact is among the third consumer group. We do
not know precisely how our estimated causal impact is distributed across the 3 consumer
groups.
However, our market study’s findings, and our basis for intervening in the first place,
lead us to think that our impact has been, predominantly, among the first 2 consumer
groups. Before intervening, we thought that many consumers who bought this product
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
29
did not need it. For example, we found that 59% of people who bought add-on GAP
insurance had not considered buying it before the day of purchase. That is not to say that
all these consumers did not value the product and/or truly needed it. But we believed
that many were buying a product that they did not need.
As a result, we consider that our causal impact on sales is, overall, a positive outcome of
our intervention.
Summary of GAP insurance sales analysis
We summarise the findings of our GAP insurance sales analysis in Table 4.5.
Table 4.5: Summary results from our analysis of GAP insurance sales
Outcome
Pre-intervention
expectation
Observed outcome
after our
intervention
Estimated causal
impact of our
intervention
Percentage change to total
GAP insurance sales
+12.5% to +35%
-4%
N/A
Percentage change to add-
on GAP insurance sales
-10% to -32.5%
-2% to -6%
-16% to -23%
Add-on GAP insurance sales
as a share of all GAP
insurance sales
60% to 67%
92%
(94% before
intervention)
N/A
Standalone GAP insurance
sales as a share of all GAP
insurance sales
33% to 40%
8%
(6% before
intervention)
N/A
Source: FCA
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
30
Section summary
Average add-on GAP insurance prices have continued to increase after our intervention,
although they would have been even higher without it.
Average standalone GAP insurance prices fell by 5% after our intervention.
The price difference between average add-on and standalone GAP insurance prices,
therefore, has increased after our intervention.
This section summarises our analysis of how GAP insurance prices
39
(total, add-on and
standalone) have changed after our intervention. First, we do so by setting out details of
our pre-intervention expectations for GAP insurance prices. Next, we present evidence on
how total, add-on and standalone GAP insurance price trends have changed after our
intervention. We conclude with our analysis of what would have happened to add-on GAP
insurance prices had we not intervened.
Before intervening, we expected lower average GAP insurance
prices if add-on prices fell
Table 2.1 gives an overview of our pre-intervention expectations. Table 5.1 shows sets
out details of our pre-intervention expectations for GAP insurance prices.
Table 5.1: Our pre-intervention expectations for average GAP insurance prices
Metric
Pre-intervention expectation
Average add-on GAP insurance prices
Scenario 1: No price change
Scenario 2: Price falls by 17%
Average standalone GAP insurance prices
No price change
Source: FCA CP14/29
Average overall GAP insurance retail prices show little change
after our intervention
Based on the analysis in Section 3 and the rationale set out at the beginning of
Section 4, we expect GAP insurance prices to be higher after our intervention. The
increase in disposable income and access to finance suggest that, all else being equal,
consumers would be willing to pay more for GAP insurance. We expect that this would
lead to higher average GAP insurance prices.
39
We focus on the final price charged to the consumer (including tax), which we call the ‘retail price’.
5 Results: Price analysis
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
31
Figure 5.1 shows that the average GAP insurance price has increased by a small amount,
in real terms, after our intervention. The average price remained almost unchanged
between the 12 months before and after our intervention. It decreased from £363 to
£362 in real terms.
40
The average price then increased to £367 for the 12 months ending
August 2017 (also in real terms).
To understand why this might have happened, the rest of this section considers what has
happened to average prices in the add-on and standalone markets, and other factors that
might influence GAP insurance prices.
Figure 5.1: Monthly market average GAP insurance retail price
Source: FCA analysis of GAP insurance transaction data provided by firms
Add-on and standalone prices show diverging trends
Section 3 suggests that there has been a large impact on add-on, rather than
standalone, GAP insurance prices. This is because consumers are buying more vehicles
on finance, thereby reducing consumers’ financial constraints at the point of buying the
vehicle. This, in turn, might have increased consumers’ ability to pay for add-on GAP
insurance. As such, we also look at average price changes between the different markets
(ie add-on and standalone).
Figure 5.2 shows the monthly average add-on and standalone GAP insurance price. Table
5.2 summarises the monthly movements by taking the average across 12-month
intervals before and after our intervention.
40
All 12-month prices are weighted averages. We calculate this as the average price for each month
multiplied by the number of policies sold in that month, which is then divided by the total number of policies sold
in the 12-month period.
0
50
100
150
200
250
300
350
400
450
500
Sep-13 Dec-13 Mar-14 Jun-14 Sep-14 Dec-14 Mar-15 Jun-15 Sep-15 Dec-15 Mar-16 Jun-16 Sep-16 Dec-16 Mar-17 Jun-17
Market average GAP insurance retail price (£, 2018 prices)
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
32
The data highlight that average add-on and standalone GAP insurance prices diverged
after our intervention. This has happened to such an extent that the average add-on GAP
insurance price is, now, almost two and a half times the average standalone GAP
insurance price. The average standalone GAP insurance price fell despite Insurance
Premium Tax (IPT) rates increasing for standalone sellers over the period.
41
These average price changes are contrary to our pre-intervention expectations (Table 2.1
and Table 5.1). We consider why this has happened in the rest of this section.
Figure 5.2: Monthly average GAP insurance retail price by market segment
Source: FCA analysis of GAP insurance transaction data provided by firms
41
Standalone GAP insurance sellers face the standard rate of IPT. This increased from 6% to 9.5% on
1 November 2015, then to 10% on 1 October 2016, and, finally, to 12% on 1 June 2017. Add-on GAP insurance
sellers also face the lower rate of IPT when the GAP insurance product is directly and solely related to a finance
contract. For other types of GAP insurance, add-on sellers face the higher rate of IPT, which has been 20% since
4 January 2011. IPT is expressed as an additional percentage to the retail selling price (excluding tax). See
HMRC’s guidance.
0
50
100
150
200
250
300
350
400
450
Sep-13 Dec-13 Mar-14 Jun-14 Sep-14 Dec-14 Mar-15 Jun-15 Sep-15 Dec-15 Mar-16 Jun-16 Sep-16 Dec-16 Mar-17 Jun-17
GAP insurance average retail price (£, 2018 prices)
Add-on average retail price Standalone average retail price
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
33
Table 5.2: Average GAP insurance price (segment and price difference), 2018
prices
42
Metric
12 months before
intervention
(September 2014 –
August 2015)
12 months after
intervention
(September 2015 –
August 2016,
% change to pre-
intervention figure)
12 months to August
2017
(September 2016 –
August 2017,
% change to pre-
intervention figure)
Add-on
£375
£379
(+1%)
£387
(+3%)
Standalone
£186
£176
(-5%)
£162
(-13%)
Add-on and
standalone price
difference
£189
£202
(+7%)
£225
(+19%)
Source: FCA analysis of GAP insurance transaction data provided by firms
Changes to policy coverage
One possible reason behind the different add-on and standalone GAP insurance average
price trends could be changes in the policy coverage offered, and sold, by firms.
We see changes in policy coverage in our data that could explain part of what we see.
Table 5.3 presents changes in average policy coverage in the 12 months before and after
our intervention.
43
However, these changes do not appear large enough to explain the
full extent of the price changes in Figure 5.2.
Table 5.3: Changes in average policy coverage by market segment (12 months
before and after our intervention)
Coverage factor
Change
44
for add-on GAP
insurance
Change for standalone GAP
insurance
Policy duration
+0.3 months
-0.7 months
Value of car insured
(real terms)
+1.9%
+5.8%
Proportion of policies
covering financed cars
-1.6 percentage points
-8.3 percentage points
Source: FCA analysis of GAP insurance transaction data provided by firms
We do not find that other costs are contributing to the divergence in add-on and
standalone GAP insurance prices after our intervention:
• It does not appear that add-on GAP insurance prices are higher because of ongoing
compliance costs (Section 7)
42
Figures are rounded to the nearest currency unit. Any differences are due to calculations that are not
based on the rounded figures presented here. Percentage changes in brackets are rounded and relative to the
figures before intervention.
43
See Technical Annex for charts illustrating the change in these factors over time.
44
Change is calculated as the difference between the averages of the relevant factors over the 12 months
following our intervention and the 12 months prior to our intervention.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
34
• Our intervention may have, indirectly, lowered the average cost of selling standalone
GAP insurance. For example, fixed costs (such as IT and customer support) are now
spread across a larger number of policies, given higher standalone GAP insurance
sales, after our intervention. However, this effect is likely to have been small.
Changes in underlying risk
GAP insurance is a risk-based product. This means that the riskiness of those being
insured influences part of the cost of providing GAP insurance. A possible explanation of
post-intervention add-on and standalone prices could be changes to the riskiness of the
people buying these GAP insurance products.
For example, we might expect that consumers who no longer buy add-on GAP insurance
(Section 4) may have a lower need for GAP insurance. This might be because, for
example, they are less risky than other consumers. As such, the remaining add-on GAP
insurance buyers would be riskier on average. This could lead insurers to raise prices to
cover the increased perceived risk among the remaining add-on GAP insurance buyers.
This is consistent with what we see in firms’ data. Add-on GAP insurance underwriter
prices
45
increased by 12% in the 12 months after our intervention, when compared to the
12 months beforehand. Underwriter prices for standalone GAP insurance fell by 9% over
the same period.
We expect that some of this is a result of policy coverage changes (Table 5.3). However,
even when we control for policy coverage changes, we still see a small increase (1.4%)
in add-on GAP insurance prices and a small decrease (0.4%) in standalone GAP
insurance prices. Our analysis of consumers’ probability to claim (see Section 7) also
confirms this higher riskiness among remaining add-on GAP insurance buyers.
How add-on GAP insurance prices are split
Another factor that may affect the average GAP insurance retail price is the margin that
the seller charges above their costs. This is a function of the value taken by the various
parts of the distribution chain, and the underlying cost of insuring the expected risk.
Figure 5.3 shows the different elements that form the average add-on GAP insurance
retail price.
45
We use underwriter prices as a proxy for the risk-based cost of providing the insurance. From discussions
with firms, we understand that the GAP insurance underwriting market is relatively competitive.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
35
Figure 5.3: Proportion of the average add-on GAP insurance retail price received
by each part of the distribution chain
Source: FCA analysis of GAP insurance transaction data provided by firms
Note: Due to our data collection, the quarters are: Q1 – September-November; Q2 – December-
February; Q3 – March-May; and Q4 – June-August.
Figure 5.3 shows that add-on GAP insurance sellers keep a similar proportion of the final
retail price before (58% in the 12 months before our intervention) and after our
intervention (56% in the 12 months after our intervention).
This suggests that add-on GAP insurance sellers still hold a strong position in the
distribution chain and can pass on supplier costs to consumers whilst maintaining their
margin.
Our intervention’s impact on add-on prices
We take the same econometric approach as in Section 4 to estimate our intervention’s
impact on add-on GAP insurance prices.
46
We compare price trends of add-on GAP
insurance and CWP for which the price trends are broadly common before the
intervention.
47
The intervention’s average price impact is the difference between our estimate of what
would have happened had we not intervened and what actually happened.
Table 5.4 summarises the results of our econometric analysis. We estimate that average
add-on GAP insurance prices are between 2% and 3% lower than they would have been
46
See Technical Annex for supporting further details, assumptions, and evidence, including a chart on pre-
intervention price trends for add-on GAP insurance and CWP.
47
Section 4 set out why our estimates might over- or underestimate the true impact of our intervention.
The same logic applies to our price analysis.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Q1,
2013/14
Q2,
2013/14
Q3,
2013/14
Q4,
2013/14
Q1,
2014/15
Q2,
2014/15
Q3,
2014/15
Q4,
2014/15
Q1,
2015/16
Q2,
2015/16
Q3,
2015/16
Q4,
2015/16
Q1,
2016/17
Q2,
2016/17
Q3,
2016/17
Q4
2016/17
Average proportion of retail price received from add
-on GAP insura ce sales
Tax Underwriter Intermediary Retailer
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
36
had we not intervened.
48
This impact falls within the bounds of our pre-intervention
expectations, and is at the lower end of our expected impact scale.
As with our sales analysis, we have run checks on the results of our econometric analysis
(see Technical Annex). Overall, these tests suggest that we should be cautious in
assigning a causal impact of our intervention to price changes.
Table 5.4: Estimated reduction in add-on GAP insurance retail prices as a result
of the intervention
Estimate
Estimated impact on add-on
GAP insurance prices
Pre-intervention estimated
impact on add-on GAP
insurance prices
Lower bound estimate
-1.8%
0% to -16.7%
Central estimate
-2.7%
Upper bound estimate
-3.4%
Source: CP14/29; FCA analysis of transaction data provided by firms
Our analysis in Section 4 indicates that more consumers appear to have left the GAP
insurance market entirely rather than move to the standalone market (see Section 4).
This might explain why our intervention had a limited impact on add-on GAP insurance
prices.
Rather than increasing competition between the add-on and standalone GAP insurance
markets, the intervention may have heightened segmentation between the two markets.
The remaining buyers that add-on sellers face, after our intervention, have, on average,
a higher willingness to pay. However, these buyers should be better informed about GAP
insurance after our intervention, so this might reduce their willingness to pay.
While the two markets compete for some consumers, it is likely that they serve entirely
different types of consumers. Add-on sellers face limited competition for their consumers
due to their point-of-sale advantage. An add-on buyer takes GAP insurance from their
vehicle seller. In contrast, standalone buyers search across the standalone market
without being tied to one seller. These differences in how firms and consumers interact
might also help explain why prices have diverged between the two markets.
The average standalone GAP insurance price might have fallen even further if new firms
had entered the market. However, we do not note any significant change in the number
of standalone GAP insurance sellers. Alternatively, it might be that, after our
intervention, existing standalone sellers have competed more vigorously for the greater
number of consumers.
Informal engagement with GAP insurance underwriters and distributors provided useful
insight. We found that standalone sellers are, to some extent, reliant on add-on sellers
informing consumers about the existence of GAP insurance. Without add-on sellers
raising GAP insurance’s profile (and the fact that it can be bought elsewhere with the
prescribed information), firms felt that the standalone market might have a far lower
presence.
48
The econometric analysis estimates a statistically significant point estimate of a 2.7% reduction in add-
on GAP insurance price relative to the comparator product CWP. The range quoted is the 95% confidence interval
around this point estimate.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
37
Summary of GAP insurance price analysis
We summarise the findings of our average GAP insurance price analysis in Table 5.5.
Table 5.5: Summary of price changes in the GAP insurance market
Outcome
Pre-intervention
expectation
Observed changed
Estimated causal
impact
Add-on GAP insurance
prices
0% or -17%
+1% to +3%
-2% to -3%
Standalone GAP
insurance prices
0%
-5% to -13%
N/A
Source: FCA CP14/29
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
38
Section summary
More consumers claim to recall receiving the prescribed information than the deferred
opt-in.
Shopping around has increased for some consumers, but not all. Consumers, overall,
appear to be more engaged with the decision-making process when considering whether
to buy GAP insurance or not and, if so, where to buy it. Our intervention is likely to have
affected a subset of consumers, with some having made their decision about buying GAP
insurance before buying the vehicle. High levels of repeat purchasing indicate habitual
behaviour playing a role in the decision-making process, making GAP insurance more of
a standard consideration for car buyers.
Add-on buyers are more confident about their GAP insurance knowledge. The knowledge
gap between add-on and standalone GAP insurance buyers’ has reduced after our
intervention. We were concerned, before intervening, about the presence of this
knowledge gap.
The prescribed information measure was more memorable than the deferred opt-in
measure. But, having time to think about buying GAP insurance was generally perceived
as more useful than the prescribed information. Consumers found the information
gathered whilst shopping around as most useful when reaching their decision.
This section sets out how consumers experienced our intervention’s two measures (ie
prescribed information and the deferred opt-in). We do this to understand how, and to
what extent, our intervention has changed consumer outcomes during the purchasing
process.
The analyses set out in Sections 4 and 5 provide an overall, market-level impact of our
intervention. We complement these analyses, in this section, by providing a sense of
consumers’ experience of our intervention.
In line with our pre-intervention expectations in Table 2.1, we consider:
• consumers’ recall and experience of the two measures
• consumers’ decision-making process (including their propensity to shop around for,
their general awareness of, and engagement with GAP insurance)
• the impact of the intervention on consumers’ perceived and actual knowledge of GAP
insurance
To do this, we draw on:
• PwC Research’s survey of 1,000 car buyers, conducted on our behalf in February 2018
(which we refer to as ‘the survey’ throughout this document)
6 Results: Consumer survey
findings
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
39
• a consumer survey that was part of the general insurance add-on products market
study, published in 2014
• our 2017 Financial Lives Survey (FLS)
We summarise the main insights from these sources here.
49
Detailed findings and
methodology from PwC Research’s work are available in Annex 2 and Annex 3,
respectively.
Why and how we compare the 2014 and 2018 surveys
We draw on comparisons between the 2014 and 2018 consumer surveys for useful pre-
and post-intervention perspectives. This gives us a sense of how our intervention might
be associated with changes in consumer behaviour (insofar as we consider the same
topics in both surveys).
The comparison is not straightforward as there are differences between the surveys. For
example:
• The 2018 survey includes car buyers who were offered, but did not buy, GAP
insurance. Findings from this consumer group are useful for our evaluation, as they
also experienced our intervention. The 2014 study did not include these consumers.
• In 2014, we issued a data request to sellers of add-on and standalone insurance
products, asking them to provide lists of recent buyers. In contrast, the 2018
research adopted a free-find method in which the approach screened out participants
if they told us they had not bought a car / GAP insurance.
Despite these differences, we can make valid comparisons. In particular, it is possible to
make meaningful comparisons where differences are larger or patterns are consistent.
Full details are set out in PwC Research’s report.
Our 2018 survey considered 4 types of car buyers
We considered four types of consumers:
1. those who bought GAP insurance as an add-on product
2. those who bought GAP insurance as a standalone product
3. those who did not buy GAP insurance, but did consider it
4. those who did not buy GAP insurance and did not consider doing so
Table 6.1 sets out selected summary statistics of our survey’s overall consumer profile.
49
The rest of the section refers to PwC Research’s survey, unless stated otherwise. We do not reference
findings from this survey with each mention of a figure or finding.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
40
Table 6.1: Summary statistics of our survey’s overall consumer profile
Percentage of consumers
54%
Purchased a vehicle in the last 12 months and discussed or considered GAP
insurance.
45%
Did not consider buying GAP insurance at all.
28%
Considered buying GAP insurance, but did not.
26%
Bought GAP insurance. This is made up of 22% of add-on GAP insurance consumers
and 5% of standalone GAP insurance consumers (difference due to rounding).
82%
Bought GAP insurance as an add-on (of those who bought GAP insurance in total).
18%
Bought GAP insurance as a standalone (of those who bought GAP insurance in total).
Source: PwC Research
Consumers’ recall and experience of the measures was mixed
Consumer recall of the prescribed information was relatively high
Table 6.2 shows that consumers’ recall of receiving the prescribed information was
relatively high. It also shows that nearly all consumers claimed to have read the
prescribed information at least briefly.
Table 6.2: Recall of and engagement with the prescribed information measure
by consumer type
Consumer group
Percentage of
consumers that
recalled receiving
the prescribed
information
Percentage of
consumers that
claimed to have
read the prescribed
information
‘thoroughly’
Percentage of
consumers that
claimed to have
read the prescribed
information at least
‘briefly’
Car buyers who were
offered GAP insurance
74%
37%
55%
Add-on GAP insurance
buyers
78%
36%
96%
Standalone GAP
insurance buyers
65%
58%
96%
Car buyers who
considered but did not
buy GAP insurance
63%
44%
86%
Source: PwC Research
However, recall of the deferred opt-in was much lower
Nearly two-thirds (63%) of add-on GAP insurance buyers believed that the sale was
finalised on the same day as the product was introduced.
This could point to some dealerships not applying this measure in its intended spirit. If
this were the case, we might see the findings in Section 4 as an understatement of our
intervention’s true impact (see Section 2).
However, this is difficult to prove using survey data alone. It might be hard for
consumers to separate the time at which they decided to buy GAP insurance from the
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
41
time when they signed papers to formalise their purchase. This might be most true of
consumers who had an upfront expectation, and did not change their mind, that they
would buy GAP insurance from the dealer when buying the vehicle.
Impact on shopping around and purchase consideration
Before the intervention, we expected that shopping around would increase and that
consumers would make more considered purchases.
These expectations were assumptions based on the 2014 survey about how add-on GAP
insurance consumers might change their behaviour in the future. For example, we
assumed that 10% of add-on GAP insurance consumers would choose not to buy GAP
insurance again after our intervention. We also thought that nearly a quarter (22.5%) of
add-on GAP insurance consumers would shop around and buy standalone GAP insurance
in the future.
We cannot, in this survey, compare our findings directly to these estimates, as we are
not making a like-for-like comparison. The previous survey asked GAP insurance buyers
whether they intended to buy GAP insurance in the future. We do not ask these questions
in the 2018 survey. However, we do set out relevant, comparable information below. For
example, we know how many people who did not buy GAP insurance this time did buy it
in the past.
Deciding to buy GAP insurance before buying the vehicle
Table 6.3 shows that nearly half of all consumer types had decided, before buying a
vehicle, whether they were going to buy GAP insurance. This means that our
intervention’s impact on these consumers was probably limited.
Table 6.3 also demonstrates that some consumers might have been influenced by our
intervention. For example, 20% of standalone GAP insurance consumers indicated that
they made their decision to buy GAP insurance after buying the vehicle.
Table 6.3: Proportion of consumers deciding whether to buy GAP insurance
across different stages of the sales process
Percentage of consumers deciding whether to buy GAP
insurance
Consumer group
Before buying a
vehicle
During buying a
vehicle
After buying a
vehicle
Add-on GAP insurance
buyers
49%
43%
8%
Standalone GAP
insurance buyers
53%
27%
20%
Source: PwC Research
The results show that GAP insurance is more of a planned purchase than before. Our
market study found that 59% of add-on GAP insurance buyers reported not having
thought about buying the product until the day they bought it. It appears that consumers
are making more appropriate purchasing decisions after our intervention.
Shopping around was higher than average (64%) among consumers who considered, but
did not buy, GAP insurance. Nearly half of these consumers decided not to buy GAP
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
42
insurance before buying the vehicle. Among the remaining consumers, around half took
at least a day to reach their decision not to buy. This shows that this group’s decision not
to buy GAP insurance was, at least to some extent, an informed one.
There is also evidence that the deferred opt-in affected consumers who were offered GAP
insurance but did not buy it. Around 40% of these consumers (ie consumers who
intended to buy GAP insurance and recalled a delay in the sales process) reported
changing their mind during the process.
Although these findings relate to a small subset of consumers, they are potentially useful
for our future work. We might assume that, without our intervention, these consumers
would have bought add-on GAP insurance. However, potentially because of our
intervention, they chose not to. Note that we cannot tell, from a survey, what caused
these consumers not to buy GAP insurance at the point-of-sale. But we do think that our
intervention had a role in their decision.
High levels of repeat buying
Table 6.4 shows that a greater proportion of consumers who previously bought GAP
insurance are deciding to buy it again. This is consistent with Table 6.3 where 49% of
add-on GAP insurance buyers had decided to buy it before buying the vehicle (up from
33% in 2014). The evidence indicates that new GAP insurance buyers are now more
likely to buy standalone rather than add-on GAP insurance than before.
50
Table 6.4: Proportion of consumers who had bought GAP insurance before
Consumer group
Pre-intervention survey
(2014)
Post-intervention survey
(2018)
Add-on GAP insurance buyers
35%
66%
Standalone GAP insurance buyers
36%
57%
Non-GAP insurance buyers
N/A – not surveyed in 2014
20%
Source: PwC Research
This repeat buying behaviour also influences consumers’ decision-making. Two-thirds of
previous GAP insurance buyers decided to buy it again before they started looking for a
car. By contrast, 20% of first-time GAP insurance buyers reached the same decision
before buying a car.
There was little evidence to suggest major disruption to habitual behaviour. 20% of
consumers who considered GAP insurance but did not take out the product had bought
GAP insurance previously.
Shopping around
Table 6.5 shows that shopping around more than doubled for add-on GAP insurance
consumers after our intervention. Again, relative to our market study findings, this
suggests that consumers are more engaged with the decision-making process after our
intervention. This is a positive impact of our intervention in this market.
51
50
Before our intervention, the percentage of repeat purchases for add-on and standalone GAP insurance
was similar. However, the repeat purchasing behaviour is more prevalent among add-on GAP insurance
consumers.
51
Notwithstanding that we know that shopping around takes time.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
43
Table 6.5: Proportion of consumers who shopped around
Pre-intervention survey
(2014)
Post-intervention survey
(2018)
Add-on GAP insurance buyers
17%
45%
Source: PwC Research
Table 6.6 shows that repeat behaviour and prior commitment to buying GAP insurance is
not associated with a lack of shopping around (and, therefore, engagement with the
decision-making process).
Table 6.6: Proportion of consumers who shopped around in 2018, by consumer
group
Consumer group
Percentage of consumers who shopped
around
Consumers who decided to buy GAP
insurance before buying a vehicle
75%
Consumers who decided during/after
buying a vehicle
32%
Previous GAP insurance buyers
61%
First-time GAP insurance buyers
46%
Source: PwC Research
Figure 6.1 sets out reasons why consumers decided to shop around. Standalone GAP
insurance buyers’ focus was on getting the best price. Consumers who considered, but
did not buy, GAP insurance tended to shop around out of habit. There were many
reasons for add-on GAP insurance buyers shopping around, with no clear single reason.
Around 75% of consumers spent between 30 minutes and 2 hours shopping around.
Add-on buyers were significantly more likely to spend less than 30 minutes shopping
around when compared with standalone buyers and those who considered, but did not
buy, GAP insurance (16% compared with 10% and 8%, respectively).
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
44
Figure 6.1: Reasons for shopping around
Base: All who shopped around for GAP insurance (add-on purchasers 267; standalone purchasers
109, considered 74)
Source: PwC Research, chart recreated by FCA
For those who bought GAP insurance but did not shop around, the main reason given was
being happy with the price quoted (32%).
However, 28% of these buyers were unaware that they could buy GAP insurance from
another provider. This might, for example, suggest a lack of engagement with the
information provided by the dealership. This response appears to contradict consumers’
claim to have read the information, at least briefly. The figure drops to 20% for those
who claimed to have read the written information provided by the dealership thoroughly.
There are many explanations why consumers may have been unaware, despite having
claimed to have read the information thoroughly. Possible explanations may include:
• the information is not being included by all dealerships
• the information is included, but is not prominent
• the information is included, but consumers do not understand it
• some consumers could have overstated how thoroughly they read the information
Within the limits of the survey, it is difficult to say what potential impact each of the
above may have had. What we can tell is that, despite our intervention, a proportion of
consumers remain unaware of an alternative way to buy GAP insurance.
52
Another possible explanation is the influence of the salesperson. The salesperson being
convincing was the top response (32%) among add-on buyers when asked about why
52
As in Section 4, this is not to say, however, that all of these consumers would choose to buy elsewhere
(eg some may choose to buy the higher-priced add-on option due to wanting to avoid shopping around).
37%
35% 35%
34% 34%
33%
31%31%
29%
40%
48%
37%
22%
20%
23% 23%
14%
32%
51%
27%
15%
0%
10%
20%
30%
40%
50%
60%
I wanted to
compare policies
to find out what
the best coverage
was
I wanted to find
out if it was really
worth buying
I thought I might
be able to get a
cheaper price than
the one I was first
quoted
I wanted to
compare prices
between more
than one provider
I always shop
around for
insurance
I wanted to check
if any deals or
offers were
available
I wanted to see if
I could find a
product from an
insurer/brand I
trusted
% of consumers
Add-on Standalone Didn't purchase but considered
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
45
they chose their GAP insurance provider. This represents a change from our pre-
intervention survey in two ways:
• 78% of add-on buyers indicated that the salesperson had convinced them in our pre-
intervention survey
• the salesperson’s influence was very closely followed by other reasons (eg the cover
amount and convenience) in the post-intervention survey, which is unlike the pre-
intervention survey
It appears that salespeople remain influential in consumers’ decision-making, but to a
lesser extent than before our intervention.
Add-on buyers are more confident about GAP insurance
Our survey asked all GAP insurance consumers:
• how confident they were in their understanding of GAP insurance
• to respond to 9 true/false statements, based on facts that they would have received
in the prescribed information, about GAP insurance to test their actual knowledge
Confidence in GAP insurance knowledge
Table 6.7 shows add-on GAP insurance buyers are more confident in their GAP insurance
knowledge after our intervention. There is now little difference between their confidence
and that of standalone GAP insurance buyers.
Table 6.7: Proportion of consumers that were ‘somewhat confident’ in their GAP
insurance knowledge
Consumer group
Pre-intervention survey
(2014)
Post-intervention survey
(2018)
Add-on GAP insurance buyers
79%
95%
Standalone GAP insurance buyers
94%
97%
Source: PwC Research
There is some evidence to suggest a link between consumer confidence and engagement
in the purchasing process. Confidence appeared to be highest (ie ‘very confident’) among
consumers that: recalled the sales process ‘very well’ (74%); had bought shopped
around (61%); or had bought GAP insurance before (57%).
Add-on buyers’ GAP insurance knowledge is now similar to standalone
buyers’
We had concerns about the knowledge gap between add-on and standalone GAP
insurance buyers. Before our intervention, we found that add-on buyers were far more
likely to answer questions incorrectly (40%) than standalone buyers (31%).
We find that, using two approaches, GAP insurance knowledge has narrowed between the
two consumer groups after our intervention:
• There is only a 1 percentage point difference between the groups when looking at
what proportion of consumers answered the majority of questions correctly (60%
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
46
add-on, 61% standalone). Those who shopped around were more likely to respond
correctly than those that did not.
• The difference in incorrect answers (ie incorrect and ‘not sure’) is now 4 percentage
points (relative to 8 percentage points in 2014
53
). This is a more comparable figure to
the 2014 work than the ‘correct’ answers figure. This is because the 2014 survey
looked at incorrect answers only.
54
Time to shop around and gather information
It is helpful to consider the relative efficacy of our intervention’s 2 measures (ie
prescribed information and the deferred opt-in). We do this to understand which measure
was more effective and to what extent. This, in turn, helps us develop a strong evidence
base on what works when intervening to tackle harm.
The measures were designed to work together. The prescribed information provides the
prompt to shop around, and the deferred opt-in offers a window in which to do so.
Nevertheless, it may be that one measure is more effective than the other in helping
consumers achieve better outcomes. In this case, and in line with Figure 2.1, we expect
consumers to reach these better outcomes, in part, through shopping around.
While the econometric analysis provides insight about the intervention’s total impact on
sales and prices, it cannot tell us about each measure’s impact. Therefore, we use the
consumer survey to help us with this.
Consumers’ views on the usefulness of the measures
We asked consumers to rate how useful they found the 2 measures.
The written information was seen as most useful by add-on GAP insurance buyers. The
deferred opt-in was most favourable to standalone GAP insurance buyers.
Figure 6.2 sets out consumers’ views on how useful the different measures were in
helping them to make their decision.
However, consumers’ view that the prescribed information improved their understanding
was not reflected in their likelihood of being able to identify correct statements about
GAP insurance. For add-on GAP insurance buyers, in particular, this may suggest that the
prescribed information acts as a prompt to shop around and reassurance, rather than
improving understanding noticeably.
53
This is different to 40% less 31%. In the 2014 survey, 46% of add-on consumers’ responses were either
incorrect or ‘not sure’, compared to 38% for standalone consumers.
54
It appears that consumers, overall, are answering a greater proportion of questions incorrectly after our
intervention. For example, 45% of standalone consumers’ responses are incorrect (compared to 38% in 2014).
However, a comparison of levels over time is not reliable here due to differences in our survey approach and the
questions asked.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
47
Figure 6.2: Usefulness of our measures in helping consumers make a decision
Base: All participants (add-on purchasers 587; standalone purchasers 121; considerers 115, non-
considerers 186).
Source: PwC Research, chart recreated by FCA
In summary, a high percentage of all consumers found that the deferred opt-in was
useful in helping them reach their decision. The perceived usefulness of the deferred opt-
in was unaffected by consumers’ awareness of the time required for an add-on seller
between introducing GAP insurance and finalising the sale.
Consumers appear to be making more informed choices
Previous GAP insurance buyers rated both measures as particularly useful. This group
were almost twice as likely as first-time buyers to rate each measure as ‘very useful’ in
helping them to make a decision. This suggests that previous GAP insurance buyers
made a more informed purchase this time.
88%
64%
70%
24%
9%
22%
20%
31%
12%
5%
27%
5%
18%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Add-on Standalone Didn't
purchase
but
considered
Didn't
consider
GAP
% of consumers
Information about GAP insurance
provided by car dealers
Useful Neither/Nor Not useful Don't know
76%
83%
79%
28%
18%
12%
14%
31%
4%
5%
4%
17%
23%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Add-on Standalone Didn't
purchase
but
considered
Didn't
consider
GAP
% of consumers
Having time to think about it
before making a decision
Useful Neither/Nor Not useful Don't know
89% 89%
86%
8% 8%
12%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Add-on Standalone Didn't
purchase but
considered
% of consumers
Information you found about GAP
insurance while shopping around
Useful Neither/Nor Not useful Don't know
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
48
Information gathered while shopping around
Regardless of the final decision made (to buy add-on or standalone GAP insurance, or not
to take out the product at all), almost 90% of consumers rated the information they
found while shopping around as useful.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
49
Section summary
Consumer benefits have improved after our intervention.
The one-off compliance costs associated with our intervention have been toward the lower
end of our expected range. Ongoing compliance costs are higher than we anticipated, but
are significantly less than the benefits of our intervention.
Overall, we find that the benefits of our intervention exceed its compliance costs.
This section summarises our analysis of the intervention’s overall impact. We do so by,
first, describing changes in the value consumers receive from GAP insurance before and
after our intervention. We then summarise firms’ costs in complying with the
intervention. We end with an analysis of how overall consumer surplus, a measure of
consumer benefits, has changed after our intervention.
55
Measuring the value of GAP insurance to consumers
Table 7.1 outlines the measures of insurance products’ value that we considered as part
of the general insurance add-on products market study.
Table 7.1: Measures of insurance product value considered in MS14/01
Measure
Description
Claims
ratios
The claims ratio shows the value of claims paid out as a percentage of the premiums
paid. It shows what financial benefit consumers might expect to receive on average
for every £1 that they spend on a product.
Claims
frequency
The claims frequency shows the number of claims paid out as a percentage of policies
sold. It shows what probability there is of a consumer making a successful claim.
Mark-ups
on net
rates
The net rate is the amount charged by an insurer to the distributor for a product. This
rate reflects the insurer’s expected claims costs (including settlements and claims
handling), operating costs and the insurer’s expected profit. Comparing the net rate
with retail prices allows us to examine the expected mark-up from net rate to retail
price for a product, and tells us something about the ability of distributors and/or
retailers to raise price above the core insurance costs they pay.
Source: MS14/01: General insurance add-ons: Provisional findings of market study and proposed
remedies
55
Our pre-intervention CBA set out two additional costs to consumers. These were that: i) consumers
might suffer uninsured loss due to the deferred opt-in, valued at between £90,000 and £490,000; and ii)
consumers might be inconvenienced in being unable to conclude the GAP insurance sale on the same day, which
was valued as ‘minimal’. We do not consider these costs in detail here. There is no evidence to suggest that these
consumer costs are significantly different to our pre-intervention expectations.
7 Results: Overall effects
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
50
We use the claims ratio as our main measure of value. This is consistent with the market
study which estimated that, between 2008 and 2012, add-on GAP insurance had an
average claims ratio of 10%.
56
We concluded that this was “exceptionally low, indicating
very poor value for money”.
57
Our pre-intervention expectation was that the claims ratio for GAP insurance would
increase after our intervention (Table 2.1).
58
Our core measure of consumer value has improved after our
intervention
We have used a different approach to the market study when calculating the claims ratio.
This helps us compare the claims ratio of policies sold before and after the intervention.
We estimate the cumulative claims ratio for all policies sold in each period, rather than
taking an average claims ratio at a given point in time, for policies sold in different
periods.
59
Most GAP insurance policies (98%) have a cover length of 3 or more years. However, our
claims data extend to only 2 years after our intervention (post-intervention data cover
September 2015 to August 2017). Our evaluation has happened too early for us to draw
conclusive findings about claims ratios.
To account for this, we estimate the claims ratio for a policy’s first 12 months of cover,
for all policies where cover length is equal to or longer than 12 months. This approach
helps us to compare claims ratios on a like-for-like basis both before and after the
intervention.
60
This is different to the claims ratio definition provided above. Our
definition used for this analysis indicates what financial benefit consumers might expect
to receive on average in the first 12 months for every £1 that they spend on a product.
61
Due to these data constraints, our analysis cannot show full claims ratio movements after
our intervention. The analysis presented here is an initial indication of what has
happened. This approach does not tell us, definitively, how the policy lifetime claims ratio
has changed.
Figure 7.1 shows that the average 12-month add-on GAP insurance claims ratio
62
was
already increasing before our intervention, albeit from a low base. Before intervening, it
had increased from 1.2% (policies sold in September 2013) to 2.9% (policies sold in
August 2015).
56
In MS14/01, we calculated claims ratios as: claims incurred (net of reinsurance and excluding claims
management costs) in a given year divided by net earned premium (plus IPT, net of reinsurance but including
distributor commission) in a given year. The market study estimated an average claims frequency between the
years 2008 and 2012 of 0.3% for add-on GAP insurance which was considered to be very low. See: Annex B:
Methodology and analysis of firm data, MS14/01, Page 11
57
General insurance add-ons: Provisional findings of market study and proposed remedies, MS14/01,
Section 1
58
This was not an explicit pre-intervention expectation. However, it is a matter of interest. This would be
driven by: a potential reduction in average GAP insurance; and more appropriate consumer purchasing.
59
In this evaluation, we calculate claims ratios as the total value of claims incurred divided by the sum of
the retail price to the consumer including IPT for all policies sold in a given period.
60
Conversations with firms, who provided us with data, informed this finding.
61
The likelihood of claiming on a GAP insurance product, and thus its ‘value’ to consumers, increases with
time. As such, this definition is likely to underrepresent GAP insurance’s true value to the consumer.
62
We use the term ‘claims ratio’ as short-hand for ’12-months claims ratio’ in the rest of this sub-section.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
51
Table 7.2 compares changes in the average 12-month claims ratio for the 12 months
before and after our intervention. It shows that the average add-on GAP insurance claims
ratio increased from 2.5% to 3.1%. This shows that the claims ratio has increased after
our intervention, although only by a small amount (and notwithstanding the data
limitations).
This increase is driven by a higher claims frequency rate. The claims frequency rate for
add-on GAP insurance increased from 0.7% to 0.9%.
Our informal engagement with firms provided useful views to support our analysis of a
claims ratio 12-month proxy. The overall view was that add-on GAP insurance claims
ratios have increased both before and after our intervention.
Figure 7.1: Add-on and standalone GAP insurance 12 month claims ratio
Source: FCA analysis of GAP insurance transaction data provided by firms
Table 7.2: Average add-on and standalone GAP insurance 12 month claims ratio
GAP insurance market
12 months before intervention
(September 2014 – August
2015)
12 months after intervention
(September 2015 – August
2016)
Add-on
2.5%
3.1%
Standalone
2.0%
2.5%
Source: FCA analysis of GAP insurance transaction data provided by firms; FCA MS14/01: General
insurance add-ons: Provisional findings of market study and proposed remedies
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
4.5%
Sep-13 Dec-13 Mar-14 Jun-14 Sep-14 Dec-14 Mar-15 Jun-15 Sep-15 Dec-15 Mar-16 Jun-16
Claims ratio for the first 12 months of policies 12 months or longer
Add-on GAP insurance Standalone GAP insurance
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
52
One-off and ongoing compliance costs
Our pre-intervention CBA indicated that firms would incur one-off costs of complying with
our intervention. These costs include revisions to consumer sales literature and changes
to systems and processes. We acknowledged that firms might incur some incremental
ongoing costs such as staff training, but thought that such costs were unlikely to be
significant.
Table 7.3 shows our CBA’s costs estimates. We have used the following data to estimate
the actual one-off and ongoing costs attributable to our intervention:
• data requested from the National Franchised Dealers’ Association (NFDA)
63
• data requested from a sample of insurers and distributors of GAP insurance
• GAP insurance transaction data provided by firms
64
Table 7.3 shows how firms’ actual costs (one-off and ongoing) of complying with our
intervention compare to our pre-intervention expectations.
Table 7.3: Estimates of one-off and ongoing costs to firms as a result of our
intervention
Estimate source
One-off costs
Ongoing costs
CP14/29
£5.0 million
Minimal
PS15/13
£5.0 million to £20.0 million
Minimal
Post-intervention
assessment of firm costs
£4.8 million to £8.2 million
£1.4 million
Source: CP14/29; PS15/13; FCA analysis of data provided by firms and the NFDA
We estimate that the actual one-off cost to dealers of complying with our intervention
was £4.8 million to £8.2 million.
65
The lower end of the range is 4% less than our pre-
intervention lower end of the range of £5m, while the upper end of the range falls within
our pre-intervention expectation range. Examples of these costs include: IT development
costs; lower, but still significant, costs in updating documentation; putting in place
governance arrangements; and running initial training sessions for staff.
We estimate that the actual ongoing costs to dealers of complying with our intervention
is £1.4 million.
66
Ongoing costs appear higher than the minimal significance we expected
63
The NFDA represents its members, which collectively operate around 4,100 franchised dealer sites.
Between April and May 2018, they voluntarily collected information from some of their members on the costs
associated in complying with our intervention. They provided us with two sources of information: i) a detailed
breakdown of costs provided by a dealer group with over 100 dealer sites; and ii) an aggregated cost estimate
provided by a number of dealer groups which collectively operate over 300 dealer sites.
64
Using transaction data from firms, we estimate that there are around 7,900 dealer sites in the UK which
sell add-on GAP insurance.
65
The detailed breakdown return suggested an average one-off cost of £547 per dealer site. The
aggregated return suggested an average one-off cost of £982 per dealer site. We multiply these cost estimates
by the total number of dealer sites in the UK which sell add-on GAP insurance (7,900). We then add total
incremental one-off compliance costs for add-on GAP insurance underwriters and distributors where this was
provided in response to our data request. The sum of these costs came to £0.45 million. This approach provides
a range for total one-off costs of £4.8 million to £8.2 million.
66
The detailed breakdown return suggested an average ongoing cost of £181 per dealer site. We multiply
this cost estimate by the total number of dealer sites in the UK which sell add-on GAP insurance (7,900). We then
add the total incremental ongoing compliance costs for add-on GAP insurance underwriters and distributors where
this was provided in response to our data request. The sum of these costs came to £0.02 million. This approach
provides a total ongoing costs figure of £1.4 million. The aggregated return suggested an average ongoing cost
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
53
to find. We see the difference as being driven by the higher than anticipated ongoing
costs of training staff. Other ongoing costs mentioned by dealers related to customer
transaction
67
and governance costs.
Consumer surplus has improved after our intervention
In our pre-intervention CBA, we estimated our intervention’s impact on consumers by
calculating how their consumer surplus might change when compared to a scenario of no
intervention. Consumer surplus is a measure of consumer benefits.
We expected consumer surplus to improve through:
• some add-on GAP insurance consumers making more appropriate purchasing
decisions
• some add-on GAP insurance consumers shopping around and finding a better price for
the same coverage in the standalone market
• there being greater awareness that GAP insurance can be bought as a standalone
product, leading to a subsequent increase in standalone sales
We calculate how consumer surplus changes after our intervention by using a similar
approach and assumptions
68
that we used in the pre-intervention CBA. We do, however,
use updated and more comprehensive data for these calculations.
To estimate consumer surplus, for both add-on and standalone GAP insurance, in the
year before and after intervention, we:
1. observe annual metrics, including sales and average prices
2. estimate the demand curve for that year using these market metrics
3. calculate consumer surplus as the area between the demand curve and price
4. subtract the deadweight loss associated with any over-purchasing
Our analysis indicates that consumer benefits have increased by £26 million to £28
million a year after our intervention (see Annex 1 for our calculations). This is a positive
outcome and consumers are, overall, better off after our intervention.
Table 7.4 summarises our estimates of consumer surplus before and after our
intervention.
of £1,403 per dealer site, suggesting total ongoing costs of £11.1 million. Following feedback from the NFDA, we
consider that this cost estimate is an outlier and includes costs which are not solely attributable to the incremental
impact of our intervention (ie they appear to be ongoing costs associated with selling GAP insurance, rather than
specifically those attributable to our intervention).
67
This includes, for example, the cost of the additional time taken by staff in discussing GAP insurance
with consumers following our intervention.
68
As we set out in Annex 1, we update the assumption around initial over-purchasing. We update the
assumption to 20% in line with updated information from our firm data analysis (ie claims ratios) and assumptions
used in recent interventions (see CP 18/12).
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
54
Table 7.4: Estimates of consumer surplus in the GAP insurance market
Pre-intervention
expectation
69
Observed change
Percentage change in
consumer surplus after our
intervention
70% to 125%
(Range based on the two
different price change scenarios
in Table 5.1)
33% to 35%
Source: FCA analysis of GAP insurance transaction data provided by firms
We find that the consumer surplus has increased after our intervention. However, this
increase is not by the same proportion as we thought it would be before intervening.
Reasons for these differences are primarily due to:
• no fall in add-on GAP insurance prices after our intervention
• the lower than expected increase in standalone GAP insurance sales (either from
substitution or new consumers entering into the GAP insurance market)
70
Higher consumer benefits outweigh the costs
Our analysis finds that consumer benefits (£26 million to £28 million a year) after our
intervention exceed firms’ total costs of implementing our intervention. This includes
one-off costs of £5 million to £8 million and ongoing costs of £1 million a year.
After the first year of our intervention, we estimate that the ongoing net benefits
71
are
approximately £25 million to £27 million a year.
72
69
Annex 1 explains that we update CP14/29’s CBA approach with updated pre-intervention data. This is to
ensure that the baseline consumer surplus figures are consistent. We have adjusted one of our pre-intervention
assumptions based on updated information. Not adjusting this assumption would be likely to decrease our
estimate of our intervention’s impact on consumer surplus. However, it would remain positive.
70
This is in line with our findings in Section 4. Based on our calculation approach, consumer surplus would
have been higher if there had been more standalone GAP insurance sales. The calculation assumes that some
consumers value buying GAP insurance (be that as an add-on or as a standalone). Consumer benefits would be
far higher, for example, if we assume that all add-on GAP insurance sales that did not happen because of our
intervention should not have happened.
71
Some of the net benefits figure may be a transfer from firms to consumers.
72
Estimated as the increase in consumer surplus of between £26 million a year and £28 million a year,
minus the ongoing cost to firms of £1 million a year.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
55
The learnings from this evaluation are a function of our intervention in this specific
market. Our lessons here may not read across directly to, for example, a similar
intervention in another market. Nevertheless, they provide useful insight in helping us
anticipate potential ways of reducing harm and the likely impact of doing so. We set out
the main lessons learned in Table 8.1.
Table 8.1: Main lessons learned from our evaluation
#
Lesson learned
Comments
1
Our intervention has
had a stronger impact
on sales than prices
We did expect this before intervening. We were unclear on
how prices might change. In practice, the sales effect has
been far greater, with very little impact on prices.
2
Attempts to break the
point-of-sale
advantage for a ‘sold’
product are likely to
reduce total
purchases, rather
than diverting
consumers to the
non-point-of-sale
market
The reduction in add-on sales has, largely, been due to
consumers no longer buying GAP insurance rather than being
diverted to buying standalone GAP insurance. We think this is
because of the interaction between how consumers make
decisions and the deferred opt-in measure. The efficacy of a
deferred opt-in measure is likely to be a function of the
specific context, including how buyers and sellers interact.
We set out, in Sections 4 and 6, that although some suitable
sales may not have taken place, overall, we see this reduction
in add-on sales as a positive outcome for consumers.
3
Pre-intervention
expectations should
be based on a range
of evidence
It is possible that our pre-intervention evidence (namely, the
consumer survey and how it was used):
• overstated the impact of the intervention on switching to
the standalone market
• underestimated the number of consumers who would make
a more considered purchase given the tools (information
and time) to do so
Recent academic literature in this area points to demand-side
remedies having a more modest impact on competition. Our
analysis, especially on the small increase in the standalone
market’s share of total sales, is in line with the research. It is
likely that our intervention had an impact among a subset of
consumers. Our expectations implied a much larger impact on
consumers.
4
Add-on sellers play an
important role in
introducing the
product to buyers – in
their absence, the
standalone market
may be smaller
Add-on sellers make consumers aware about GAP insurance.
One of our potential interventions was to ban the sale of add-
on GAP insurance. Had we done this, some consumers, for
whom GAP insurance might be a valuable purchase, may not
know that the product exists.
8 Lessons learned
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
56
#
Lesson learned
Comments
5
The salesperson still
plays an important
role in convincing
consumers to buy any
add-ons
This type of intervention cannot remove a point-of-sale
advantage – it can only look to reduce it. The salesperson’s
influence has fallen noticeably after our intervention and
consumer outcomes appear to have improved too.
We might need to consider alternative measures in markets
where we are concerned about poor product value and the
strong effect of salespeople on consumers’ decision to buy a
potentially unsuitable product.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
57
Our pre-intervention CBA’s approach to calculating consumer surplus
In our pre-intervention CBA, we converted our intervention’s impact on consumers into
monetary terms. We did this by estimating how their consumer surplus might change
relative to a scenario of ‘no intervention’.
The pre-intervention CBA estimated the pre-intervention consumer surplus for the add-
on GAP insurance market only. This is because there were little data available on the
standalone market. We used annual sales and average price data that we could observe
at the time. We then made many simplifying assumptions to helps us estimate consumer
surplus.
The main assumptions were:
1. the demand curve for GAP insurance is linear
2. the standalone market is perfectly competitive (ie price equals marginal cost)
3. the price elasticity of demand (ie the sensitivity of sales to price changes) is the same
in the add-on and standalone GAP insurance markets
Our approach adjusted the estimate to account for those who may not buy GAP
insurance if they considered their needs in more depth (one of the intended outcomes of
the intervention). We applied an estimate of 10% to account for this in the consumer
surplus calculation approach in the add-on GAP insurance market.
73
That is, we assumed
that 10% of sales were made to consumers who, based on their preferences, did not
need add-on GAP insurance.
Our approach to calculating post-intervention consumer surplus
We use a similar approach to the pre-intervention CBA. We do this for consistency and
comparability between the pre- and post-intervention estimates. However, we use
updated and more comprehensive data received from firms as part of this evaluation.
The pre-intervention CBA estimated consumer surplus for 2 scenarios:
1. no change in add-on price
2. a fall in add-on price by 16.7%
We only estimate consumer surplus for a single price scenario. This is because we see
the actual change in average add-on GAP insurance prices.
Figure 8.1 sets out the different components of our consumer surplus calculation.
73
This was based on consumers’ indication of regret during our market study’s consumer survey.
Consumer surplus
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
58
Figure 8.1: A summary of how we estimate changes to consumer surplus after
our intervention
Source: FCA analysis; CP14/29
Although the calculation approach is similar pre- and post-intervention, there are some
additional steps and assumptions that we need to make/change.
#
Update
Comments
1
We calculate consumer
surplus for the
standalone market
We did not previously calculate consumer surplus for the
standalone market due to data availability. We collected pre-
intervention data in the evaluation. This allowed us to calculate
consumer surplus for the standalone market.
2
We update our
assumption around
consumers making more
considered purchasing
decisions
We have collected data and made recent interventions which
suggest that our assumption that 10% of consumers may make
more considered purchasing decisions might have been too low.
We based our estimate on consumer responses to a survey
question on whether they would buy add-on GAP insurance again
if offered the chance. Consumer survey responses can, at times,
be influenced by consumer behavioural biases (ie confirmation
bias) and other factors (ie time elapsed since purchase).
We consider that the appropriate approach is to update this
assumption to 20%.
3
We do not assume that
over-purchasing is fully
removed
Our causal analysis provides us with an estimate of our
intervention’s impact on add-on GAP insurance sales. We can
estimate to what degree we have reduced over-purchasing. We
do this by comparing the estimated percentage fall in add-on
GAP insurance sales with the assumed percentage of over-
purchasing.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
59
We take two approaches to calculating consumer surplus after our intervention to provide
our estimated range:
• One approach assumes that add-on customers that become standalone customers
take on the demand characteristics of standalone customers.
• The other approach assumes that add-on customers keep their demand preferences.
We set out a summary of our calculations in the Table 8.2 and Table 8.3. The difference
between row 5 in the two tables below represents the lower end of the range change (ie
£26 million). In Figure 8.2, we also provide an illustration of how the different factors in
the tables relate to a demand curve.
74
Table 8.2: Summary table for pre-intervention CBA calculations (September
2014 to August 2015 data)
Add-on
Standalone
Total
Comments
(1) Price
£375
£186
Firms' data, weighted monthly average
(2) Quantity
809,508
61,149
870,657
Firms' data, annual sales; add-on sales reduced
by 20% based on assumed over-purchasing from
consumer survey
(3) Price
elasticity of
demand
-1.98
-1.98
= add-on price / (add-on price - marginal cost);
marginal cost = standalone price; assumed that
these are the same in both markets
(4) Price that
makes quantity
demanded = 0
£564
£279
(quantity = a + b*price, therefore price = (0 - a)
/ b); b = (3) * [(2) / (1)]; a = (2) - b*(1);
Additional calculations required for add-on to
compare observed sales and over-purchasing
assumption
(5) Consumer
surplus
£71,694,581
£8,298,783
£79,993,365
= 0.5 * [(4) – (1)] * (2); Additional calculations
required for add-on to compare observed sales
and over-purchasing assumption
Source: FCA analysis of GAP insurance transaction data provided by firms; CP14/29
74
At higher prices, consumers are willing to buy less of a good or service. As the price falls, they buy more.
Therefore, the demand curve is downward-sloping.
EP 18/1: An evaluation of our guaranteed asset protection insurance intervention
60
Table 8.3: Summary table for post-intervention calculations (September 2015 to
August 2016 data)
Add-on
Standalone
Total
Comments
(1) Price
£379
£177
Firms' data, weighted monthly average
(2) Quantity
940,856
84,721
1,025,577
Firms' data, annual sales; add-on sales reduced
by 19.4% based on causal sales analysis
(3) Price
elasticity of
demand
-1.87
-1.87
= add-on price / (add-on price - marginal cost);
marginal cost = standalone price; assumed that
these are the same in both markets
(4) Price that
makes quantity
demanded = 0
£581
£271
(quantity = a + b*price, therefore price = (0 -
a) / b); b = (3) * [(2) / (1)]; a = (2) - b*(1)
(5) Consumer
surplus
£95,027,977
£11,128,005
£106,155,981
= 0.5 * [(4) - (1)] * (2). Additional calculations
required for add-on to compare observed sales
and remaining over-purchasing
Source: FCA analysis of GAP insurance transaction data provided by firms; CP14/29
Figure 8.2: Illustration of the different rows in Table 8.2 and Table 8.3
Source: FCA analysis
Note: We do not show the price elasticity of demand on the graph. It is the change in the slope as
we move along the demand curve.
© Financial Conduct Authority 2018
12 Endeavour Square, London, E20 1JN
Telephone: +44 (0)20 7066 1000 Website: www.fca.org.uk
All rights reserved
