Evidence type: Insight i
Qualitative research is more exploratory, and uses a range of methods like interviews, focus groups and observation to gain a deeper understanding about specific issues - such as people’s experiences, behaviours and attitudes.
Quantitative research uses statistical or numerical analysis of survey data to answer questions about how much, how many, how often or to what extent particular characteristics are seen in a population. It is often used to look at changes over time and can identify relationships between characteristics like people’s attitudes and behaviours.
There are approximately 65 million active personal current accounts in the UK. These accounts generated £8.1 billion revenue in 2013; an average of £125 per account. In 2014 it was estimated that 94% of UK adults have at least one account, with 40% having two or more. While the importance and penetration of the current account market is irrefutable, there have been major public concerns about how well it works. Two of the main concerns are the low transparency of overdraft charges and the low levels of switching between personal current accounts. In 2008 the Government recommended annual summaries including charges to consumers, while in 2012 text alerts were available at all major UK banks. Over the same period, mobile banking apps were also rolled out.
This 2015 report from the Financial Conduct Authority, in conjunction with the Office of Fair Trading, looks to understand the impact of annual summaries, text alerts and mobile banking apps on customers. To infer the impact of the initiatives, monthly data was analysed (using advanced econometric methods) from customers of two major UK banks in the UK between 2011 and 2014. Account level data on a representative sample of 500,000 customers over 30 months from one bank (Bank A) was obtained, along with aggregated results over 36 months from another bank (Bank B), allowing the authors to cross-check and validate their results.
Because annual summaries are sent out on a rolling basis, some people receive them before others. This allows for a natural experiment that makes it possible to analyse their impact by comparing the behaviour of those who receive them early to those yet to receive them, while controlling for other factors.
To infer the impact of text messages and apps from customers of Bank A, the authors compare the behaviour of those who do sign up for these services to their own behaviour before doing so, along with the behaviour of those who do not sign up.
For Bank B, the authors use a spike in sign-up rates after the release of the mobile banking app as a natural experiment to estimate the impact of it. The switching behaviour or the effect of text alerts could not be analysed for customers from Bank B due to limitations of the data.