![]() The FCA is taking steps to follow up with some of the firms whose trading apps we reviewed and has stated that 'some product design features could be contributing to problematic, even gambling-like, investor behaviour. We may look at aspects of this through future research and explore potential wider context and financial vulnerabilities for users of these apps, such as whether they borrow and invest and the scale of any losses. ![]() This would require further investigation. It does not tell us whether the design features themselves are causing poor outcomes such as investing in products beyond one’s risk appetite. The potential 'problem-gambling' behaviours our research has uncovered are associated with apps that have more gamification and sludge design elements. We also asked a range of questions to understand wider investing behaviours and vulnerabilities such as how frequently they traded, their financial resilience and financial literacy. Although our research looked at investments, we use the term ‘problem gambling behaviour’ here for consistency with previous studies. Scores of over 8 on the PGSI are classed as ‘problem gambling’, with those scoring between 3 and 7 classed as ‘at-risk’. We grouped respondents according to the degree of problematic behaviour they report. It asks a range of questions around problematic behaviour such as ‘Have you bet more than you could really afford to lose?’ With academic advice, we adapted this in our survey for investing. Gambling behaviour in a population is often assessed using the Problem Gambling Severity Index (PGSI). For example, if they chose a high-risk investment (such as cryptoassets) but had a low or medium risk appetite, we classified them as engaging in investing that was potentially beyond their risk appetite. We compared these preferences to their reported investment choices. We used a method from academic literature, using a hypothetical investment decision to categorise participants into high, medium or low risk aversion or not risk averse. We also included participants from a trading app of a more traditional investment platform, which does not have the features we were concerned about, as a comparator. We also undertook in-depth qualitative interviews with a sample of 20 app users. We undertook a survey with over 3,000 app users, sampling customers of 4 trading apps. There is extensive literature showing that people are much more likely to stick to a default. For example, we found that investment amounts and the amount of leverage offered were sometimes defaulted to high amounts (Figure 4). Other features are likely to influence consumer choice such as how much to invest. Displaying ‘leader boards’ for stocks that have seen the largest price changes in the last 24 hours have been shown to drive consumers to pay attention to and trade on the basis of this information, making poorer returns as a result. Research has found that push notifications can stimulate people to trade in a riskier way using higher leverage and trading larger amounts, with the biggest impact on younger and less experienced investors. We are concerned that giving information to consumers in this way may lead them to pay attention to spurious information and make investments which are not in their interests. We found frequent push notifications with the latest market news on stock movements (Figure 3) and lists that draw attention to real-time price changes by flashing red and green, as well as lists of stocks that had seen the largest price movements in the last 24 hours. For example, A recent study found that celebratory messages and badges can lead people to take on more risk when investing. We are concerned that these positive reinforcements may encourage people to trade more frequently or make investment choices that they otherwise wouldn’t. ![]() ![]() We also found the use of points, badges and rewards for undertaking certain behaviours and ‘leader boards’ that rank people based on these rewards (Figure 2). We found gamification techniques that use positive reinforcement immediately after a trade, such as celebratory messages and falling confetti (Figure 1). Many of the features used give us cause for concern, based on the existing behavioural theory and literature. We selected several firms to demonstrate their apps to us, and it was clear that an extensive behavioural design toolbox had been used to create them.
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