There are important behavioural reasons why financial consumers tend to make suboptimal financial decisions, and financial firms are often in a position to exploit them. So far, however, well-meaning regulatory interventions have regularly made consumers worse rather than better off, due to their own behavioural blind spots. Taking recent developments in behavioural science and economics into account, this article stresses that the limited cognitive power of financial consumers and their present-biased preferences are the main obstacles on which traditional regulatory interventions have often stumbled. This article also stresses that protective interventions designed to modify consumers’ choice architecture can only be effective if they take into account individual differences in behaviour and degrees of rationality. 

The article predicts that the combination of behavioural insights and big data analysis, while raising issues relating to privacy and equality before the law, will open up the possibility of tailoring the regulation of financial market behaviour to more empirically valid characteristics. Analysis of big data sets (“Big Data”) can be used to find correlations and predict behaviour. Private law can potentially embrace and harness these insights, as well as other results from behavioural science, and use them to solve problems such as unfair terms, debt payment issues, or over-selling, in innovative ways. The article’s main claim is that the combination of behavioural economics and Big Data analysis opens up the possibility of tailoring the regulation of market behaviour to more empirically valid characteristics and to personalise it. For the purpose of this brief article, I will focus on the example of consumer finance. 

Consuming financial products

Retail clients engage with the financial system in various ways: by opening accounts face-to-face or via a website, getting a personal loan, investing in bonds or shares, etc. Though there is not much room for negotiating the offers, consumers can find attractive opportunities in the financial market and improve their well-being, even as modest investors. There is a lot of diversity among financial products. Some investments can easily be undone (e.g., shares freely tradeable on an exchange might effortlessly be redeemed), while others are stickier (e.g., early repayment of personal loans might include a substantial charge). Products also vary in complexity: a life insurance policy that offers the benefit of a lump sum pay-out upon premature death of the insured is a simple product; life insurance coupled with a savings component, which converts at a future point into a payment stream tied to stock market returns, is a more complex product. 

While individual consumer markets have their own local features, it is a common theme across jurisdictions that financial markets are complex and expose consumers to greater risks than other marketplaces. Some risks are product specific and derive from the speculative nature of the instrument. Other risks are more general: even products such as insurance products that are not indexed on the ups and downs of the financial market do expose financial consumers to ill-suited or expensive choices.

Consumers make predictably costly mistakes in financial markets: they buy high and sell low, invest in attractively presented instruments they do not understand, and pay excessive fees. It is now widely recognised that individual cognitive processing has limited capacity. The human brain deploys mechanisms to economise on cognitive processing in decision-making: this saves time but results in systematic errors in decision-making, which might not happen if the person was given unlimited time and the analytic resources to make these choices. Only close attention to consumers’ behaviour, including their imperfect analyses and distorted judgment, can shed light on the risks that financial markets present to consumers, and how ‘financial citizens’ might be correctly protected and empowered.

Behavioural insights on consumer protection 

Existing rules are written with a fictional (rational) consumer in mind: someone who reads labels and disclosures, takes the time to scrutinize contracts, and checks the terms and conditions. In reality, we all use shortcuts to make decisions, relying on intuition rather than deliberation. In evolutionary terms, trading off accuracy for speed appears rational in the presence of finite mental processing power. Decisions are made on the basis of heuristics: they spare processing power, but also yield only approximately accurate results. Many potential errors, anomalies or biases in consumer decision-making relative to the decisions expected from individuals who are seeking to maximize their own welfare, may be explained by the use of rules of thumb leading to incorrect beliefs. A few examples illustrate this phenomenon.

We are unlikely to make an active choice when one option is a default (“inertia”). An example of this is automatically renewable contracts, such as are often found in banking services. It has also been established that we can only deal effectively with a limited amount of information (“information overload”). For this reason, it is not sensible to throw into the terms and conditions of loan agreements more information than consumers can process. Another example is present bias. This causes us to discount costs that seem distant in the future (“hyperbolic discounting”). For example, a credit card with low introductory teaser interest rate and high long-term interest rates is regarded as attractive, irrespective of the total cost. A last example, “optimism bias” can lead us to misjudge the amount of use we will make of a service: thus we might believe that we will never be in a situation where we need an expensive overdraft. Errors of this kind can result in selection of a contract that does not suit our needs.

Leveraging Big Data and technology to personalise protection

Businesses have long known of these behaviours – and have exploited them. Regulations have started to incorporate insights from behavioural studies, but more can be done to harness insights from behavioural economics and, potentially, neuro-economics. And it would be useful to bridge the gap with Big Data. Big Data is indeed another key to understanding consumer behaviour. Businesses have started to exploit Big Data to improve customer relationship management and, above all, to increase their profits. 

The power of Big Data and associated predictive analytics, could also be used to improve the efficiency of consumer law. While heterogeneity among consumers often means that regulations are over- and under-inclusive, the rise of Big Data has significantly decreased the costs associated with creating and administering personalized legal rules tailored to specific individual profiles or circumstances.

As to disclosures, one possibility would be for salient messages to focus on overdraft or above-plan charges for consumers with a lower degree of will-power and who are likely to consume more than planned; they could focus on the core deal for consumers likely to remain within its limits. Whether this will be effective, or desirable, is currently an open question. 

Regarding default rules, such as caps on overdraft charges, their stickiness could be increased for customers whose profile indicates that they have a low credit score and are more likely to need overdrafts and might be the primary target of banks’ effort to have them opt out; other profiles could enjoy lower interest rates in exchange for an easier opt-out from the default. Even some mandatory protective rules (e.g., usury thresholds), which limit options for consumers, could be applied according to the individual consumer’s degree of rationality. Again, this raises questions both of practicality and policy.

In short, the combination of behavioural economics and Big Data analysis opens up the possibility of tailoring the regulation of market behaviour to more empirically valid characteristics, and to personalise it. This exciting prospect also opens up major questions relating, in particular, to how privacy can be ensured and to how justice can be achieved. 

Geneviève Helleringer is a fellow of the Institute of European and Comparative Law (IECL) at the Oxford Law Faculty and a fellow of St Catherine’s College. She is an associate law professor at Essec Business School and an ECGI research member.