Neurofinance and decision-making

neurofinance and decision-making article now available on Neuroprofiler's website

Neurofinance and decision-making: edited by Maria Gabriella Ceravolo, Gianmario Raggetti, Lucrezia Fattobene, translated and adapted by Neuroprofiler. 

Key findings

Decision-making, including in the financial sphere, is largely modulated by automatism and the unconscious. Neuroscience (and neurofinance) is essential for studying the stages of decision-making that affect the subject’s unconscious choice.

Factors linked to the presentation of visual information (color, location), rather than content, can be decisive in choice.

What is neurofinance?

As a relatively new discipline, neurofinance combines finance, neuroscience and psychology to advance theories and knowledge related to decision-making. The majority of neural processes that guide choices, including economic-financial ones, are automatic and unconscious by nature, and are therefore difficult to assess via self-evaluation.

Neuroscience offers research methods such as functional magnetic resonance imaging, electroencephalography, eye-tracking and facial expression recognition, which can shed light on the neural mechanisms of economic-financial decision-making. 

Decision-making and the limits of the human brain

Decision-making is a cognitive process that can be defined as “the ability to select an advantageous response from a set of available options”.

Whatever the domain involved (from the purchase of consumer goods to the response to an election, via the selection of financial products), human beings have to deal with cognitive resources, knowledge and, sometimes, limited time availability. Hence the need to “filter” information.  Indeed, our brains quickly navigate between those deemed most relevant to the final decision and those that are more detailed.

In general, the number of stimuli is so high that it is impossible to process each one systematically. The functional limitations of the human brain make it impossible to construct an effective behavioral response to every stimulus received. At the physiological level, therefore, the need arises to select the sensory stimuli to be taken into account in order to organize and stimulate behavioral responses that are congruent and effective.

In this sense, all stimuli continuously collected by the sensory system and transferred to the brain undergo selection before being processed. The mechanism that enables a stimulus to overcome this selection, to the detriment of others that are inhibited, is that of selective attention: a process that is mainly automatic and partly voluntary.

  • In its automatic phase, it can be linked to the intrinsic characteristics of the stimuli derived from the observed sources. For example, shape, color, location or clutter.
  • In the will phase, on the other hand, motivational aspects dominate. In other words, the individual’s objectives and expectations.

Decision-blocking in the financial sector

The financial sector offers a wide range of financial products and services, accompanied by information and documentation. As a result, investors are continually exposed to financial information and are often confronted with problems of information overload.

To increase transparency and promote consumer protection, financial authorities are introducing succinct disclosure documents that present the main features of products. This enables consumers to assess their quality.

These summaries are standardized throughout Europe, as consistency facilitates comparison, which can improve decision-making. Validation of information documents is generally carried out by combining qualitative interviews with quantitative surveys of consumers, who are asked to comment on the clarity of the information they receive.

Research in neuroeconomics suggests the possible limits of self-reported measures, and calls for the evaluation of decision-making by combining economics and finance with neuroscientific theories and methodologies. 

How can attention process be studied using neurofinance and decision-making approaches?

In recent years, a number of researchers have begun to study a specific stage in the decision-making process. Namely, the processing of visual information, using the non-invasive technique of eye-tracking.

Capturing the visual attention process with eye-tracking

The brain constantly receives stimuli from the environment, which are selected by automatic processes, then processed and interpreted. In the case of visual stimuli, the first motor reactions set in motion by the brain involve activation of the eye muscles: the gaze is thus fixed, “focusing” images of objects/phenomena deemed “relevant”, while those identified as “background noise” are excluded from processing.

It can be argued that eye movements are indicators of attentional processes, and that their evaluation enables us to predict which information most influences the final decision.

With the eye-tracking method, the minute movements made by the eyeballs while an individual is observing a controlled visual stimulus (an image or a document) are measured non-invasively, safely and objectively: we thus obtain a series of quantitative parameters, such as background noise level, background noise intensity, duration of exposure, and so on.

Some studies on the visual attention process in neurofinance and decision-making

In some research carried out by BrainLine on investment products described by the Key Investor Informational Document (KIID) (Ceravolo et al. 2019, 2020), it was observed how the layout and color of information documents affect the allocation of attention and the perception of product attractiveness by the subjects interviewed. In a succession of visual or auditory information, the position occupied by a stimulus represents a significant factor in the probability of it being considered as the object of attention, and deserves to be taken into consideration.

The anchoring effect is the phenomenon whereby individuals attribute a determining value (with a view to subsequent decision-making) to the first or last (the anchor) in a set of information (Turner & Schley, 2016). Numerous studies testify to the use of anchoring even when making decisions in real estate (Lambson et al. , 2004) or finance (Baker et al. , 2016; Dougal et al. , 2015).

In a recent study (Ceravolo et al. , 2021), BrainLine researchers investigated the role of anchoring in subjects’ assessment of the attractiveness of current account prospectuses by reading and evaluating a piece of information (Fee Information Document – FID). The aim of the FID, introduced by the Payment Accounts Directive, is to improve the transparency of charges and information relating to current accounts. 

The study, carried out on 70 cases, confirmed the tendency of respondents to anchor their judgement of product attractiveness to the information presented in the top left-hand corner (in this case the annual fee), neglecting other elements and thus making unprofitable decisions in many cases. Subjects with low levels of financial education were more likely to use the anchoring heuristic, basing their decisions on biased assessments of available information.

Decision-making processes, algorithms and advisors: who can we trust?

To cope with the abundance of information and its growing complexity, individuals often decide to rely on operators in the banking and financial sector. Numerous researchers have studied the appearance, personality and behavioral characteristics of financial advisors, which influence consumers’ willingness to follow their advice.

In finance, no study to date has investigated the advisor’s influence on subjects’ visual attention mechanisms and the likelihood of them accepting the advice they receive.

A recent study (Fattobene et al., 2022) attempted to fill this gap by assessing the distribution of visual attention. Subjects analyzed a pre-contractual information document on a consumer loan application (the Standard European Consumer Credit Information – SECCI), while alternately receiving advice from a human operator or an algorithm.

It was observed that attention to specific interests (notably those related to costs) was modulated by the type of advisor. Subjects show a different distribution of attention, and in particular of costs, when the advice to buy the product is provided by a human rather than an algorithm. The different attention mechanisms according to advisor type are followed by a different tendency to trust the algorithm, depending on whether the contract conditions are objectively advantageous or disadvantageous.