Robo-Advice Risks and Benefits

By Jim Bulling and Michelle Chasser

The Joint Committee of the European Supervisory Authorities (JCESA) is considering what regulations, if any, will be required for robo-advice throughout the European Union (EU). JCESA has released a discussion paper on automation in financial advice to assist it evaluate how robo-advice is currently being used in the EU and its potential growth in banking, securities and insurance. The discussion paper highlights what the JCESA identify as the main potential benefits and risks to both consumers and financial institutions which offer some form of robo-advice.

Benefits to consumers

  • more affordable to a wider range of consumers
  • wider range of service providers and investments
  • faster, easier and non-time-consuming
  • more consistent advice
  • advice is based on the most up-to-date market information
  • easy record keeping

Risks to consumers

  • reduced opportunity to ‘fill the gaps’ in information or to seek clarification
  • unsuitable advice because of lack of understanding how their information is used
  • not aware of bias within the advice tool
  • unclear information about the extent to which the recommendations are tailored
  • limitations, assumptions or errors within the advice tool
  • underlying advice algorithms being hacked and manipulated
  • many consumers receive similar advice which may impact investments

Benefits to financial institutions

  • fewer costs to deliver financial advice
  • access to a wider range of consumers
  • delivery of consistent consumer experience
  • easier to audit the provision of advice

Risks to financial institutions

  • exposure to litigation and reputational damage due to faulty automation
  • legal disputes due to unclear allocation of liability when a number of parties are involved in the provision of advice tools

The JCESA expects that automation in financial advice will continue to grow in the future and incorporate more sophisticated tools and increased integration of different data sources.

The discussion paper can be found here.

Copyright © 2024, K&L Gates LLP. All Rights Reserved.