Automated advice models (including ‘robo-advice’) in financial services
Produced in partnership with Kushal Gandhi and Charles Kerrigan of CMS
Automated advice models (including ‘robo-advice’) in financial services

The following Financial Services practice note Produced in partnership with Kushal Gandhi and Charles Kerrigan of CMS provides comprehensive and up to date legal information covering:

  • Automated advice models (including ‘robo-advice’) in financial services
  • Scope and uses of robo-advisers
  • Advantages and disadvantages
  • Risk creation versus risk mitigation
  • Regulatory framework
  • Legal issues in relation to advice provided by robo-advisers
  • Record keeping is key
  • Views from the market

Automated financial product advisers or robo-advisers are automated computer systems that provide financial planning services with little or no human intervention. They are emerging across the financial service industry, helping consumers choose investments, banking products and insurance policies.

This Practice Note considers the following:

  1. Scope and uses of robo-advisers

  2. Advantages and disadvantages

  3. Risk creation versus risk mitigation

  4. Regulatory framework

  5. Legal issues in relation to advice provided by robo-advisers

  6. Views from the market

Artificial intelligence (AI) underpins robo-advice and provides an opportunity for financial institutions to develop business models in order to better meet the needs of clients. Banks are aware that they need to organise, analyse and use data to reshape business models. This is the potential of AI: offering a range of benefits from better client experience, efficient risk management and compliance through to operational efficiency. AI technology improves speed, accuracy and consistency.

As with most industries, banking clients’ expectations are changing along with technological development, and clients now expect a more personalised service. AI can perform analysis of data to determine client needs, using insights to offer more tailored products and services as well as automated and predictive resolution of service issues.

For banks, this not only means a chance to provide a better, more tailored service, but the possibility to recommend other products in the banks’ portfolios that can add further value to their business.

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