Investor Expectations - Theory versus reality

Wealth Management and Private Banking

16 November 2023

DigitalInvestmentsMeeting of MindsResearchroboTechWealth Management and Private Banking

Expert: Paulo Costa, Senior Behavioural Economist, Vanguard Facilitator: Charlie MacFarlane, Managing Partner, The C & D Partnership

Headlines:

  1. Classical vs. behavioural theories of investor decision making - Classical economics assumes investors are rational and disciplined. Behavioural economics recognises emotional biases like present bias and inconsistencies.
  2. Investor return expectations track recent returns - Vanguard surveys show investors' expected returns rise after market rallies and fall after declines, often wrongly expecting the trend to persist.
  3. Human advisers provide emotional value technology lacks - Surveys show investors value human advisers for trust, understanding and personalised relationships, especially during challenging times.
  4. Leveraging both human and digital capabilities - The right balance of human and digital support depends on the client's needs and life stage, with more tech for basic investors but more human input as complexity increases. 

Discussion:

The discussion centred on various topics related to investor expectations and the role of technology in financial advice. It covered how classical economic theory assumes investors are rational, but behavioural economics shows they can be emotional and biased.

Surveys by Vanguard show investors' return expectations often mirror recent market performance, with high expectations after market rallies and low expectations after declines. This can lead to bad decisions, like abandoning their long-term investment plans.

The presentation argued that human advisers provide important emotional value by building trust and personalised relationships, but technology can handle many routine tasks efficiently. Surveys show investors want humans for emotional support but are fine with technology handling tasks such as portfolio construction, reporting and account monitoring. The best model may involve a spectrum of tech and human support tailored to each client's needs and life stage.

Overall, the session examined the complex balance between tech efficiency and human relationships in delivering high-quality financial advice to various investor types.

Key takeaways:

  • Research emotional biases like present bias and loss aversion that lead investors astray
  • Review Vanguard's investor expectations surveys over time for insights on return expectations
  • Consider segmenting clients by their need for human interaction vs. digital services
  • Identify routine tasks that could be handled digitally to free up adviser time
  • Discuss with clients the appropriate tech vs. human advice balance for their situation
  • Develop frameworks for providing both robo-advice and human adviser services

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