Week 12

Question 1

What are the Limitations of Traditional Financial Advisors

Answer 1

○ High fees and conflicts of interest
○ Transmission of human biases (e.g., overtrading, lack of diversification)
○ Inadequate tailoring of advice beyond generating “peace of mind”

Question 2

What are Robo-advisors? How does it work? and what are the key advantages?

Answer 2

Robo-advisor: is a digital platform that uses algorithms to provide automated financial advice or portfolio management
* How it Works:
○ Collects user data (e.g., age, income, goals, risk tolerance)
○ Builds a personalized investment plan
○ Automatically manages the portfolio
* Key Advantages:
a. Cost-effective – lower fees due to automation
b. Accessible – low or no minimum investment required
c. Emotion-free advice – helps reduce behavioral biases
Transparent – easy to audit, monitor, and update

Question 3

What are the 4 dimensions of robo-advisors

Answer 3

1. Personalization
   ○ How tailored is the advice?
   ○ Ranges from basic models to highly customized plans using multiple user-specific factors.
2. Involvement
   ○ How much control does the user have?
   ○ Some platforms are fully automated, others allow active user participation in decisions.
3. Discretion
   ○ Can users override recommendations?
   ○ Some allow portfolio tweaks; others follow algorithmic outputs strictly.
4. Human Interaction
   ○ Is the service fully digital or a hybrid model?
   Hybrid models include access to human advisors alongside automated systems.

Question 4

What is the main goal of Robo-advisors ? What problems do they address? And how do they help?

Answer 4

Main Goal of Robo-advisors
Improve investment behavior and reduce common mistakes.
* Problems Addressed:
○ Poor diversification
○ Home bias (favoring domestic investments)
○ Trend-chasing
○ Disposition effect (selling winners too early, holding losers too long)
* How They Help:
○ Use finance theory (e.g., mean-variance optimization) to build diversified portfolios
○ Reduce risk and concentrated positions
○ Provide discipline and structure for new or anxious investors

Question 5

What are the two types of Robo-Advisors?

Answer 5

○ Passive/Retirement-focused robo-advisors
§ Long-term
§ Focus on low-cost ETFs
§ Evolve asset allocation over time

○ Trading-focused robo-advisors
§ Short-term
§ Serve active users
§ Offer real-time suggestions and efficient rebalancing tools

Question 6

What are the 4 challenges with robo-advisors ?

Answer 6

1. Holistic Robo-Advising

Need for robo-advisors that support entire financial life cycles (e.g., mortgages to retirement)
More research needed to find which investor traits matter most for personalized advice

2. Algorithmic Aversion & Hybrid Models

Some investors, especially older clients, distrust robo-advice
Hybrid models (humans + algorithms) may improve trust and provide education

3. Democratization vs. Inequality

Robo-advisors offer low-cost access to financial guidance for the middle class
But high-end personalized advice may still only be available to the wealthy, possibly widening inequality

4. Systemic Implications

If everyone follows similar algorithm-based advice, portfolios may become too similar
This homogenization could lead to greater systemic risk, especially during market shocks

5. Ethical and Legal Standards

Need to define fiduciary duties in a world of algorithm-driven advice
Must address issues like:

• Data privacy
• Algorithm bias
• Cybersecurity
• How regulators can interpret the “language” of complex financial algorithms

Question 7

What are some opportunities with this ai?

Answer 7

• Enhanced Efficiency & Personalization:
  ○ AI can process large volumes of data to deliver personalized, efficient, and scalable financial advice
  ○ Possibility to democratize access to high-quality advice previously available only to the wealthy
• Automation Benefits:
  ○ Streamlines processes such as investment management, tax filing, and college tuition planning
  Drives down costs and increases accessibility for everyday consumers

Question 8

What are some Ethical Challenges and Risks with this ai?

Answer 8

1. Bias in AI Systems

AI may generalize too much, ignoring personal needs
Example: Recommending 529 plans for all children—even those with special needs
Broader risk: AI trained on limited or biased data may misidentify or misadvise certain groups
E.g., facial recognition errors due to non-diverse training sets

2. Credit Scoring Concerns

AI credit models are 5–10% less accurate for lower-income or minority borrowers
Why? Because the data used is often biased or incomplete
Reflects systemic problems like the racial wealth gap

3. Data Homogeneity & Representation

Financial data often reflects wealthy, White families
Using this skewed data can unintentionally reinforce existing inequalities
Urgent need for diverse, inclusive datasets to ensure fair and personalized recommendations

Question 9

what are some liability issues?

Answer 9

• Liability Issues:
  ○ If AI recommendations lead to suboptimal or harmful financial decisions, the question of liability is complex
  ○ Financial advisors and institutions may risk breaching fiduciary duties if due diligence in AI oversight is neglected
• Importance of Due Diligence:
  ○ Advisers must continue rigorous evaluation of AI outputs, ensuring decisions are in clients’ best interests

Question 10

What are some recommendations for this ai?

Answer 10

Recommendations for Ethical AI:

• Diversify training datasets;
• Develop explainable, transparent models;
• Ongoing technical oversight;
• Regulatory certification and standards for AI;
• Ethical frameworks tailored to financial AI;
• Collaborative effort (technologists + ethicists + financial professionals)