15 Topics
10 Days
61 Sessions
Programme Overview
Training Description
Who Should Attend
- Pension and retirement investment professionals
- Fintech and digital transformation professionals
- Financial analysts
- Risk and compliance professionals
- Product development and innovation teams
- Private banking professionals
- Relationship managers
- Senior executives in financial institutions
- Professionals interested in digital wealth management
Session Objectives
- Understand the principles and benefits of robo-advisory and automated investing.
- Implement techniques for evaluating robo-advisory platforms and technologies.
- Understand the principles of risk management and portfolio optimization in robo-advisory.
- Implement techniques for enhancing client engagement and personalization in automated investing.
- Understand the role of data analytics and machine learning in improving robo-advisory performance.
- Understand the challenges and opportunities of integrating robo-advisory with traditional wealth management services.
- Develop strategies for implementing and scaling up robo-advisory solutions.
About the Course
Robo-Advisory & Automated Investing: Revolutionizing Wealth Management is a specialized training course designed to equip wealth management, investment, banking, and financial-services professionals with practical knowledge of automated investment advisory and digital wealth-management technologies. The course examines how robo-advisors use algorithms, investor data, portfolio models, automation, and artificial intelligence to deliver scalable and personalized investment services.Participants will explore automated client onboarding, risk profiling, portfolio construction, asset allocation, rebalancing, investment monitoring, digital client engagement, risk management, cybersecurity, governance, and regulatory considerations. The course also examines how traditional wealth managers can integrate automation while preserving appropriate human oversight and client trust.
Curriculum & Topics
15 Topics | 61 Sessions
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Workshop 1.1:
• Principles and benefits of automated wealth management.
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Workshop 1.2:
• Understanding the evolution of robo-advisory platforms.
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Workshop 1.3:
• Benefits of cost-efficiency, accessibility, and personalization.
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Workshop 1.4:
• Historical context and emerging trends in automated investing.
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Workshop 2.1:
• Techniques for evaluating robo-advisory platforms and algorithms.
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Workshop 2.2:
• Implementing performance analysis and risk assessments.
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Workshop 2.3:
• Utilizing platform feature and user experience evaluations.
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Workshop 2.4:
• Managing platform selection and integration strategies.
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Workshop 3.1:
• Understanding the role of algorithms in portfolio construction and rebalancing.
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Workshop 3.2:
• Implementing AI-driven investment strategies and models.
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Workshop 3.3:
• Utilizing machine learning for market analysis and forecasting.
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Workshop 3.4:
• Managing algorithm performance and validation.
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Workshop 4.1:
• Techniques for developing and managing automated investment strategies.
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Workshop 4.2:
• Implementing portfolio optimization and asset allocation models.
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Workshop 4.3:
• Utilizing algorithmic trading and quantitative analysis.
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Workshop 4.4:
• Managing strategy testing and deployment.
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Workshop 5.1:
• Understanding the principles of risk management in automated investing.
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Workshop 5.2:
• Implementing portfolio diversification and risk-adjusted returns.
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Workshop 5.3:
• Utilizing risk tolerance assessments and modeling.
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Workshop 5.4:
• Managing portfolio volatility and drawdown.
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Workshop 6.1:
• Techniques for developing and validating risk-adjusted investment models.
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Workshop 6.2:
• Implementing stress testing and scenario analysis.
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Workshop 6.3:
• Utilizing risk modeling and simulation tools.
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Workshop 6.4:
• Managing model calibration and performance monitoring.
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Workshop 7.1:
• Understanding the role of digital onboarding in robo-advisory.
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Workshop 7.2:
• Implementing customer journey mapping and optimization.
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Workshop 7.3:
• Implementing customer journey mapping and optimization.
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Workshop 7.4:
• Utilizing client communication and engagement strategies.
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Workshop 7.5:
• Managing client data privacy and security.
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Workshop 8.1:
• Techniques for enhancing client engagement and personalization.
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Workshop 8.2:
• Implementing personalized portfolio recommendations and insights.
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Workshop 8.3:
• Utilizing client feedback and data analytics.
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Workshop 8.4:
• Managing client relationship management (CRM) systems.
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Workshop 9.1:
• Understanding regulatory frameworks for robo-advisory and automated trading.
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Workshop 9.2:
• Implementing compliance with investment regulations and guidelines.
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Workshop 9.3:
• Utilizing regulatory sandboxes and pilot programs.
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Workshop 9.4:
• Managing legal and regulatory compliance.
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Workshop 10.1:
• Techniques for ensuring regulatory compliance in automated investment platforms.
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Workshop 10.2:
• Implementing risk management and compliance controls.
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Workshop 10.3:
• Utilizing regulatory technology (RegTech) solutions.
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Workshop 10.4:
• Managing regulatory audits and reporting.
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Workshop 11.1:
• Understanding the role of data analytics in robo-advisory performance.
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Workshop 11.2:
• Implementing machine learning for portfolio optimization and forecasting.
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Workshop 11.3:
• Utilizing data visualization and reporting tools.
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Workshop 11.4:
• Managing model performance monitoring and improvement.
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Workshop 12.1:
• Understanding legacy system integration challenges.
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Workshop 12.2:
• Implementing API integration and data exchange protocols.
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Workshop 12.3:
• Utilizing cloud-based robo-advisory platforms.
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Workshop 12.4:
• Managing change management and adoption.
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Workshop 13.1:
• Techniques for developing robo-advisory project roadmaps.
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Workshop 13.2:
• Implementing pilot project testing and evaluation.
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Workshop 13.3:
• Utilizing scalability and performance optimization techniques.
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Workshop 13.4:
• Managing robo-advisory team and governance.
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Workshop 14.1:
• Analyzing real-world examples of successful robo-advisory implementations.
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Workshop 14.2:
• Highlighting best practices and innovative solutions.
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Workshop 14.3:
• Documenting project outcomes and impact.
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Workshop 14.4:
• Industry and technology leader testimonials.
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Workshop 15.1:
• Exploring emerging technologies and trends in automated wealth management.
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Workshop 15.2:
• Integrating AI and machine learning for advanced personalization
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Workshop 15.3:
• Adapting to evolving regulatory landscapes and market demands.
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Workshop 15.4:
• Building resilient and innovative robo-advisory ecosystems.
