AI-Powered Robo-Advisory Platforms & Ethics

With digital wealth management on the rise, AI driven robo advisors are transforming how portfolios are built, rebalanced, and managed. This course equips participants with the technical, regulatory, and ethical dimensions of AI powered investment platforms. From automated risk profiling to behavioral finance integration and algorithmic transparency, the program merges cutting edge technology with responsible advisory practices.

TRAINING TOPICS

• Architecture and components of modern robo advisory platforms
• AI techniques in portfolio recommendation engines
• Risk profiling using machine learning and behavioral cues
• Automated rebalancing and tax loss harvesting algorithms
• Chatbots and conversational AI for client interaction
• ESG integration and personalization in robo advisory
• Regulatory frameworks and compliance requirements (EU, SEC, etc.)
• Ethical AI in finance: transparency, bias, and client consent
• Explainability and model governance in AI investment tools
• Use of large language models (LLMs) in client communication

BY THE END OF THIS TRAINING COURSE, DELEGATES WILL BE ABLE TO:

• Design the architecture of an AI enabled robo advisory system
• Apply ML algorithms to assess client risk tolerance and goals
• Develop rebalancing models using AI based optimization
• Integrate ethical and regulatory principles into automated advice
• Evaluate model explainability and auditability in real time platforms
• Utilize NLP tools to improve digital client interactions
• Ensure responsible AI deployment in digital investment platforms
• Understand global compliance requirements for robo advisory services

TRAINING IS TAILORED TO

• Wealth management professionals and fintech innovators
• Investment advisors transitioning to digital platforms
• Financial analysts and product developers
• AI engineers and data scientists in financial services
• Compliance, legal, and ethics officers in wealth tech firms

TRAINING METHODOLOGY

• Case studies of global robo advisory platforms
• Technical hands on labs and simulations using Python & AI tools
• Ethical dilemma role plays and group discussions
• Real time analysis of chatbot responses and LLMs
• Scenario based exercises for regulatory alignment
• Interactive model building with AI based client profiling tools

DAY ONE:

FOUNDATIONS OF AI IN ROBO ADVISORY SYSTEMS

• Introduction to robo advisory platforms: evolution and business models
• Key components: onboarding, profiling, portfolio construction
• Role of AI and automation in advisory pipelines
• Data sources and AI pipelines in client onboarding
• Case review: Betterment, Wealthfront, and global players
• Lab: Simulate onboarding workflow with dummy client data

DAY TWO:

AI DRIVEN CLIENT PROFILING & PERSONALIZATION

• ML for investor risk profiling (decision trees, clustering)
• Behavioral finance patterns and psychometric data use
• Personalization algorithms for portfolio strategies
• NLP for extracting preferences from chat/voice inputs
• Lab: Building a client risk scoring model in Python
• Case: AI bias in profiling – risk vs responsibility

DAY THREE:

AUTOMATION OF PORTFOLIO MANAGEMENT

• AI for rebalancing, optimization, and tax efficiency
• Reinforcement learning for continuous portfolio adjustment
• ESG filters and user defined portfolio constraints
• Multi objective optimization using AI tools
• Lab: Automate a rebalancing strategy using historical data
• Case: Comparative rebalancing methods across platforms

DAY FOUR:

ETHICS, EXPLAINABILITY & MODEL GOVERNANCE

• Ethical frameworks in robo advisory services
• AI explainability tools: SHAP, LIME, and model transparency
• Consent and accountability in automated recommendations
• AI governance: auditing, risk reporting, and fairness
• Group discussion: Cross border regulatory dilemmas
• Simulation: Designing an ethically compliant AI investment journey

DAY FIVE:

NLP, CHATBOTS & AI ENABLED CLIENT COMMUNICATION

• Conversational AI and robo advisor front end design
• Role of LLMs (e.g., ChatGPT) in advisory dialogue
• Compliance and record keeping in AI assisted advice
• Multilingual support, accessibility, and trust building
• Lab: Develop a basic chatbot for investment FAQs
• Capstone: Present a prototype of a compliant, ethical robo advisory solution