Robo-Advisory Investment Management Course

Design automated investment services with controlled portfolios, traceable algorithms, suitable client journeys, and human oversight.
Robo-Advisory Investment Management Course

At a glance

Duration
5 days
Format
Classroom
Cities
Kuala Lumpur, Singapore, Phuket, Accra, Trabzon, Manama and more
Next session
12 – 16 October 2026, Kuala Lumpur
Average fee
5,800 €

Overview

Robo-Advisory and Automated Investment Management Training Course is a five-day professional course for digital wealth, portfolio, fintech, risk, data, and product teams who leave with an Automated Investment Service Design and Governance Plan. Participants connect client profiling, goal-based portfolios, allocation, rebalancing, algorithms, disclosures, resilience, oversight, and performance monitoring. The course replaces disconnected digital features with a controlled service model. Agile Leaders Training Center addresses robo-advisory through client outcomes, investment logic, and operational governance.

Who Should Attend

  • Digital wealth teams responsible for online advice propositions and client journeys
  • Investment product functions responsible for model portfolios, allocation, and rebalancing
  • Fintech and technology teams responsible for automated service design and integration
  • Risk and compliance functions responsible for suitability, disclosure, conflicts, and supervision
  • Data and model teams responsible for algorithms, inputs, testing, and monitoring
  • Leaders responsible for selecting vendors or governing automated investment services

The course assumes participants already work with investment products, digital financial services, data, risk, or governance and leaves out personal investment advice and external certification preparation.

Departments and Industries

The course supports departments and industries that design, operate, procure, or oversee automated investment services.

  • Wealth management, private banking, asset management, and investment-advisory teams
  • Fintech, digital banking, brokerage, retirement, and savings platforms
  • Investment product, portfolio construction, research, and trading functions
  • Technology, data science, model risk, cybersecurity, and architecture departments
  • Compliance, legal, conduct, operational risk, and internal-audit teams
  • Customer experience, operations, vendor management, and transformation functions

Learning Objectives

By the end of this course, participants will be able to:

  • Analyze robo-advisory service models, clients, goals, and delivery boundaries
  • Build profiling, suitability, allocation, portfolio, and rebalancing logic
  • Evaluate algorithms, data, fees, conflicts, disclosures, and client outcomes
  • Design model governance, testing, human escalation, and vendor controls
  • Apply resilience, cybersecurity, monitoring, and incident-response arrangements
  • Produce an Automated Investment Service Design and Governance Plan

Course Agenda

Day 1: Client Proposition and Advice Journey

  • Robo-Advisory Service Model Canvas
  • Target Client and Use-Case Profile
  • Goal, Horizon and Constraint Framework
  • Risk Capacity and Risk-Tolerance Questionnaire
  • Digital Advice Journey and Human-Escalation Map

Day 2: Portfolio Automation and Investment Logic

  • Strategic Asset-Allocation Policy
  • Model Portfolio Construction Rules
  • Product Universe and Selection Criteria
  • Portfolio Rebalancing and Drift Controls
  • Tax-Aware and Transaction-Cost Decision Rules

Day 3: Algorithms, Data and Model Governance

  • Algorithm Decision-Logic Inventory
  • Data Lineage and Quality-Control Register
  • Model Validation and Outcome-Test Plan
  • Bias, Limitation and Exception Assessment
  • Change Approval and Version-Control Process

Day 4: Client Protection and Operational Control

  • Suitability and Client-Outcome Control Matrix
  • Fee, Conflict and Disclosure Review
  • Cybersecurity and Data-Protection Control Map
  • Operational Resilience and Service-Continuity Plan
  • Vendor Due-Diligence and Oversight Scorecard

Day 5: Service Monitoring and Governance Practice

  • Suggested Exercise: Test a Client Profiling Journey
  • Suggested Exercise: Review Allocation and Rebalancing Rules
  • Suggested Exercise: Challenge an Algorithm Control Pack
  • Suggested Exercise: Design Monitoring and Escalation Triggers
  • Capstone Exercise: Automated Investment Service Design and Governance Plan

Practical Exercises

Suggested activities connect the investment engine, digital client journey, model controls, and operational governance.

  • Suggested activity: define target clients, goals, exclusions, profiling questions, risk measures, suitability logic, disclosures, and routes to human assistance.
  • Suggested activity: construct a model-portfolio policy covering asset allocation, product eligibility, drift thresholds, rebalancing, transaction costs, tax-aware considerations, and exceptions.
  • Suggested activity: challenge data lineage, algorithm rules, validation evidence, bias risks, change controls, cybersecurity, resilience, and third-party dependencies.
  • Suggested activity: assemble service ownership, client-outcome measures, portfolio monitoring, incident triggers, vendor review, reporting, escalation, and improvement actions in the capstone plan.

FAQs

What is robo-advisory and automated investment management?

Robo-advisory uses digital journeys and algorithmic rules to collect client information, develop or deliver investment recommendations, and sometimes manage portfolios. Automated investment management can include allocation, portfolio selection, execution, monitoring, rebalancing, and related controls with defined human oversight.

Who is the robo-advisory training course for, and what does it assume?

The course suits digital wealth, investment product, portfolio, fintech, data, risk, compliance, and operational leaders. It assumes practical exposure to investments, digital financial services, analytics, or governance but does not require participants to build production software.

How does robo-advisory differ from an algorithmic trading course?

Robo-advisory centers on client profiling, goals, portfolio recommendations, ongoing management, disclosures, and service governance. Algorithmic trading courses typically focus on market signals, order execution, trading strategies, and market microstructure rather than a client advice relationship.

How should a robo-advisor assess client suitability?

A robo-advisor should collect relevant goals, horizon, circumstances, constraints, knowledge, risk tolerance, and risk capacity through clear questions, test inconsistent answers, explain limitations, preserve evidence, refresh material information, and route cases outside the automated boundary to suitable human review.

How is an automated investment algorithm governed?

Governance defines ownership, intended use, data, decision rules, validation, limitations, outcome tests, approvals, version control, access, monitoring, exceptions, incidents, change triggers, and retirement. Human reviewers should be able to trace decisions and intervene when thresholds or service boundaries are breached.

Conclusion

Participants leave with an Automated Investment Service Design and Governance Plan covering target clients, profiling, investment logic, models, data, disclosures, controls, vendors, resilience, monitoring, and escalation. The plan turns a digital investment concept into a traceable operating model. It supports accountable decisions across product, investment, technology, risk, and operations.

credits: 5 credit per day

Course Mode: full-time

Provider: Agile Leaders Training Center

Showing 1-20 of 74 events
Image Location Dates Duration Mode Price Actions
Kuala Lumpur Kuala Lumpur Week 42, 2026
12 – 16 October 2026
5 Days Onsite €5,200
Singapore Singapore Week 42, 2026
12 – 16 October 2026
5 Days Onsite €5,700
Phuket Phuket Week 42, 2026
18 – 22 October 2026
5 Days Onsite €6,000
Accra Accra Week 43, 2026
25 – 29 October 2026
5 Days Onsite €4,100
Trabzon Trabzon Week 43, 2026
25 – 29 October 2026
5 Days Onsite €6,800
Manama Manama Week 44, 2026
1 – 5 November 2026
5 Days Onsite €4,700
Madrid Madrid Week 46, 2026
9 – 13 November 2026
5 Days Onsite €5,700
Porto Porto Week 46, 2026
9 – 13 November 2026
5 Days Onsite €5,700
Bali Bali Week 46, 2026
15 – 19 November 2026
5 Days Onsite €5,700
Vienna Vienna Week 47, 2026
16 – 20 November 2026
5 Days Onsite €5,700
Amsterdam Amsterdam Week 48, 2026
23 – 27 November 2026
5 Days Onsite €5,700
Tashkent Tashkent Week 48, 2026
29 November – 3 December 2026
5 Days Onsite €4,500
London London Week 49, 2026
30 November – 4 December 2026
5 Days Onsite €5,700
Amman Amman Week 49, 2026
6 – 10 December 2026
5 Days Onsite €4,100
Cape town Cape town Week 50, 2026
13 – 17 December 2026
5 Days Onsite €4,500
Kuala Lumpur Kuala Lumpur Week 51, 2026
14 – 18 December 2026
5 Days Onsite €5,200
Dubai Dubai Week 52, 2026
21 – 25 December 2026
5 Days Onsite €4,500
Abu Dhabi Abu Dhabi Week 52, 2026
21 – 25 December 2026
5 Days Onsite €4,700
Jakarta Jakarta Week 53, 2026
28 December 2026 – 1 January 2027
5 Days Onsite €5,700
Casablanca Casablanca Week 01, 2027
4 – 8 January 2027
5 Days Onsite €4,100

Frequently asked questions

What does this course cover?

OverviewRobo-Advisory and Automated Investment Management Training Course is a five-day professional course for digital wealth, portfolio, fintech, risk, data, and product teams who leave with an Automated Investment Service Design and Governance Plan. Participants connect client profiling, goal-based portfolios, allocation, rebalancing, algorithms, discl…

Are training dates available?

Yes. Available dates and destinations are listed in the course dates section on this page.

How can I register?

Choose an available date on this page and complete the registration form, or send a programme enquiry.

Can I download the course brochure?

Yes. Use the brochure download link provided on this page.

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