Robo-Advisory Investment Management Course

Name: Robo-Advisory and Automated Investment Management Training Course
Availability: InStock

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 €

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Robo-Advisory and Automated Investment Management Training Course

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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

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Showing 41-60 of 74 events

Location	Dates	Duration	Mode	Price
Rome	Week 20, 2027 17 – 21 May 2027	5 Days	Onsite	€5,700
Athens	Week 20, 2027 17 – 21 May 2027	5 Days	Onsite	€6,700
Istanbul	Week 21, 2027 24 – 28 May 2027	5 Days	Onsite	€4,500
Amsterdam	Week 22, 2027 31 May – 4 June 2027	5 Days	Onsite	€5,700
New York	Week 22, 2027 31 May – 4 June 2027	5 Days	Onsite	€12,000
Bangkok	Week 23, 2027 13 – 17 June 2027	5 Days	Onsite	€6,000
Chicago	Week 23, 2027 13 – 17 June 2027	5 Days	Onsite	€12,000
Tbilisi	Week 25, 2027 21 – 25 June 2027	5 Days	Onsite	€5,000
Abu Dhabi	Week 25, 2027 21 – 25 June 2027	5 Days	Onsite	€4,700
Toronto	Week 25, 2027 27 June – 1 July 2027	5 Days	Onsite	€12,000
Paris	Week 26, 2027 28 June – 2 July 2027	5 Days	Onsite	€5,700
Cairo	Week 27, 2027 5 – 9 July 2027	5 Days	Onsite	€4,100
Milan	Week 28, 2027 12 – 16 July 2027	5 Days	Onsite	€5,700
London	Week 29, 2027 19 – 23 July 2027	5 Days	Onsite	€5,700
Rome	Week 30, 2027 26 – 30 July 2027	5 Days	Onsite	€5,700
Dubai	Week 31, 2027 2 – 6 August 2027	5 Days	Onsite	€4,500
Nairobi	Week 31, 2027 8 – 12 August 2027	5 Days	Onsite	€4,500
Munich	Week 32, 2027 9 – 13 August 2027	5 Days	Onsite	€5,700
Zanzibar	Week 32, 2027 15 – 19 August 2027	5 Days	Onsite	€5,500
Baku	Week 33, 2027 16 – 20 August 2027	5 Days	Onsite	€5,000

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.

Robo-Advisory Investment Management Course