Robo-Advice Strategy Training Course: Suitability, Portfolios and Oversight

Programme Summary

Robo-advice strategy is the subject of this one-week training course for heads of wealth, asset management, digital product and risk, ending in an oversight pack for one automated advice service. Automated advice now reaches clients who never meet an adviser, yet reviews have found weak suitability questions, unclear disclosure and thin oversight of the algorithms. The programme moves from client profiling to model portfolios, rebalancing rules, algorithm controls and service oversight, using prepared client and portfolio records. Mars Training Centre UK delivers this programme on robo-advice strategy to mixed-organisation cohorts.

The Business Case

Banks, wealth managers and platforms are asked whether to build automated advice, buy it or partner, and how to prove it treats clients fairly. Leaders who can test a questionnaire, read a portfolio rule and demand evidence from the algorithm can widen access to advice while holding conduct and operational risk in check.

• Suitability Failures: Fall when profiling questions, limits and overrides are tested against realistic client cases.
• Service Cost: Is controlled when rebalancing, fees and servicing rules are set with the volume of clients in view.
• Conduct and Model Risk: Is contained when ownership, testing and escalation of the algorithm are agreed before launch.

Principles and Evidence Base

• IOSCO suitability principles for intermediaries: Applied in Sessions 1 and 5 to judge whether profiling and advice outcomes fit each client.
• Modern portfolio theory: Applied in Sessions 2 and 3 to read how risk, return and diversification shape model portfolios.
• ISO 31000 risk management guidelines: Applied in Session 4 to rate conduct, model and operational risks of the service.
• ISO/IEC 42001 AI management system standard: Applied in Session 4 to set ownership and testing of the advice algorithm.

Intended Participants

• Wealth and asset management leaders who decide whether and how to offer automated advice.
• Digital product owners who design the client journey, questionnaire and fee model.
• Risk and compliance leaders who supervise suitability, disclosure and complaints.
• Investment and technology leads who maintain model portfolios and the algorithm behind them.

Typical settings include retail banking, wealth management, pension providers and asset management platforms.

Learning Outcomes

1. Participants will be able to evaluate profiling questionnaires for suitability gaps and unclear client disclosure.
2. Participants will be able to compare model portfolio designs by risk, diversification and cost.
3. Participants will be able to construct rebalancing and fee rules for a defined client base.
4. Participants will be able to diagnose weaknesses in algorithm testing, ownership and escalation.
5. Participants will be able to prioritise build, buy and partner options by control and cost.
6. Participants will be able to justify an oversight pack for an automated advice service to a risk committee.

Programme Structure

Day 1: Robo-Advice Strategy and Client Profiling

How does an automated service learn what each client needs?

• Automated Advice Service Map
• Client Segment Profile
• Risk Questionnaire Review
• Capacity for Loss Test
• IOSCO Suitability Principles Reading

Day 2: Model Portfolios and Diversification

How are risk and return turned into portfolios clients can hold?

• Modern Portfolio Theory Primer
• Asset Allocation Table
• Index and Fund Selection Screen
• Portfolio Cost Comparison
• Client-to-Portfolio Matching Rules

Day 3: Rebalancing, Fees and Service Design

Which rules keep portfolios on target at a workable cost?

• Drift and Threshold Rule Set
• Rebalancing Trade Cost Model
• Fee Structure Comparison
• Hybrid Adviser Handover Design
• Client Communication Standards

Day 4: Algorithm Controls and Conduct Risk

Who is accountable when the algorithm advises badly?

• Algorithm Test Plan
• ISO 31000 Conduct Risk Rating
• ISO/IEC 42001 Ownership Review
• Complaint and Escalation Log
• Outage and Resilience Check

Day 5: Oversight Pack for One Automated Advice Service

Do the findings join into a pack a risk committee can approve?

• Applying the Session 1 Questionnaire Review
• Testing the Session 2 Matching Rules
• Checking the Session 3 Rebalancing Rule Set
• Reviewing the Session 4 Test Plan
• Completing the Oversight Pack

Methodology

The programme is a case analysis built on prepared client records, portfolio data and service reviews from a retail bank and an asset management platform. Participants answer the questionnaire as sample clients, test portfolio rules and probe the algorithm in small groups, then defend their oversight pack to peers acting as a risk committee.

• Suggested activity: Completing a risk questionnaire as three client types and comparing the advice produced.
• Suggested activity: Setting drift thresholds and costing the resulting trades.
• Suggested activity: Reviewing a prepared algorithm test report and agreeing escalation steps.

Capstone Output

Each participant completes an oversight pack for one automated advice service. It holds a questionnaire review, a portfolio matching rule set, rebalancing and fee rules, an algorithm test plan and an escalation protocol. At work it goes to the risk committee for approval and becomes the routine for reviewing the service after launch.

Frequently Asked Questions

Is robo-advice strategy training suitable for leaders who are not investment specialists?

Yes. Robo-advice strategy is taught through prepared client cases and templates. You need responsibility for advice, product, risk or technology decisions, but no portfolio management or programming background.

Which standards does robo-advice strategy rest on in this programme?

Robo-advice strategy here rests on IOSCO suitability principles, modern portfolio theory, the ISO 31000 risk management guidelines and the ISO/IEC 42001 AI management system standard, each applied to a profiling, portfolio or control decision.

How is the oversight pack from robo-advice strategy training used at work?

You take the oversight pack to your risk committee, use its questionnaire review to correct suitability gaps, and keep its test plan and escalation protocol as the routine for later reviews.

How does robo-advice strategy differ from a programme on traditional wealth management?

Robo-advice strategy concentrates on designing and supervising automated, rule-based advice at scale, while a traditional wealth management programme concentrates on personal adviser relationships and bespoke client planning.

• Course Mode full-time
• Provider Mars Training Centre UK