Scenario-Based Investment Client Risk Profiling eLearning
I designed and developed a scenario-based microlearning experience that equips new financial advisors with the skills to assess client risk profiles and make suitable investment recommendations. Through guided instruction, visual decision frameworks, a Salesforce workflow walkthrough, and realistic client scenarios, learners practice balancing client goals, time horizons, risk tolerance, and risk capacity to improve client outcomes.
Overview
Audience
Responsibilities
Instructional Design, eLearning Development, Storyboarding, Graphic Design & Asset Sourcing, AI Video Production
Tools
Analysis
The fictitious wealth management firm Summit Wealth Advisory investigated why they lost a higher number of clients than expected in the last two fiscal quarters. Through audits, they discovered that some recommendations by advisors did not consistently align with clients’ goals, risk tolerance, or investment timelines.
Interviews with senior advisors and compliance leaders revealed that new advisors often focused on a client’s age or income while overlooking other critical factors such as emotional tolerance for losses and financial capacity to absorb risk.
A performance analysis determined that the issue stemmed from a skills gap rather than a knowledge gap.
As a result, I proposed a microlearning solution focused on developing risk profiling and decision-making skills through realistic client scenarios.
After further review of the performance analysis and consultation with the SME, I identified the key observable behaviors advisors must perform on the job rather than simply having them recall financial terminology.
Advisors should be able to:
- Identify factors influencing client risk profiles
- Differentiate between risk tolerance and risk capacity
- Evaluate client goals and time horizons
- Select appropriate investment recommendations
- Document recommendations accurately in Salesforce
Once stakeholders gave their approval, I moved into the design phase.
Design
Foundational Knowledge
The first step was to identify the key factors that financial advisors need to fully consider before making a recommendation.
Brainstorming with ChatGPT, I uncovered the core concepts, and I decided on presenting them through video for higher engagement:
- Investment goals
- Time horizon
- Risk tolerance
- Risk capacity
This approach aligns with Mayer’s Pre-Training Principle, providing foundational knowledge before learners apply it in scenarios.
Salesforce Workflow Support
Because advisors must document recommendations accurately within the firm’s CRM, I decided to incorporate instructions for how to create and update a custom investment recommendation field within Salesforce Accounts.
This performance-support component helps bridge the gap between learning and workplace execution.
Realistic Scenarios
To help the learners apply the core concepts, I came up with 4 different client scenarios where learners have to review profiles and make decisions accordingly.
This design reflects Bloom’s Taxonomy by moving learners from understanding concepts to analyzing client information and evaluating investment options.
I generated a logo with a style fitting for a corporate brand and used it to design the Rise 360 and the interactive simulation.
Development
Process
Following stakeholder approval of the storyboard and visual designs, I developed the learning experience using Rise 360, Synthesia, Notebook LM, and Scribe.
The goal was to create a concise, performance-focused learning experience that mirrored the decision-making process financial advisors use when assessing client risk profiles and recommending investments.
Throughout development, I focused on creating a clean, professional aesthetic that reflected the financial services industry while maintaining a high level of learner engagement.
Interactive elements were designed to reinforce decision-making rather than content recall, ensuring that learners practiced the same analytical skills they would use when working with actual clients.
Features
Interactive Labeled Graphic
The labeled graphic allows learners to investigate each risk profiling factor while maintaining a clear visual model of the overall decision-making process.
This design supports Cognitive Load Theory by chunking information into manageable sections and reducing unnecessary complexity.
Claude Vibe-Coded Simulation With 4 Client Scenarios
The core learning experience consists of four client personas representing different levels of risk tolerance, risk capacity, and investment goals.
Learners review client profiles and recommend investment strategies:
- Conservative
- Balanced
- Aggressive
The scenarios increase in complexity, culminating in a client whose financial capacity and emotional tolerance create conflicting signals.
Consequence-Based Feedback
Rather than simply identifying correct answers, each recommendation produces realistic outcomes showing how the client might react.
For example:
- Anxiety during market downturns
- Failure to meet financial goals
- Increased confidence and trust
This approach aligns with Michael Allen’s Seven Magic Keys to eLearning, emphasizing meaningful feedback and decision-making.
Scribe Step-by-Step Walkthrough of Salesforce Account Update
Implementation & Evaluation
To reinforce foundational knowledge before learners entered the scenario-based assessment, I included a matching activity in Rise 360 that required learners to correctly associate key concepts such as risk tolerance, risk capacity, time horizon, and investment goals with their definitions. This formative knowledge check serves as a Kirkpatrick Level 2 (Learning) evaluation by measuring whether learners have acquired the foundational knowledge needed to perform the task.
In the final simulation, learners received a personalized performance report summarizing their recommendations and decision-making. In a production environment, this report could be emailed automatically to managers, instructors, or compliance teams to support coaching and follow-up discussions. This reporting mechanism could contribute to Kirkpatrick Level 3 (Behavior) evaluation by helping organizations monitor whether learners are demonstrating sound decision-making and applying the risk profiling framework consistently.
Additionally, Salesforce could be configured with custom Account fields for each of the four risk profiling factors, along with recommendations—investment goals, time horizon, risk tolerance, and risk capacity—requiring advisors to document their assessment before recording a recommendation. This not only encourages deliberate analysis and consistent documentation practices but also generates data that can be used for compliance reviews, quality assurance, and performance dashboards. When combined with manager review of actual client recommendations, these fields could support both Kirkpatrick Level 3 (Behavior) evaluation by measuring workplace application and Level 4 (Results) evaluation by examining trends such as recommendation quality, client satisfaction, client retention, or reductions in unsuitable investment recommendations.
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