What is Risk Profiling?

Gauging risk limits for comfortable lifetime clients

Risk profiling is the process of assessing what level of risk your clients can mentally and financially handle. Accurate assessment means relaxed and happy clients.

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  • Profiling Steps

  • Step 1

    Administer surveys

  • Step 2

    Assess risk profile

  • Step 3

    Recommend suitable investments

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riskTRACK™ Methodology

We analysed the competition to find the best questions

The riskTRACK™ methodology was built to take the best elements of existing surveys, purify them, and then exploit them to generate highly reliable risk scores.

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What is a Risk Profile?

A person's risk profile is the combination of many individual risk factors, which in sum shape their risk taking behaviour. We call psychological factors the person's "willingness" to take risk and practical factors their "ability"


  • Risk profile is the overlap of willingness & ability

Why assess your client's risk profile?
Correctly assessing their risk profile will minimise panic during inevitable downturns and reduce blame placed for unexpected losses.

How to Use riskAPP

Once you join, the process of adding clients and generating risk profiles happens like this

  • Add Clients

  • Bulk upload

    Simply copy and paste client details from a spreadsheet

    Pre-existing clients

    Adding all your clients to Stackup is simple. Just copy from a spreadsheet and paste into our upload tool, and we will do the rest.

  • Add as you go

    Add new clients by manual entry or API

    New clients

    Each time you onboard a client, you can simply add them to Stackup through our dashboard or your system can interact with our API so they are added automatically.

  • Administer Surveys

  • Send by email

    Delivered straight to their inbox

    Convenience and flexibility

    Send a personalised link and allow clients to complete surveys when it suits them on their desktop, smartphone or tablet. Save time and know their preferences before they walk through your door.

  • Fill in person

    Completed in your office

    Timed with consultations

    Chat with your clients before they progress to risk tolerance scores, and allow them to fill out the questionnaire in person in your office.

  • Assess Client's Risk Profile

  • Retrieve scores

    We generate a Stackup Risk score

    See how they're placed

    Based on your client's responses, we place them into one of 5 bands for willingness, and seperately, ability, to take risk.

  • Discuss discrepancies

    Stackup identifies mismatches between questions

    Sometimes things dont quite stack up

    We aren't always consistent in how we respond. Stackup highlights answers that may need clarification and gives you the opportunity to resolve these together via discussion.

  • Finalise Their Score

  • Sign off

    Ask your client's to confirm their score

    Shared decisions lower liability

    Once you have discussed your client's risk profile with them and resolved any questions, we ask them to sign the report to attest that we have accurately captured their risk profile.

  • Generate a report

    Find out what you need to know

    Their risk profile and personality defined

    Based on our validated methodology and extensive research in psychology and behavioral finance, we build a profile of your client and package it into a report, ready for them to view and for you to reference.

Methodology

Robust Risk Profiles.

Stackup Risk Scores (SRS) are the product of hundreds of hours of finance and psychology research, integrated with the best elements of current industry practice. We've leveraged on this to generate risk scores that provide highly reliable estimates of risk tolerance. Here's what we did:

  •   1   Theoretical Model

    We started by identifying a theoretical model that, as holistically as possible, describes risk tolerance.

    The literature is broad and diverse, however Cordell (2001) provides a solid framework for defining risk tolerance. Risk tolerance is defined as the maximum amount of uncertainty someone is willing to accept when making a financial decision, and is influence by a range of highly individual psychological and contextual factors, such as a client’s attitude and propensity to take financial risks, along with their financial literacy and capacity for loss. Cordell’s (2001) model encompasses each of these components, so we used it as the starting point for our risk score.

  •   2   Question Generation

    From the theoretical model, we progressed to developing questions that would measure each relevant factor of a comprehensive risk profile.

    We began by collating a database of questions, which were reflective of common industry practice. Our goal was to compile a comprehensive list of questions with subtle differences that would elicit nuanced individual responses. From this large database, we analysed each question in consultation with our psychology and finance team to filter out questions that had in-built bias or readability issues. We were left with a set of 115 questions that were considered valid.

  •   3   Survey Purification

    Our next task was to determine which questions from our large sample were best at eliciting relevant risk profile preferences from our respondents.

    To do this, we had hundreds of people who were representative of the population as a whole complete the full 115 question set. Their responses provided the data on which our next analyses were performed. Through a statistical method called factor analysis, we grouped questions with strong correlations together. These question groups mapped onto the factors that we set out to assess, as per our initial theoretical model. We discarded other questions that showed too much divergence or overlap. We were able to purify our question list down to a more manageable set, while retaining enough breadth of focus for a comprehensive questionnaire. We now had a set of 25 questions.

  •   4   Robustness Checking

    With our survey length more manageable, we next validated our chosen questions statistically for their ability to measure risk behaviours.

    Our end goal was to develop a survey that could place clients in appropriate investments for them. Thus, the survey’s ability to predict which investments would make each client feel comfortable throughout the cycle was key. Our analysis into validity via a stepwise regression found that our questionnaire was indeed good at explaining people's allocation to risk assets. Our reliability analysis with a statistical test called Cronbach's alpha showed that the questions within each factor group were highly internally consistent and thus likely to be measuring the same thing. We now had a reliable, valid and comprehensive survey that was ready for industry practice.

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