Methodology and Assumptions - Documentation and Communication

As of July 1, 2021, FP Canada introduced two rules of conduct to the Standards of Professional Responsibility related to the use of technology. These rules were updated again with the new standards coming into effect from June 1, 2024 onward. This article outlines resources available to Snap Projections clients to meet these requirements.

1

Rule 29

Rule 29: When selecting, relying on, recommending, or using technology in the financial planning process, a Certificant:

a) Must take reasonable proactive steps to gain a general understanding of the methodologies underlying the technology that have a direct impact on financial planning projections and recommendations;

b) Must have an understanding of the financial assumptions underlying the technology that have a direct impact on financial planning projections and recommendations;

c) Must validate that the inputs and assumptions used are reasonable and appropriate based on the client’s circumstances; and

d) Must validate that the outputs generated are reasonable and appropriate for the client before relying on them, or presenting the final recommendations or strategies to the client.

Snap Projections takes great care to document and share the methodologies and assumptions that underlie the software. We believe a thorough understanding of these inputs is important to ensure the outputs of the software are as intended for your needs.


We use current government-provided inputs where available (e.g., tax rates, CPP benefits) and use reasonable and customizable assumptions where required (e.g., inflation, portfolio holdings). Where possible, we use industry-recommended inputs (e.g., the FP Canada Projection Assumption Guidelines (PAG) for the rate of return assumptions).


Articles outlining our methodologies and assumptions can be found throughout our Help section of the website. Some of the most relevant sections and articles are included below:

Our data entry flow encourages the review and validation of many of these assumptions as the plan is initially being created.


2

Rule 30

Rule 30: In all cases, irrespective of the data used, the material assumptions used as well as the rationale must be documented, and clearly communicated to clients.

Snap Projections includes a dedicated page in the Report section for assumptions used in the projection. In addition to these values, advisors can add their own comments in this section for any other material details not captured in the default tables.


If assumptions are more appropriate in reference to specific figures (e.g., tables, charts) you can add comments to any section of the Report.


Assumptions currently included are listed below:

  • Start year
  • End year
  • Inflation rate
  • Province for tax purposes
  • Rate of return on financial assets
  • Rate of return on corporate assets
  • Appreciation rate on real assets
  • Debt interest rate
  • Retirement age
  • CPP start age
  • OAS start age
  • CPP % of maximum
  • OAS % of maximum

Other assumptions may be included depending on additional functionality added to the projection (e.g., education goal, insurance).


There is also the option to export the plan as an Excel file, which documents 100+ different assumptions/parameters used in the plan on the input parameters tab.

Here is an example of a portion of the Assumptions section of the Report.


3

Considerations for the use of AI in Financial Planning

Artificial intelligence is rapidly finding its way into financial planning practices, and tools like ChatGPT can be incredibly useful for drafting communications, summarizing information, brainstorming ideas, and automating repetitive tasks.

But should AI be used to actually create financial plans and generate client recommendations?

As stated earlier in this article, FP Canada’s Standards of Professional Responsibility place clear obligations on CFP® professionals to understand the methodologies, assumptions, inputs, and outputs behind the technology they use. When viewed through that lens, relying on a large language model (LLM) like ChatGPT to generate financial planning recommendations creates significant challenges for meeting those professional standards.

Generative AI is a valuable tool for many tasks, but it should not be relied upon to generate financial plans or client recommendations without appropriate oversight and validation. Generative AI can produce incomplete, inaccurate, or fabricated information and may not consistently produce the same results when given similar inputs. Responses can also vary depending on the prompt, the conversation history, the model being used, and updates to the underlying AI system.

When helping clients make important financial decisions, it's essential to rely on transparent calculation engines that have been extensively tested, validated, and designed specifically for financial planning; such as Snap's calculation engine.

The safest and most effective way to use AI in financial planning is to focus on tasks that improve efficiency without replacing professional judgement.

AI can help summarize client documents, extract information from investment statements, identify missing data, draft meeting notes, prepare client communications, and create first drafts that Advisors can review and verify. In these cases, AI acts as an assistant rather than a decision-maker. Learn more about Snap’s AI Import Assistant here.

Regardless of the tool used, the Advisor remains responsible for validating the information, selecting appropriate assumptions, evaluating recommendations, and ensuring the final advice is suitable for the client. It is also the Advisor's responsibility to be transparent about how AI is used in their practice. They should ensure that any client information shared with AI tools complies with applicable privacy laws, firm policies, the AI provider's terms of service and receives the client's consent to be shared.

The FP Canada Standards Council™ outlines many of the above insights and more information in their Staff Bulletin titled Professional Use of Generative Artificial Intelligence: Guidance for the Profession.


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