In 2015, PMG was tasked with building a predictive model to identify specific factors that the industry can influence to increase the propensity of an investor’s financial success. The model was initially challenged as the definition of success used in creating the framework was solely based an investor’s level of assets. Examining multiple datasets, we could not establish direct causal correlations between assets and the specific things investors were doing or how they managed their portfolios. Although a link between financial planning and asset level was observed, planning methodologies and engagement behaviour varied greatly.
Back to the drawing board
We needed to approach the problem differently and modify our definition of success beyond simply the level of assets a household possesses. Notably, only 15% of Canadians can fully fund their retirement while the majority rely on company and/or government pension plans to assist in their transition to life after employment. Regardless of where the investor’s journey ends, the pathway is highly influenced by intrinsic behaviors as well as external forces, making ‘success’ a relative term.
We learned that the definition of success is not correlated simply to the level of assets a household possesses, but to a host of different factors. The pathway to financial health is also different depending on life stage. Through multiple research engagements, we determined that success is more closely defined by several weighted factors, including but not limited to: financial assets, rate of savings, debt position, spending behaviour, as well as other non-financial related contributors. We refer to these specific contributors that impact financial success as the Gamma Factors.
When overlaying the new success index against multiple research samples, statistical correlations began appearing everywhere. This allowed us to map specific investor behaviours (advice, product, technology, etc.) that have the greatest contribution to successful outcomes. This was then mapped across age band segments as well as the progressive and successive sub-segments that reside within each of these life stage categories.
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