Researchers at the Center for Retirement Research at Boston College modeled a semi-personalized TDF that reflects information known to the employer: the participant’s earnings, plan balance and saving rate. The researchers found that, using this data, households remain in a suboptimal position and require some additional compensation for investing in the strategy to achieve optimal savings. For a household that has precisely the average income, by definition, the semi-personalized portfolio performs just as well as a one-size-fits-all TDF. However, for most other households, the semi-personalized portfolio is closer to the optimal than the one-size-fits-all TDF.

The CRR expanded their model further to include information regarding the participant’s spouse’s income and 401(k) plan balance or the household’s non-401(k) financial assets. The Issue Brief contends that employers can predict this information using the Federal Reserve’s Survey of Consumer Finances and knowledge of the participant’s income, 401(k) plan balance, age, gender, marital status and job tenure. 

Building this information into the methodology used by the CRR brings the allocations closer to the optimal outcome for both types of TDFs. Under the assumptions, if the employer is able to predict the household’s income, the semi-personalized portfolio is perfectly optimal for households at all earnings levels.

The Issue Brief can be downloaded from here.