An HSA provides a direct way to save pre-tax dollars for qualified out-of-pocket medical expenses. By definition, it is a way to save money for health-related expenses. So why do HSAs suffer from chronic negative perception? Lack of adequate education has long been pigeon-holed as the pain of the HSA experience, but that is just one symptom. The real issue is that there is no average HSA account holder. And the industry's understanding of what the typical HSA account holder looks like is wrong. Individual health savings needs vary greatly. A personalized approach is the only way to combat these concerns and deliver a modern, impactful HSA experience.

Looking at a variety of observable data, we can understand expected account value, detailed account usage, and, most notably, how to increase health savings for all types of account holders.

Unlike other behavioral HSA persona studies, our machine learning classifies like groups based on data analysis, not marketing-based segments or assumptions. That also means that data sets can change - and they often do over time. As such, our models and segmentations are configured to change with them. As expected, an HSA account holder can move from one segment to another over the life of their HSA. In fact, from this modeling, we predict the expected path over the lifecycle of an account holder from one persona to the next. Only predictive data modeling, like the one used at Lively, can account for these future iterations.

This first annual report will break down these behavioral-based identifiers from both an account and a demographic perspective. This process allows the needs and expectations of a specific segment to come to the surface in order to create a better experience, that doesn't feel generic. We show user needs and expectations for each HSA persona and critical differences in the HSA from other financial verticals, like retirement.

Key Findings

• 56% of account holders have less than $1,050 in assets in their HSA. The average family spends $8,020 on healthcare expenses each year. HSAs help, but even HSA account holders need more help.
• Healthcare costs are a serious concern and drive direct financial decisions. The majority of HSA account holders are keeping their funds ready for the possibility of unexpected healthcare costs.
• Only 2.4% of account holders had an average balance of $32,000 in assets. These account holders are typically the oldest (59) and have the highest household income (HHI) of all personas.
• The ability to invest is seen as a feature only for high asset accounts. Investment offering impacts both savings and investing. Even lower asset accounts want to invest but have been deterred by HSA investment options and traditional HSA providers' fees.
• That said, HHI is not directly correlated to HSA assets. This runs counter to the 401(k) industry. The age of an HSA is more impactful when it comes to HSA account balance. The older the account (and account holder), the higher the account balance. Account-holders need to start as early as possible to set themselves up for financial success.

Methodology

Lively compiled 13 account traits from 40,000 randomly selected Health Savings Accounts (HSA) for this study, including accounts with and without active contributions. With this information, Lively’s data science team used a machine learning k-means user clustering approach (vector quantization) to organize and delineate the optimal number of HSA personas based on our entire data set of anonymous HSA account holders.