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Gen Z needs life-stage-based financial advice

The data: Gen Zers are becoming increasingly financially independent. A Pathward and Mastercard study of Gen Zers found that 70% of post-college respondents are mostly or completely financially independent, up from 37% in college and 44% in a college alternative.

  • The most popular financial products among post-college Gen Z respondents are checking accounts (88%), debit cards (84%), and mobile payment apps (78%).
  • Gen Zers’ confidence in their knowledge is limited: Fewer than half of post-college respondents are “extremely knowledgeable about finances.”
  • More than half of all respondents are “optimistic about achieving financial goals.”
  • Respondents seek parental financial advice in large numbers: 68% post-college or in a college alternative, 74% in college, and 87% pre-college.

Respondents’ top sources for financial advice are parents and family (74%), peers, friends, or siblings (43%), internet searches (28%), and social media (26%).

Our take: According to our June 2025 report “Future-Proofing Banking Through Customer-Centric Journeys,” banks must pivot from a strategic model based on selling financial products and services to one in which the bank guides customers through solutions to their financial needs and different life stages. Gen Z’s current life stages include:

  • Pre-college, with parental supervision over spending and saving
  • College or a college alternative, when they depend heavily on advice
  • Post-college, when three-quarters are employed but have mixed confidence in their financial knowledge

To offer Gen Z meaningful guidance, banks must offer tools and services relevant to their incremental life stages: More than 60% of US mobile banking users see value in features tailored to their life stages, which is particularly important to serving the mobile-native generation.

All-of-the-above banking apps aren’t the solution: When apps don’t address customer needs with intent, they turn into a jumble of product-based features, sticking to a model that should be long dead.

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