Generational Trends in Financial Services

by Josee Farmer 2 min read June 24, 2025

Understanding generational trends and preferences is more crucial than ever, especially for the financial services industry. From Baby Boomers to Gen Z, each generation brings a unique set of preferences, values, and challenges. Financial institutions must navigate a complex web of technological advancements, demographic shifts and changing trends to match consumers of different generations with tailored solutions. Exploring the world of generational dynamics within the financial sector reveals how different age groups interact with financial products and services, and what this means for the future of the industry.

The next five years are crucial for key financial milestones: the largest Gen Z cohorts will turn 18 and acquire credit, millennials will reach the average first-time homebuying age of 38, and Baby Boomers and older Gen X cohorts will reach the average retirement age of 63.

Amid these demographic shifts, Gen X stands out with the highest expenditures among all generations, while millennials are growing their assets through homebuying and investments. Credit cards are increasingly the first acquired credit product, reflecting a trend towards early financial independence. Additionally, the preference for digital financial services and banking interactions decreases with age, highlighting the generational divide in embracing technology. Explore these generational trends, preferences and insights below and with even more depth in our Generation Next Chartbook.

Gen Z

The entire Gen Z generation will be old enough to independently acquire credit by 2031, with the largest cohorts reaching the age of credit-eligibility over the next 1-2 years. However, as the effects of declining birth rates come into effect, the subsequent cohorts will be smaller in size.

Millennials

Millennials are the largest generation, and over the next five years, the largest cohorts of millennials will reach the average first-time homebuying age of 38.

Gen X and Baby Boomers

The largest cohorts of the Baby Boomer population and the oldest Gen X cohorts are at or near average retirement age, and with Baby Boomers leaving the labor force and retiring earlierthan prior to the pandemic, we are in the midst of an immense retirement wave.

Download our generational trends report to uncover more trends shaping the financial preferences of today’s generations.

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When a credit view and a fraud view are generated separately, they must be reconciled instead of read together in the same instant. Every handoff is a place where a decision slows down and a signal gets missed. It's why a fraud pattern that would be obvious next to the credit file often surfaces only after the funds are already gone. Fragmentation also makes it harder to optimize lending strategies over time. When data, analytics and decisioning are disconnected, credit unions have less visibility into what's working, what's changing and where strategies need to be adjusted. An integrated decisioning ecosystem closes those seams by design, with credit, fraud and lending strategy running on one platform and accessed through a single Application Programming Interface (API). Identity and compliance capabilities can be an integrated decisioning flow. The data doesn't need to be reconciled after the fact because it was never separated in the first place. Stop overengineering, start removing friction When decisioning underperforms, the instinct is to build something more custom: a proprietary model, tighter segmentation, more configuration.  Custom modeling has its place for institutions with the scale and data to justify it. But often, for small or mid-sized credit unions, the bigger opportunity is a flexible decisioning strategy that uses a strong, continuously refreshed model. This shouldn't be either/or. The right approach gives credit unions a strong decisioning strategy today, with the ability to introduce more customized analytics and modeling as their needs evolve.  The same principle applies to strategy management: credit unions can gain greater control through self-service capabilities as they build a more sophisticated data science team.   That kind of flexibility is important as credit unions modernize their decisioning infrastructure. 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A smaller number are flagged for quick step-up verification and cleared within minutes. Only genuinely ambiguous cases reach an underwriter, who is working from one complete picture instead of reconciling multiple signals. The member has an answer before the weekend is over. The credit union books the loan before competitors even open on Monday. Built to scale This kind of process holds up today. However, the better test is whether it holds up eighteen months from now when application volume has grown, new products are live and the data flowing through the system looks nothing like it does right now. Future-proofing isn't only about handling more volume. It's about having room to be nimbler and make adjustments as quickly as the market changes. A credit union that relies on standard models within a decisioning strategy may want more customized analytics and greater control over its strategies tomorrow. 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