UX Research in Finance: Context Matters
Aug 12
/
Odette Jansen
With insights from Jennifer Blatz, UX Researcher and Design Leader
At UXR Study, we’re speaking with researchers working in different corners of the finance industry to understand how UX research is practiced in this space.
In this article, we share insights from Jennifer Blatz, an experienced UX researcher who’s worked across a wide range of finance sectors—from auto loans to retirement accounts and credit unions. Her experience highlights just how much context, company culture, and business domain shape the way research gets done.
If you’re working in—or considering moving into—finance, this piece will give you a grounded look at what the work really involves.
1. Finance is not one thing
One of the key takeaways from our conversation with Jennifer was how broad the term "finance" really is.
She’s worked on products related to:
She’s worked on products related to:
- Auto loans
- Retirement accounts
- Mortgages
- Credit union platform
Each one required learning entirely new terminology, compliance rules, user expectations, and mental models. Even within the same sector, the research challenges and team dynamics varied significantly.
“Auto loans are not the same as investing tools or internal banking dashboards. The context really matters.”
If you're entering finance UX research, it's important to go beyond the label and understand which part of the ecosystem you're working in.
2. You won’t always be the user
Jennifer shared that when she first worked on auto loan servicing tools, she didn’t have an auto loan herself—and still doesn’t.
In finance, this is common. You may be building for users with highly specialized needs that don’t match your own life experience. The key is to approach it with curiosity and humility, and rely on your research skills to learn from the people who use the systems every day.
3. Challenges that come with the territory
Working in finance brings a set of recurring challenges, many of which are tied to regulation, culture, and operational complexity.
Jennifer mentioned a few that stood out:
Jennifer mentioned a few that stood out:
- Slow participant recruitment. Finding the right users can take several weeks, especially when working through internal channels or legal review processes.
- Compliance restrictions. Even small design or language changes often require legal review and approval, which can delay testing and release.
- Difficulty measuring impact. Research insights often take months to be implemented, making it hard to track outcomes or attribute success.
- Limited visibility. Research may occur weeks or months before decisions are made. Plus,in that time difference, team structures and product ownership can shift. This sometimes creates a gap between insights and outcomes.
4. ResearchOps and stakeholder navigation
In large organizations, researchers are often embedded in product teams but must collaborate across business units, design, and legal. Jennifer emphasized the need to work closely with product managers, while also pushing back when needed.Demonstrating the value of research isn’t always straightforward. She found that sharing competitive examples or highlighting potential cost savings was often more persuasive than presenting findings alone.
“You have to speak the language of the business. Show what’s at risk—not just what users said.”
5. Culture matters as much as compliance
While regulation shapes what’s possible, company culture shapes how work actually gets done. Jennifer noted that some organizations are more open to research and experimentation, while others are more rigid or siloed.
Even within the same industry, different employers had very different levels of maturity in their research operations, tools, and stakeholder understanding.
Knowing how to adapt your approach based on the team and culture around you is just as important as your methods.
6. Cautious approach to AI
We also asked Jennifer about the role of AI in UX research within finance.
Her take: financial institutions are moving cautiously. Some are experimenting with internal tools, but most have not widely adopted AI for research purposes.
Jennifer expressed skepticism about AI’s ability to analyze research data reliably, citing examples where tools produced fabricated or misleading results. For now, her approach is to keep an eye on developments but rely on human-led analysis for anything that informs business decisions.
7. Advice for researchers in finance
Jennifer offered practical guidance for researchers interested in this field:
- Give yourself time to learn. Every domain—whether it’s auto lending, retirement planning, or banking—has its own rules, jargon, and workflows.
- Stay close to the business. Understanding how the company makes money and what success looks for our business partners and stakeholders like helps you uncover insights that matter.
- Work with what you’ve got. Legal constraints, legacy systems, and slow approvals are real. Adapt your research plans instead of waiting for ideal conditions.
- Show the cost of inaction. To get buy-in, frame your insights in terms of business risk or missed opportunities—not just usability.
Final thoughts
Finance isn’t just one industry—it’s a complex system made up of many sectors, users, and priorities. Jennifer’s story reminds us that UX research in this space is deeply contextual. It demands flexibility, business awareness, and strong collaboration across functions.
If you’re moving into finance research, prepare to work across legal, design, and product teams. Expect delays, complexity, and competing priorities. But also expect opportunities to shape systems that impact millions—and to develop a broad understanding of how businesses operate.
This is one perspective. In future articles, we’ll share more stories from researchers across the finance industry to build a richer picture of the work and what it takes to succeed in it.

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