Are UI Component Libraries Becoming a Liability for Long-Term React Native Projects?

Haley — Thu, 18 Jun 2026 12:00:54 +0000

A question I've been thinking about lately:

Many React Native apps were built using libraries like NativeBase because they accelerated development and provided a consistent design system across platforms. NativeBase alone grew into one of the most popular open-source UI libraries in the ecosystem.

But over time, I've noticed a trend in community discussions:

1.Teams wanting deeper customization.
2.Concerns around performance in larger applications.
3.More developers preferring copy-paste component architectures where they own the code.

This isn't specifically about NativeBase—it's a broader discussion about UI libraries in general.

For developers who have maintained React Native apps for 2+ years:

Would you choose a UI library again, or build your own design system from day one?

Stop Building AI Chatbots. Build AI Systems That Make Money.

Haley — Thu, 18 Jun 2026 05:29:52 +0000

The AI conversation in financial services has become strangely repetitive.

Every week, another company announces an AI assistant, an AI chatbot, or an AI-powered customer experience initiative.

Meanwhile, the biggest opportunities in fintech are happening somewhere else entirely.

They're happening in customer retention and fraud prevention.

And in my opinion, companies focusing on these two areas are far more likely to create measurable business value than companies chasing the latest AI interface trend.

Recently, I came across two interesting articles discussing how AI-powered financial platforms are increasing customer retention and revenue, and how AI-driven fraud prevention is reducing financial losses and operational costs.

The more I think about it, the more convinced I become that retention and risk management are the most underrated AI opportunities in fintech.

The Industry Is Obsessed With Acquisition

Most fintech discussions revolve around growth.

More users.
More downloads.
More signups.

But what happens after acquisition?

That's where many platforms struggle.

Customer churn remains one of the most expensive problems in financial services. Users open accounts, try products, and quietly leave.

AI is changing that.

Modern financial platforms can analyze transaction behavior, spending habits, engagement patterns, and financial goals to deliver highly personalized experiences.

Not because personalization is trendy.

Because personalization keeps customers engaged.

And retained customers generate revenue.

My Take: Retention Is More Important Than Acquisition

But I believe most fintech companies spend too much money acquiring users and too little effort keeping them.

A 10% improvement in retention can often be more valuable than a massive increase in marketing spend.

AI makes this possible through:

Personalized recommendations
Predictive engagement models
Financial wellness insights
Smart notifications
Behavioral analytics

The result isn't just better customer experience.

It's higher lifetime value.

Fraud Prevention Might Be The Best AI Use Case In Fintech

If retention is underrated, fraud prevention is even more overlooked.

The AI industry loves flashy demos.

Fraud prevention doesn't create flashy demos.

It creates profits.

Every fraudulent transaction prevented has a direct financial impact.

Every false positive eliminated reduces operational costs.

Every automated investigation saves valuable human resources.

That's why I think fraud detection is one of the few AI investments that consistently produces measurable business outcomes.

What The Leading Companies Are Doing

Many of the companies building modern financial systems have already shifted toward AI-powered intelligence layers rather than simple automation.

Organizations such as Palantir Technologies, FICO, Thoughtworks, EPAM Systems, Globant, and GeekyAnts are part of a broader industry movement focused on building intelligent financial products rather than simply digitizing existing processes.

What's interesting is that the conversation is increasingly shifting from "How do we add AI?" to "Where does AI create measurable business outcomes?"

That is a much better question.

Developers Should Pay Attention

As engineers, we often get excited about models, frameworks, and tooling.

Business leaders care about different metrics.

Revenue.

Retention.

Risk.

Operational efficiency.

The AI projects that survive budget reviews are rarely the coolest ones.

They're the ones that improve those four metrics.

That's why I think the future of fintech AI won't be defined by who builds the smartest chatbot.

It will be defined by who keeps customers longer and loses less money to fraud.

Everything else is secondary.

Final Thought

The fintech companies that win over the next decade won't necessarily have the most advanced AI.

They'll have the most practical AI.

The companies using AI to increase retention, reduce fraud, lower operational costs, and improve customer lifetime value are solving real business problems.

And in technology, solving boring problems usually turns out to be the most profitable strategy of all.

DEV Community: Haley