Open Banking and Customer Experience: Building Loyalty in the Digital Era

Open Banking and Customer Experience: Building Loyalty in the Digital Era

 

Open Banking has become a new standard for financial services worldwide. By enabling the secure sharing of customer data through APIs, banks are reshaping how they interact with clients and how those clients expect to interact with financial products. At the heart of this transformation lies one decisive factor: customer experience.

 

Shifting expectations in the digital age

 

Today’s banking customers no longer measure loyalty by efficiency alone. A quick transaction or error-free service is now taken for granted. What truly differentiates institutions is the ability to deliver simple, transparent, and personalized digital journeys. Customers want products built around their own financial habits, with seamless experiences across channels.

Generational shifts also amplify these expectations. Millennials and Gen Z expect banking to feel like using their favorite apps: intuitive, responsive, and tailored. If their bank cannot provide this, fintechs and digital-first competitors stand ready to step in.

 

Trust as a competitive advantage

 

While bigtechs and neobanks excel at digital design, trust remains a major advantage for traditional banks. Studies consistently show that a significant share of consumers (37% globally) trust their bank more than technology companies to safeguard their financial data. This trust positions banks as natural custodians in the open data economy.

Open Banking allows financial institutions to capitalize on this trust by orchestrating ecosystems where customers remain in control of their data, but still enjoy broader services, from faster payments to new advisory tools.

 

How APIs reshape customer journeys

 

The real promise of Open Banking is the ability to reimagine customer journeys:

  • Open Payments: The “pay with your bank” model is gaining traction as an alternative to cards. It lowers intermediation costs, increases security in e-commerce and subscriptions, and streamlines the checkout process. For the customer, it’s safer and faster. For the bank, it’s stickier engagement and new revenue opportunities.
  • Faster onboarding: By leveraging secure APIs, institutions can streamline KYC and account-opening processes, reducing friction for new customers. This is particularly impactful in competitive markets where convenience drives choice.
  • Personalized insights: Open Banking enables aggregation of a customer’s financial life across multiple providers. Banks that design simple dashboards or advisory tools based on these insights can move from being a transactional partner to a trusted financial coach.
  • Corporate use cases: For business clients, APIs integrate directly into ERP or treasury systems, enabling real-time visibility of liquidity and cash flow. This empowers corporate decision-makers and creates high-value B2B relationships.

 

Revenue and resilience opportunities

 

Customer experience is not only a retention lever; it is directly tied to profitability. Globally, more than $416 billion in banking revenues are at stake in the transition to open data ecosystems. Institutions that move quickly can capture this opportunity by aligning new services with customer expectations.

Equally important, Open Banking partnerships with fintechs and technology players allow banks to remain resilient. Instead of competing with every new player, institutions can integrate them into their ecosystem, offering customers broader choice while retaining control of the relationship.

 

Why banks need to act now

 

The pace of change is undeniable. Three out of four banks worldwide expect Open Banking adoption and API usage to grow by more than 50% in the next few years. In Europe, the number of third-party providers quadrupled in just two years. Latin America is following with Brazil, Mexico, and Colombia pushing regulatory and market-led models.

Banks that delay action risk falling behind as customer loyalty shifts toward institutions that can monetize data and deliver seamless experiences.

Engineering the Future: Inside Our AI-Assisted Legacy Migration Workflow

Engineering the Future: Inside Our AI-Assisted Legacy Migration Workflow

 

Legacy modernization is no longer a luxury. For many companies, it’s the only way to stay competitive, secure, and scalable. But rewriting systems built in languages like VB6, PHP, or .NET Framework is time-consuming and risky, especially when documentation is missing and business logic is buried deep inside outdated code.

At Huenei, we’ve taken a different route. We’ve built a legacy modernization workflow that combines engineering expertise with the power of prompt engineering and large language models (LLMs). The result? Faster migrations, smarter decisions, and more resilient systems.

Let’s walk through how it works and why it matters.

 

A 5-Phase Approach to Smarter Legacy Migration

 

Our methodology is structured around five key phases. Each one leverages prompts to support technical teams without replacing them, acting as a cognitive layer that speeds up and simplifies complex work.

 

1.  AI-Assisted Discovery & Diagnosis

Most legacy systems have little documentation and lots of accumulated complexity. Instead of digging through line after line, we use prompts to:

  • Summarize code modules by purpose and function
  • Map dependencies and detect tightly coupled components
  • Identify critical business logic and custom rules

Example prompt: “Explain this method like you’re documenting it for a new developer.”

This allows teams to move faster without losing context.

 

2.  Target Architecture Definition

Once we understand the current system, we use prompts to evaluate modernization paths based on performance, scalability, and risk.

Prompts help us:

  • Suggest modern architectures (microservices, RESTful APIs, cloud-native patterns)
  • Simulate migration scenarios
  • Recommend refactoring patterns like strangler or event sourcing

This bridges the gap between legacy systems and future-ready platforms.

 

3. Assisted Refactoring & Code Generation

With prompts embedded into developer workflows, we automate many previously manual tasks:

  • Translate legacy code into modern languages and frameworks
  • Generate unit tests for refactored components
  • Improve readability and adherence to current coding standards

Engineers still validate and review, but the process is accelerated and more consistent.

 

4. Living Documentation

We use prompts to create technical documentation in real time, not as an afterthought. This includes:

  • OpenAPI specs
  • Updated README files
  • Endpoint descriptions
  • Functional and architectural overviews

Because it’s generated alongside the code, this documentation is always aligned with the current system and always versioned.

 

5. Continuous Validation and DevOps Integration

Modernization doesn’t end when the code compiles. We integrate prompts into CI/CD pipelines to:

  • Generate changelogs
  • Summarize pull requests
  • Validate refactors and coverage
  • Enforce quality standards through semantic review

PromptOps isn’t just a buzzword, it’s how we embed LLMs into our delivery lifecycle.

 

A Real Transformation in Action

 

In a recent project, we migrated a mission-critical app developed over 15 years ago. No documentation. Discontinued tech. Highly entangled code.

Within weeks, we had:

  • Understood and documented the system using prompts
  • Designed a new architecture
  • Automated the generation of test suites and internal documentation
  • Delivered a fully modernized, scalable platform

All with lower risk, faster delivery, and clearer visibility across teams.

 

Why This Works

 

This isn’t about replacing developers. It’s about enabling them to work smarter. By combining prompt engineering with engineering discipline, we:

✅ Shorten migration timelines

✅ Reduce reliance on tribal knowledge

✅ Deliver better code and documentation

✅ Build reusable assets and libraries for future projects

 

Looking Ahead

 

Prompt engineering has moved beyond experimentation. For us, it’s become a key part of how we modernize systems and scale technical teams — without burning time or resources on outdated methods.

If you’re looking to modernize with confidence, our hybrid approach might be the path forward.

 

Let’s build the future of your legacy together.

From Compliance to Growth: Rethinking Banking Models in the Open Data Economy

From Compliance to Growth: Rethinking Banking Models in the Open Data Economy

 

For years, Open Banking has been framed primarily as a compliance exercise. Regulations across Europe, Latin America, and parts of Asia established standards for data sharing, interoperability, and consumer rights. But as the model matures, it is becoming clear that regulatory alignment is only the first step. 

The real opportunity lies in transforming Open Banking from a legal obligation into a growth strategy. 

 

The pressure on banking margins 

 

The global banking industry faces sustained pressure on margins. Rising operational costs, higher capital requirements, and growing expectations from digital-first customers are eroding profitability. Traditional efficiency levers, closing branches, automating back office processes, or reducing headcount, are no longer sufficient to guarantee long-term resilience. 

In this context, Open Banking emerges not as another compliance burden, but as a strategic lever to unlock new revenue streams. By embracing open data ecosystems, banks can diversify services, strengthen partnerships, and monetize APIs as products in their own right. 

 

Beyond technology: a shift in business models 

 

Many institutions still view APIs as “plumbing”. A technical necessity to comply with regulators or connect with partners. This narrow perspective misses the broader point. APIs represent distribution channels. They enable banks to deliver products beyond their own platforms, reaching customers through fintech apps, corporate systems, and third-party marketplaces. 

 

In other words, Open Banking is not only about redesigning systems. It is about reimagining the business model: 

  • Moving from product-centric to ecosystem-centric strategies. 
  • Monetizing data access as a service for fintechs, insurers, and corporates. 
  • Building value-added services on top of transaction data, such as credit scoring, financial planning, or embedded payments. 

 

This shift is not optional. Competitors that position themselves at the center of ecosystems will capture disproportionate value. Those that remain siloed risk irrelevance. 

 

The rise of partnerships 

 

One of the most promising aspects of Open Banking is the ability to collaborate with fintechs and new entrants rather than compete head-on. Partnering allows banks to accelerate innovation without reinventing the wheel. For example: 

  • A retail bank can integrate a fintech’s personal finance management tool into its mobile app, enhancing customer stickiness. 
  • A corporate bank can connect its treasury services directly into ERP platforms, creating seamless B2B experiences. 
  • A universal bank can leverage fintech lending platforms to expand credit access to underbanked populations while keeping risk management in-house. 

 

In all cases, the open API model allows banks to extend their relevance across customer journeys while maintaining trust as the core differentiator. 

 

Profitability in the open data economy 

 

The scale of the opportunity is undeniable. Globally, more than $416 billion in banking revenues are at stake in the transition toward the open data economy. APIs are becoming products in themselves, with banks charging partners for premium data sets, advanced analytics, or real-time connectivity. 

Equally important, collaboration strengthens resilience. Rather than trying to outcompete every new digital player, banks can become orchestrators of ecosystems, offering customers more choice while capturing a share of third-party innovation. 

 

Corporate treasury and B2B innovation 

 

While much of the Open Banking conversation focuses on retail banking, corporate use cases may prove just as transformative. Large enterprises are demanding real-time visibility of liquidity, cross-border positions, and cash flow forecasting. APIs enable banks to plug directly into ERP and treasury systems, providing: 

  • Instant position management across geographies. 
  • Liquidity optimization through automated sweeps and transfers. 
  • Reduced operational risk by eliminating batch processes and manual reconciliation. 

These capabilities create sticky, high-value relationships with corporate clients, an essential buffer against commoditization in retail banking. 

 

Acting with urgency 

 

The momentum is clear. Three out of four banks worldwide expect Open Banking adoption and API usage to grow by more than 50% in the next few years. In Europe, the number of third-party providers quadrupled in just two years, proving how fast ecosystems can scale once regulation and market demand align. 

For banks in emerging markets, the lesson is straightforward: waiting for regulation to mature is not a strategy. Institutions that take a proactive stance, investing in data governance, API monetization, and partnership models, will be best positioned to capture growth. 

 

The Huenei perspective 

 

At Huenei, we see Open Banking as an inflection point. The winners will be those that treat it not as a box to tick for compliance, but as a platform for growth. Success requires: 

  • Fast integration: APIs that connect seamlessly into ecosystems without downtime. 
  • Specialized teams: squads capable of modernizing legacy systems and embedding security into every layer. 
  • Scalable architecture: solutions that support both current regulatory requirements and future innovation. 

 

Ultimately, Open Banking is about shifting from closed, product-driven models to open, ecosystem-driven strategies. It is about turning regulation into opportunity. 

 
Download the full whitepaper HERE

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A Practical Guide to Open Banking

A Practical Guide to Open Banking

A Practical Guide to Open Banking

 

Open Banking is no longer just regulation — it has become the backbone of modern financial infrastructure. Data sharing through APIs is reshaping how banks connect with customers, fintechs, and corporations. 

This report explores how open banking is evolving into a model centered on customer experience and new business opportunities. It’s no longer only about compliance, but about integrating fast, with no downtime, and with teams ready to capture value. 

In this whitepaper you’ll find:

  • Why customer experience is now the true driver of Open Banking
  • How open payments are changing the digital checkout journey
  • What profitability and resilience opportunities collaboration with fintechs can bring
  • Corporate use cases: treasury and real-time APIs
  • Huenei’s practical vision to accelerate adoption without disrupting operations 

A clear and actionable guide to moving from compliance to value creation with Open Banking. 

 

Read the full report here

Beyond the Rewrite: How Prompt Engineering Is Redefining Legacy Modernization

Beyond the Rewrite: How Prompt Engineering Is Redefining Legacy Modernization

 

Legacy systems are often the backbone of critical operations, but as technology evolves, so does the pressure to modernize. The problem? Traditional modernization approaches are slow, expensive, and risky. Full rewrites can take months (or years), and the cost of lost knowledge, especially in poorly documented environments, is almost impossible to quantify. 

But what if there was a way to accelerate legacy transformation without starting from scratch? At Huenei, we’re using a new strategy that’s changing how legacy modernization happens: Prompt Engineering. 

 

From Code Archaeology to Prompt-Powered Discovery 

 

Legacy applications are built in outdated languages, like Visual Basic, PHP, or .NET Framework, and often come with little to no documentation. Reverse engineering them is tedious. Understanding their logic takes time, and recreating functionality in modern stacks carries high risk. 

Instead of relying solely on manual code analysis, we now use large language models (LLMs) to assist in code comprehension. How? With well-crafted prompts. 

By asking targeted questions like: 

  • “Explain what this class does, like a senior software architect.” 
  • “List the key business rules in this module.” 

…we accelerate understanding. LLMs provide summaries, dependency mappings, and business logic overviews, without the need to read every line. This creates faster alignment and a clearer modernization path. 

 

Not Just Smarter Analysis — Smarter Delivery 

 

Prompt engineering isn’t just about asking questions. It’s about embedding natural language into technical workflows, enabling new kinds of productivity. Here’s how: 

  • Architecture planning: Prompts help simulate migration scenarios and propose cloud-native architectures like microservices or serverless models. 
  • Code refactoring: We use prompts to reframe legacy functions in modern syntax (e.g., from .NET Framework to .NET Core). 
  • Automated testing: With prompts, we generate unit tests from functional descriptions or legacy flows. 
  • Live documentation: As we work, prompts generate OpenAPI specs, README files, and system overviews. No more documentation as an afterthought. 

Every prompt becomes part of a governed, reusable library. Teams iterate, version, and validate them just like they would with code. 

 

Developers Aren’t Replaced — They’re Augmented 

 

Prompt engineering doesn’t eliminate the need for technical teams. Instead, it makes them more effective. 

Engineers still design architectures, validate outputs, and review code. But now, they do it with AI copilots that help reduce repetitive work and make better decisions faster. This also enables less experienced devs to ramp up quickly, leveling the playing field across teams. 

The result? Reduced risk, faster time-to-delivery, and a reusable modernization playbook. 

 

Why This Matters Now 

 

The pressure to modernize is real. But not every business can afford to shut down core systems or spend a year rewriting from scratch. 

Prompt engineering creates a middle ground: an intelligent, scalable approach to evolve what works, without starting over. 

At Huenei, we believe modernization doesn’t have to mean disruption. By blending AI and engineering best practices, we’re turning technical debt into a launchpad for innovation. 

Ready to rethink your legacy strategy? 

 

 

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