Modern data architecture can turn open banking into a business accelerator
JUL. 3, 2025
3 Min Read
Open banking isn’t just about APIs—it’s a data-driven strategy that can unlock new revenue, quick ROI, and smarter services for banks.
Open banking is no longer just an IT integration project; it has become a strategic data initiative that drives tangible business results.
Banks that treat open banking as part of a broader data strategy are realizing new revenue streams and faster innovation, rather than simply meeting compliance mandates. The opportunity is massive: open banking users worldwide are expected to exceed 645 million by 2029 (up from 183 million in 2025), with particularly high monetization potential in areas like underwriting and identity verification. Financial institutions embracing this mindset are transforming previously siloed information into personalized services and partnerships that generate value quickly, all while maintaining the stringent security and regulatory standards the industry demands.
Key Takeaways
- 1. Open banking delivers measurable value when treated as a data-centric business initiative rather than a basic API or compliance requirement.
- 2. Modern cloud-native platforms, data lakes, and streaming analytics form the critical foundation for scalable open banking success.
- 3. AI-powered open banking services must be explainable, auditable, and aligned with regulatory expectations to build trust and avoid risk.
- 4. Early wins like real-time personalization and partner integrations demonstrate ROI and pave the way for broader data modernization.
- 5. Strategic partners with regulatory and architecture expertise help banks accelerate time-to-value while ensuring compliance and scalability.
Open banking’s value lies in data, not in integration alone
Many banks first treated open banking as a checkbox compliance exercise, exposing a few APIs just to satisfy regulations. This narrow approach misses the real prize: the rich data flowing through those APIs. Treating open banking as more than a connectivity project, banks can monetize data via personalized offerings, ecosystem partnerships, and insights that directly drive revenue. In contrast, an API-only mindset yields little ROI and often stalls out once the technical work is done.
The evidence of data’s value is compelling: 87% of U.S. consumers now use open banking services in some form, creating streams of transactions and insights. Forward-looking banks transform this flood of data into actionable intelligence by launching personalized product recommendations or forging fintech partnerships that drive new services. Breaking down internal silos and analyzing aggregated customer information enables these banks to uncover unmet needs and profitable niches that would have remained invisible. This “data-to-value” approach quickly translates into tangible revenue and efficiency gains, far beyond what basic API integrations achieve.
Cloud-native platforms and data lakes lay the groundwork for open banking success
A modern, scalable architecture is the unsung hero behind any successful open banking program. Banks need technology environments that can ingest massive volumes of data from APIs, store it securely, and analyze it in real time. Traditional legacy systems simply aren’t built for this level of agility or scale. That’s why cloud-native platforms, data lakes, and streaming analytics have become foundational for open banking initiatives. Together, these technologies ensure that opening up data doesn’t overwhelm the bank, but rather propels it forward.
Cloud-native platforms for agility and scale
Moving core systems to the cloud is a game-changer for open banking. Cloud-native platforms let banks rapidly deploy new API-driven services and scale on demand as data volumes surge. No longer tied to on-premises hardware, a bank can process open banking transactions with far greater speed and flexibility. It’s no surprise that nearly 80% of financial institutions are ramping up cloud investments to meet these needs. Cloud platforms also come with built-in security and compliance features, ensuring that as banks open their data, it remains protected.
Unified data lakes break down silos
A cloud-based data lake aggregates information from core systems, customer channels, and open banking APIs into a single repository breaking down silos between products and teams. With all customer and transaction data in one place, banks can run advanced analytics to uncover patterns and opportunities across the entire portfolio. Modern data platforms like Snowflake and integration tools such as Talend help ingest and organize these massive datasets, while analytics solutions (for example, Qlik) enable business teams to derive insights quickly. Unifying disparate data gives open banking feeds a 360-degree view of each customer that can fuel more targeted services and proactive risk management.
Streaming analytics for real-time insights
Real-time data streaming is the third pillar. Processing open banking events as they happen means banks can react instantly to emerging trends or threats, such as sending a personalized offer right after a spending spike or flagging a suspicious transaction on the spot. Banks that master real-time data can deliver the instant, tailored experiences customers now expect, gaining an edge in service quality. This capability helps turn raw data into immediate action, meeting customer expectations for swift service while also protecting the institution.
Together, these architectural elements do more than just support compliance, as they unlock the agility, insight, and scalability needed to turn open banking from a technical initiative into a high-impact business strategy. With the right foundation in place, banks can move faster, innovate with confidence, and extract real value from every data exchange.
"Banks that treat open banking as part of a broader data strategy are realizing new revenue streams and faster innovation."
Open banking AI must be explainable and compliant to build trust
Adding AI-driven services on top of open banking data raises new challenges: customers and regulators demand that automated decisions be transparent, fair, and accountable. To innovate with AI without eroding trust, banks must ensure their models are explainable, well-governed, and used responsibly under strict oversight.
- Explainable AI algorithms: Ensure AI decisions on open banking data can be understood and justified. Regulators increasingly expect banks to explain how their models make decisions, so transparency is essential for trust.
- Robust model governance: Treat AI algorithms like any other critical model, with rigorous validation, bias testing, and oversight. Embedding AI into the bank’s model risk management framework keeps it compliant with fair lending and other rules.
- Data privacy and security: Open banking data sharing demands strict adherence to privacy laws and cybersecurity standards. Banks must encrypt sensitive data, audit its usage, and ensure third-party partners meet equally strong security requirements.
- Customer consent and control: Customers should have clear control over what data they share and how it’s used. Explaining the benefits of data sharing and allowing easy opt-outs builds trust, especially since only 27% of consumers currently trust AI for financial advice.
- Continuous monitoring: After deployment, AI models need ongoing monitoring and periodic audits to catch any issues or drift. This vigilance ensures the AI remains fair, accurate, and compliant over time, reinforcing stakeholder confidence.
Responsible AI in open banking is not optional. It is foundational to scaling innovation while maintaining trust. With clear governance, explainability, and oversight, banks can confidently use AI to personalize services, strengthen security, and meet regulatory expectations at the same time.
"Cloud-native platforms let banks rapidly deploy new API-driven services and scale on demand as data volumes surge."
Open banking delivers quick wins that justify broader data investments
For banks under pressure, open banking can deliver rapid wins that prove the value of data modernization. Using open banking data to offer personalized financial wellness tools, for example, can immediately boost customer engagement and generate new revenue through cross-sell opportunities. Many banks are also partnering with fintechs to launch services—like integrated small-business accounting or streamlined loan applications—that start contributing fee income as soon as they go live.
Operational efficiencies provide quick wins as well. Consolidating and automating data flows often uncovers redundancies and cuts costs. Migrating from legacy systems to cloud data platforms has reduced total IT costs by as much as 40% over five years for some institutions. Those savings, combined with faster product rollouts and improved customer satisfaction, create a compelling business case for further open banking investments. Early successes build confidence among stakeholders and pave the way for scaling up larger digital transformation initiatives.
Lumenalta’s approach to data-driven open banking acceleration
Maintaining momentum after early open banking success requires a shift from isolated integrations to cohesive, scalable architecture. CIOs need more than infrastructure; they need a coordinated system of cloud-native services, governed data pipelines, and explainable AI that together reduce friction, increase transparency, and enable new services to launch quickly. The challenge is building this system without adding technical debt or compromising compliance in the process.
Lumenalta works directly with IT and business leaders to co-develop this foundation. Our approach embeds modern architecture within your delivery workflows, focusing on practical wins like shortened release cycles, more efficient data operations, and model governance that satisfies both regulators and stakeholders. With the right architecture and execution model in place, banks move faster, reduce risk, and convert open banking from a compliance cost into a long-term business accelerator.
Table of contents
- Open banking’s value lies in data, not in integration alone
- Cloud-native platforms and data lakes lay the groundwork for open banking success
- Open banking AI must be explainable and compliant to build trust
- Open banking delivers quick wins that justify broader data investments
- Lumenalta helps turn open banking into a business accelerator
- Common questions
Common questions
How can open banking create business value for my bank?
What data architecture do I need for open banking success?
How can I use AI in open banking without risking compliance?
What quick wins can justify investing in open banking projects?
How can a partner like Lumenalta help accelerate open banking initiatives?
Transform your open banking strategy from regulation to revenue. Go beyond compliance, turn open banking into a growth engine.
