Article
Technology modernization to improve customer experience for banks, credit unions
Automation, AI and a cloud strategy can reduce friction and support growth
Key takeaways
Many banks and credit unions still rely on legacy systems and manual processes that slow service.
Cloud strategy plays a critical role in enabling automation, AI and data integration.
Data governance is foundational for financial institutions’ technology modernization initiatives.
Midsize community banks and credit unions are under pressure to deliver fast, intuitive digital experiences while managing risk, regulatory expectations and cost constraints. Many institutions, however, still rely on legacy systems and manual processes that slow service and limit visibility across the organization.
Process automation is a critical starting point for modernization efforts, but it is most effective when paired with data platforms, artificial intelligence tools, a strong data framework and a thoughtful data strategy. All these capabilities are anchored by a strong cloud strategy and application architecture. Together, these capabilities can help financial institutions modernize incrementally while improving customer experience.
Automation also benefits employees. Streamlined processes can reduce manual data entry and make information easier to access and track. With fewer administrative burdens, bank staff can spend more time on relationship‑driven work, judgment‑based decisions and proactive service, all of which contribute to a stronger customer experience.
What’s more, automation and related technologies are becoming more of a competitive imperative: 71% of respondents to the Bank Director’s 2025 Technology Survey said their organization increased its budget for technology in fiscal year 2025 compared to its technology budget for fiscal year 2024.
How AI in banking can extend the value of automation
As banks mature their automation efforts, AI tools can extend value beyond simple task execution. These AI tools can help interpret data, identify patterns and support decision making in ways traditional automation cannot. For example, AI‑enabled document processing can extract and validate information from loan files, account-opening forms or compliance documents more efficiently than manual review. Second, review processes can provide meaningful insight without adding resources by focusing on root cause analysis and exception clearing.
In customer‑facing interactions, AI‑powered virtual assistants can handle routine inquiries, guide users through processes and escalate complex issues to appropriate staff. When implemented thoughtfully, these tools can improve response times without sacrificing service quality. Importantly, AI should support rather than replace human judgment, particularly in areas involving credit decisions, compliance or exception handling.
Across the financial services ecosystem, AI has also become table-stakes; in the RSM Middle Market AI Survey 2026, 87% of the 193 respondents from financial services organizations reported that AI is at least partially integrated into their operations, including 41% who reported full integration, with AI embedded across core operations and processes.
The survey data reinforces that AI is being used across a wide range of capabilities. Among financial services respondents:
- 69% are using generative AI
- 60% are using prediction AI
- 55% are using language AI
- 51% are using agentic AI
Why data governance is essential for AI and banking modernization
AI tools are most effective when embedded within well‑designed processes, and data governance is a key foundation for such processes. Many midsize banks and credit unions struggle with fragmented data spread across systems, departments and vendors.
RSM’s AI survey found that the leading inhibitors to AI deployment in financial services are:
- Security and privacy concerns (33%)
- Data quality and availability issues (32%)
- Integration with legacy systems (27%)
A robust data framework helps support accurate, accessible and usable information across the organization. For customer experience, this means fewer channel disconnects and a more complete view of the customer relationship. For example, relationship managers, lenders and service teams can access consistent data during customer interactions, reducing the need for repeated questions or accessing multiple systems.
A strong data framework also supports reporting, risk management and regulatory compliance. Automated data pulls and standardized definitions can reduce errors and rework while improving confidence in insights used for decision making. Over time, this foundation enables more advanced analytics and AI use cases.
How cloud strategy supports banking technology modernization
Cloud strategy plays a critical role in enabling automation, AI and data integration. Rather than requiring a wholesale replacement of legacy systems, cloud-based platforms can act as an integration layer, connecting existing applications and enabling scalable innovation.
For midsize and community banks and credit unions, the cloud offers flexibility to modernize at a manageable pace. Teams can deploy new capabilities, test use cases and scale successful solutions without large upfront infrastructure investments. Cloud environments also support faster updates, improved resilience and better collaboration across teams.
When aligned with governance and security requirements, cloud strategy can help banks and credit unions balance innovation with risk management, a key consideration for financial institutions.
Where banking technology modernization efforts can deliver value
When it comes to modernization efforts enabled by automation, AI, strong data governance and cloud-based strategies, banks and credit unions may see benefits by focusing on high‑volume, repeatable processes that directly affect customers, such as:
- Loan operations: Automated data collection, document review and workflow routing can speed up credit decisions and reduce back‑and‑forth with borrowers.
- Account opening and onboarding: Digital identity verification, document upload and workflow automation can shorten onboarding timelines for retail and business customers.
- Customer service: AI‑enabled chat and case routing can improve response times while allowing staff to focus on complex needs.
- Compliance and reporting: Automated data aggregation and validation can reduce errors and ease the burden on compliance teams.
Key considerations for financial institution leaders
Modernization efforts are most successful when treated as a strategic initiative rather than a series of disconnected technology projects. Leadership teams should focus on the following:
- Clarify customer experience goals: Identify where friction occurs today and which moments matter most to customers.
- Understand system and data readiness: Assess how data flows across platforms and identify where integration gaps exist.
- Start with focused, achievable initiatives: Small wins build confidence and demonstrate value without disrupting operations.
- Support people through change: Clear governance, communication and training help support adoption and sustainability.
A strategic path forward
Process automation is a powerful foundation for improving customer experience, but its impact grows when combined with AI tools, a strong data framework and a cloud-enabled architecture. Together, these capabilities can help banks and credit unions modernize, enhance service delivery and position themselves for future growth.
Frequently asked questions
Technology modernization involves updating systems, processes and tools to help banks and credit unions operate more efficiently and serve customers more effectively. Modernization often includes automation, artificial intelligence, improved data management and cloud-based technologies.
