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AI adoption in financial services is no longer experimental – it’s delivering measurable results. Leading institutions across Central and Eastern Europe are proving how agentic AI and data-driven architectures can transform core operations.
Leading European Bank: Building a Data Lakehouse for AI Workloads
Leading European Bank serving over 15 million clients regionally, faced the challenge of modernizing its data infrastructure.
The solution? A migration from an on-premise Oracle data warehouse to a cloud-based Data Lakehouse powered by Databricks. With this foundation, the bank unlocked AI use cases such as:
- Predictive models for marketing campaign efficiency
- Automated report corrections for regulatory compliance with the National Agency for Fiscal Administration
- Competitor analysis against top five national banks
The outcome: streamlined reporting, smarter marketing, and faster decision-making.
Leading Romanian Bank: Scaling HR with Agentic AI
As Romania’s largest bank with over 10,000 employees, the institution struggled with HR overload. Requests flooded in daily, overwhelming a small team.
By deploying AI Agents with Microsoft Copilot Studio and Azure AI Foundry, the bank automated request classification and resolution. Now, tasks like contract updates or leave approvals are managed autonomously.
The result: improved productivity, less employee frustration, and a more agile HR function.
Leading CEE Bank: AI-Accelerated Legacy Migration
The institution, serving 2 million clients in Romania, needed to modernize 80+ legacy apps. Instead of manual rewrites, they turned to AI.
Using AI for code documentation, test scenario generation, and automated unit testing, the bank achieved:
- A 40% reduction in migration effort and timelines
- Preserved functionality on a modern tech stack
- Improved resilience and maintainability
This is a blueprint for how AI can future-proof banking systems without compromising continuity.
The AI Innovation Funnel
What unites these success stories is not just technology, but methodology. Mindit.io’s AI Innovation Funnel ensures that each initiative begins with strategic alignment:
- Initial Assessment – evaluate readiness, infrastructure, and priorities.
- Workshops – define goals, KPIs, and AI scenarios with stakeholders.
- Prioritization Matrix – rank use cases by impact and feasibility.
- Proof of Concept Proposal – validate scope, metrics, and timeline.
This funnel helps banks think big but start small, ensuring incremental growth and organizational buy-in.
Beyond Technology: Culture and Governance
For sustainable adoption, cultural readiness is as important as data pipelines. Banks must:
- Build a culture open to AI adoption
- Foster collaboration across IT, business, and compliance
- Communicate transparently to reduce uncertainty and build trust
With evolving regulations like the EU AI Act and PSD3, robust governance will separate leaders from laggards.
The Takeaway
AI is no longer a promise – it’s a competitive necessity in banking. From data lakehouse to HR agents and accelerated migrations, success stories show the tangible value of AI transformation.
For banks ready to act, the message is clear: start with a real problem, adopt a structured roadmap, and grow incrementally. The future of banking is AI-enabled, human-centered, and innovation-driven.
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