Raiffeisen Bank Romania: AI-Supported Credit Decisioning with CRESCENDO

How governed AI is helping Raiffeisen Bank Romania evolve credit strategies and turn specialist knowledge into faster, higher-quality decisions.

Raiffeisen Bank Romania, one of the country’s leading financial institutions serving more than 2.36 million customers, is leveraging AI-powered decision intelligence to accelerate credit strategy changes, improve operational efficiency, and strengthen governance across its lending processes. As part of Raiffeisen Bank International (RBI), the bank continues to combine financial expertise and digital innovation to deliver efficient, customer-centric services and support sustainable growth.

Business Imperative: Accelerating Credit Strategy Change

Traditional decision engines often require months to implement even minor changes. Raiffeisen Bank Romania was looking for a more agile operating model to enable the bank to respond more quickly to regulatory developments, shifts in customer acquisition trends, and emerging fraud patterns.

CRIF Solution: How CRESCENDO Supports Teams Across Credit Decisioning

To address this challenge affecting lenders, CRIF introduced CRESCENDO, the decision intelligence solution within CRIF ORCHESTRA. Following its evaluation of the solution, Raiffeisen Bank Romania identified several key capabilities that support a more agile, efficient, and scalable approach to credit decisioning:

• Accelerated Business Agility: Supports faster responses to market dynamics, regulatory requirements, and fraud-related developments while maintaining governance and control.
• Business User Empowerment: Helps non-technical policy managers to confidently design and implement new credit policies with AI assistance, reducing dependency on specialized technical resources.
• Strategy Development Simplification: Streamlines strategy analysis, configuration, testing, and ongoing maintenance through AI, reducing complexity and effort throughout the process.
• Continuous AI Innovation: Supports the progressive adoption of new AI capabilities through a modular agentic ecosystem as business priorities and use cases evolve.

“By embedding agentic AI into the decision engine, our policy managers can configure new credit policies with greater autonomy from IT. This enables our bank to respond to market shifts, regulatory changes, and emerging fraud patterns in minutes—not days. Its modular agentic ecosystem also allows banks to progressively expand their AI capabilities as business needs evolve, while preserving expert oversight and strong governance”

Mihai Rauta, Executive Director Retail Risk, Raiffeisen Bank Romania

Greater Capacity for Quality and Collaboration

By automating repetitive development activities, CRESCENDO enables teams to dedicate more time to validation, knowledge sharing, innovation, and continuous improvement.

“Instead of spending all our time on repetitive development, we can dedicate more capacity to learning, sharing knowledge, and improving the way we work. I see AI not simply as a way to develop faster, but as an opportunity to achieve better quality, fewer bugs, stronger technical capabilities, and a more cohesive team.”

Ionut Vasil, Risk Decisioning System Management, Raiffeisen Bank Romania

Reusable Knowledge and Transparent Rule Management

Acting as an “AI colleague,” CRESCENDO makes previously configured knowledge easier to access and reuse, shortening learning curves and simplifying handovers. It also brings greater clarity and structure to complex, interconnected rule frameworks, helping specialists understand, optimize, and retire rules more effectively. Raiffeisen Bank Romania expects these capabilities to reduce development time by around 30%, with the potential to reach 50% as adoption expands and the solution continues to evolve.

Greater Risk Management Control and Agility

A governed connection between policy, IT, and configuration processes enables risk teams to respond more effectively to regulatory changes, acquisition trends, and emerging fraud patterns. Increased transparency across decision strategies and rules enables faster portfolio optimization while maintaining human oversight and accountability.

“Multiple scores and rules make policy increasingly complex. Better documentation allows teams to interact directly with the system and focus on optimization. When action is required on a specific sub-segment, this approach can eliminate additional development effort and help reach the optimal portfolio segment faster.”

Mihai Rauta, Executive Director Retail Risk, Raiffeisen Bank Romania

Business Outcomes

• Days to Hours: Expected acceleration in implementing and updating credit strategies.
• 30%–50%: Potential reduction in development time as the solution matures and adoption expands.
• Up to 40%: Potential reduction in rejection rates while maintaining credit quality standards.

“Our collaboration with CRIF brings together Raiffeisen Bank Romania’s risk expertise and CRESCENDO’s decision intelligence capabilities. This shared approach allows us to turn innovation into practical value, accelerating change, strengthening control, and creating the conditions for better credit decisions.”

Mihai Rauta, Executive Director Retail Risk, Raiffeisen Bank Romania

“The partnership with Raiffeisen Bank Romania demonstrates the value of combining deep banking expertise with CRIF’s technology and decisioning know-how. By working closely together, we can make governed AI operational and translate it into measurable, sustainable outcomes across the credit lifecycle.”

Marcello Nadalini, Executive Director, Head of Solutions and Digital Services, CRIF