Case Study · Productivity
Alior Bank's voicebot won an international award for measurable, not just flashy, results
What happened
Alior Bank deployed InfoNina, a voice assistant, alongside a speech-analytics platform that monitors and analyzes conversations between bank representatives and customers. The system wasn't positioned as a customer-facing novelty - it was built to measurably improve how call-center interactions were handled.
The bank reported roughly a 10% reduction in average call handling time and more than 30% of calls automated. Retail Banker International recognized the deployment with its "Best Banking Use of AI" award, judging it specifically on operational impact rather than the technology itself.
The business problem
The bank needed to improve call-center efficiency and consistency without sacrificing service quality in a function customers interact with directly.
Why it worked
- The strongest AI adoption case studies have a number attached - call time, automation rate, resolution rate - not just a description of the feature
- Speech analytics on existing conversations is a lower-risk starting point than a fully autonomous customer-facing system
- External recognition follows measurable operational results, not the novelty of the technology used
- Combining a voice assistant with an analytics layer creates a feedback loop for continuous improvement, not just a static deployment