United StatesFinance and insurance2025 – ongoingFifth Third Bank
NiCE Enlighten and Topic AI contact-center analytics
NiCE reported a 35% improvement in Fifth Third Bank's customer sentiment scores
Problem
Manual call reviews and limited surveys left Fifth Third Bank with an incomplete view of customer sentiment. Supervisors lacked consistent evidence for coaching.
Approach
The bank expanded NiCE Interaction Analytics and used Enlighten AI to assess agent behavior. Topic AI categorized interactions with generative AI, while staff customized the taxonomy. Results informed coaching and service improvements.
Results
Takeaway
Sentiment scoring became part of supervision. The reported improvement concerned the system's sentiment measure, rather than a separately measured satisfaction survey.
Categories
- Size
- Large enterprise
- Industry
- Finance and insurance
- Business function
- Customer service
- Innovation type
- Process innovation
- AI technology
- Generative AIPredictive analytics and ML
- Adoption
- Vendor solution
- Evidence
- Vendor case study
Sources
Source summaries
NiCE described automated interaction categorization and behavior-based coaching at Fifth Third Bank. It reported a 35% sentiment-score improvement over 18 months and classification accuracy reaching 93%.
Full details are in the original sources.