Case study: Fifth Third Bank

Fifth Third Bank Modernizes CX with NiCE GenAI Powered Interaction Analytics

Fifth Third Bank is one of the largest money managers in the Midwest, with over $211 billion in assets and a strong focus on delivering top-tier customer experiences.

CUSTOMER PROFILE

ABOUT

Fifth Third Bank, a subsidiary of Fifth Third Bancorp, is a leading financial institution headquartered in Cincinnati, OH.

INDUSTRY

Financial services

WEBSITE

LOCATION

Cincinnati, OH

AGENTS

1,500

GOALS

  • Replace surveys with scalable insight into customer sentiment
  • Improve CX through agent behavior coaching
  • Enable real-time root cause analysis
  • Streamline operations through AI-powered interaction analytics

FEATURES

  • Topic AI replaces manual queries with automated interaction categorization
  • Sentiment and agent softskill behavioral scoring on every call
  • Customizable generative AI-powered topic taxonomy and dashboards
  • Automated trend tracking and alerting
  • Integrated coaching workflows

01 THE BEFORE

Legacy systems with limited insights

Fifth Third Bank’s contact center relied on manual quality evaluations and a handful of post-call surveys per agent per month, representing just a drop in the bucket of thousands of daily customer interactions. These limited snapshots left blind spots, especially when it came to understanding customer sentiment or uncovering recurring service issues.

“We were pulling calls manually, and it wasn’t scalable or efficient,” said Kara Hoyer, Vice President, Speech Analytics and Vendor Oversight Program Manager at Fifth Third. “Customer sentiment was anecdotal at best. We didn’t have a consistent way to measure it.”

02 THE DESIRE TO CHANGE

A mission to modernize customer experience

With a focus on customer service, Fifth Third Bank needed better tools. Leaders wanted to move beyond spot-checks and survey samples to gain a complete, data-driven picture of performance. The goal was to make sentiment a primary measure of success and refine processes based on insights from all customer interactions, not just a limited number of surveys.

Pilot programs leveraging NiCE Interaction Analytics sentiment analysis capabilities confirmed the potential. One early win traced a call spike to unclear online messaging. Fixing the language reduced volume almost immediately, proving that interaction analytics could speed decision-making and improve outcomes.

Customer sentiment is the one metric we look at more than anything else. It’s more important than handle time—it drives who gets recognized, who gets coached, and how we improve.

KARA HOYER

Vice President, Speech Analytics and Vendor Oversight Program Manager Fifth Third Bank

03 NiCE SOLUTION

NiCE Interaction Analytics aligned to customer and business priorities

Fifth Third Bank now uses NiCE Interaction Analytics to measure and improve customer experience at scale, with sentiment scoring the centerpiece. Results inform coaching, leadership reviews, and recognition, including eligibility for the bank’s top honor, the President’s Circle.

Supervisors rely on Interaction Analytics with Enlighten AI for CSAT to identify agent behaviors—such as demonstrating ownership, asking effective questions, and active listening—that are proven to be tied to positive sentiment. Reviewing high- and low-performing calls has helped agents build confidence and skills.

“It’s hard to coach consistently if you’re not looking at the same thing,” Hoyer said. “Now we’re comparing apples to apples—everyone’s using the same behaviors, same standards, and same expectations.”

The bank also used the Interaction Analytics Topic AI feature to replace manual queries with automated interaction categorization. Powered by generative AI technology combined with pre-built, industry-specific CX AI models, Topic AI provided Fifth Third Bank with a fast and accurate analysis of all of their interactions with less effort. The bank also used the Topic AI Editor to customize the taxonomies to align with their processes and terminology, ensuring clarity and consistency across reports. Fifth Third Bank’s initial implementation of Topic AI immediately boosted interaction classification accuracy by 12 percentage points, reaching 93%, and increased call coverage by 2.3 percentage points, reaching 87%. Additionally, Interaction Analytics has powered more than 80 cross functional initiatives this year, from workforce planning to CX strategy.

04 THE RESULTS

Steady sentiment gains and stronger collaboration

Since implementing Interaction Analytics, sentiment scores have improved across Fifth Third Bank’s call centers, with a 35% improvement recorded over 18 months. Coaching is now consistent and based on comprehensive call data.

Topic AI has also improved efficiency, saving the equivalent of one-quarter of a full-time employee—time that’s now spent on deeper analysis and collaboration with teams across the organization. Leaders have more confidence in CX data, and requests for support have increased as the value of analytics becomes clearer.

“As we’ve improved our sentiment scores, we’ve also seen an increase in how other departments engage with us,” Hoyer said. “Whenever somebody is working to make a process improvement, we are their stop one, and I love that. People know we have reliable data now, and they want to use it.”

“We’re layering on sentiment, volume, and handle time so we can better tell that story and ensure that any customer experience issues are being addressed. It has helped us move from reactive fixes to proactive improvement.”

05 THE FUTURE

A culture of continuous improvement

With actionable insights drawn from 100% of interactions, Fifth Third Bank is building a culture that centers on customer sentiment. Supervisors are equipped with tools to coach effectively and recognize performance in meaningful ways, and the bank anticipates continued improvements as it leverages AI to deliver interaction insights at scale.

“It has been remarkable to witness the transformation,” Hoyer said. “Agents now care more because every call counts. Supervisors appreciate the comprehensive data available for each call, including agent behaviors, which was not possible before. Department leaders value the granularity of the data and trust the sentiment performance more than surveys, knowing it accounts for every single call rather than just a sample. NiCE has enabled us to focus on the customer experience of every call through customer sentiment.”

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