What challenges did Commerzbank face before AI implementation?

Provide fast, consistent, cross-channel customer service. Reduce wait times and churn while improving self-service. Handle a large volume of FAQs and support seamless handoff to human agents.

What was the impact of the AI solution?

The proof-of-value was set up in nine weeks. The implementation improved operational efficiencies and customer experience through reduced wait times and self-service. The bank reported greater employee productivity through enriched CCAI data and expects improved conversion rates from more fruitful customer journeys.

Source

GCPExpanded

Commerzbank chatbot for customer service using Contact Center AI and Dialogflow CX

Use case typeCustomer service automationUpdated Jun 13, 2026

Commerzbank, through Commerz Direktservice, implemented a customer-service chatbot to provide fast, consistent support across app and web channels. The solution was designed to handle more than 100 FAQs, identify leads and prospects, and transfer complex cases to human agents with enriched context.

Organization: Commerzbank
Industry: Finance
Location: Germany
Published: June 2022

Reported outcomes

Strategic outcomes

Customer experience & trustImproved self-service customer supportSpeed & agilityBuilt chatbot rapidlyEmployee experienceGreater employee productivityNew product / capabilityEnabled lead identification and handoff

Primary read

Use case focus

Showing 3 of 3

1Customer Service Automation
2Conversational AI
3Contact Center Modernization

Provide fast, consistent, cross-channel customer service.
Reduce wait times and churn while improving self-service.
Handle a large volume of FAQs and support seamless handoff to human agents.

Commerzbank built an agile proof-of-value chatbot in nine weeks using Google Contact Center AI and Dialogflow CX.
The chatbot detects the customer touchpoint (app or web), answers suitable FAQs, identifies leads and sales prospects, and supports handoff to human agents with enrichment parameters.
Commerzbank integrated Dialogflow CX with the Genesys platform to leverage existing contact center infrastructure and orchestrate incoming interactions.

Technologies

Google Contact Center AI Dialogflow CX Genesys Platform

The proof-of-value was set up in nine weeks.
The implementation improved operational efficiencies and customer experience through reduced wait times and self-service.
The bank reported greater employee productivity through enriched CCAI data and expects improved conversion rates from more fruitful customer journeys.

Architecture

A customer-service chatbot built with Google Contact Center AI and Dialogflow CX, integrated with the Genesys platform and connected to existing on-premise applications and components to support resilient, secure omnichannel orchestration.

Implementation partners1

Genesys

Sources & evidence1

ExpandedExpanded

The same organization appears in newer AI deployment evidence.