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The Future of Networking in 2025 and Beyond
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About us
CLIENT STORIES
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Liantis
Over time, Liantis – an established HR company in Belgium – had built up data islands and isolated solutions as part of their legacy system.
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Randstad
We ensured that Randstad’s migration to Genesys Cloud CX had no impact on availability, ensuring an exceptional user experience for clients and talent.
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CLIENT STORIES
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Liantis
Over time, Liantis – an established HR company in Belgium – had built up data islands and isolated solutions as part of their legacy system.
-
Randstad
We ensured that Randstad’s migration to Genesys Cloud CX had no impact on availability, ensuring an exceptional user experience for clients and talent.
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CLIENT STORIES
-
Liantis
Over time, Liantis – an established HR company in Belgium – had built up data islands and isolated solutions as part of their legacy system.
-
Randstad
We ensured that Randstad’s migration to Genesys Cloud CX had no impact on availability, ensuring an exceptional user experience for clients and talent.
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Everest Group PEAK Matrix® Assessment
NTT DATA is a Leader and Star Performer in the Everest Group Sustainability Enablement Technology Services PEAK Matrix® Assessment 2024.
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- Careers
MONETA Money Bank is a highly digitized bank in the Czech market that enables its customers to handle most of their requests through self-service options such as internet banking or a mobile application. The bank’s long-term goal is to maximize the efficiency of available resources and use modern technology to optimize its processes. This strategy aligns well with the bank’s efforts to digitize and automate the handling of common customer requests through its call center.
After a successful and longstanding collaboration on implementing and operating the call center using the Genesys platform, MONETA Money Bank decided to adopt a voicebot solution developed by NTT in partnership with Feedyou. This solution is built on the integration of several cloud technologies and uses the bank’s internal systems to carry out its tasks. At the beginning of the project, strict criteria for success were established. All of these were met, and the implementation team even exceeded expectations in certain parameters.
Client profile
With a customer base of more than 1.5 million, MONETA Money Bank is the fourth-largest bank in the Czech Republic. They operate a network of 140 branches with more than 2,500 employees. In 2022, the bank reported a net profit of 5.2 billion Czech koruna. As recognized by Deloitte, MONETA Money Bank stands at the forefront of digitalization and ranks among the top 10% of the world’s leading digital banks.
Vision
Accelerating customer call handling without increasing call center operator numbers
As the COVID-19 pandemic unfolded, MONETA Money Bank experienced a significant increase in the number of customer calls to their call center. These numbers haven’t fallen back to pre-pandemic levels: the call center receives thousands of calls every day, many of which are about unblocking internet banking, resetting passwords and adjusting online payment limits.
The bank wanted to improve the customer experience by reducing waiting times and handling customer requests faster. And they needed to do this by using their available resources efficiently to avoid the burden of additional call center operational costs. MONETA Money Bank therefore opted to deploy an advanced voice assistant, or voicebot. This cutting-edge technology proved to be the most effective approach to meet the increasing demands of the call center.
The voicebot was equipped with identity verification capabilities and the ability to recognize and autonomously address common reasons for customer calls.
“Our customers like to handle their requests remotely, using the internet and phone. We needed a solution that would substantially increase the capacity of our call center, efficiently handling the most common types of requests without the need to transfer the call to an operator.”
Transformation
Voicebot expands call center capacity in just a few weeks
MONETA Money Bank and NTT share a long history of successful cooperation, including the implementation of the bank’s Genesys call center and an extensive project to optimize processes for most of the bank’s back-office teams. Building on these positive experiences, we won the tender for the voice-assistant project. To deliver the outcomes MONETA was looking for, we engaged Feedyou as a technology partner to implement the project.
As part of the project requirements, NTT and Feedyou defined scenarios for the most common customer calls and requests. These scenarios focused mainly on services related to unblocking internet banking, resetting forgotten passwords, adjusting limits for online payments, and other routine requests that could be fully automated.
During the implementation phase we integrated several advanced technologies, including speech recognition and speech-to-text conversion, text content evaluation, and subsequent text-to-speech conversion to the voicebot’s synthesized voice output.
The foundation of the entire solution is MONETA Money Bank’s Genesys contact center platform, which also supports call monitoring and evaluation. Genesys Voice Platform (GVP) IVR technologies were expanded to include the voicebot functionality. The realistic call experience is further enhanced by leveraging the advanced services of the Microsoft Azure cloud platform. From the available synthesized human speech models, MONETA Money Bank chose a male voice and named their voice assistant “Tom”.
With the deployment of Tom, customers no longer wait for a connection to the operator. Tom picks up all calls to the MONETA Money Bank call center, greets the customer with a prepared set of messages and listens to their request. Several key processes run in real time in the background: the customer’s voice input is converted to text via Google’s speech recognition technology and is then analyzed in the NLP model of the Feedyou Platform. Here, based on keyword analysis, the customer’s intent is detected.
The system then decides whether the request can be resolved with the prepared scenarios or whether the customer needs to be redirected to a human operator.
Tom guides the customer through the identity verification process, using the Smart Banka mobile banking app or data capturing customer information, which is verified against the bank’s databases. If the request can’t be resolved by the defined scenarios, Tom will direct the call to the appropriate operator, based on the identified topic.
Today, Tom independently manages to resolve approximately a quarter of customer calls. He operates based on prepared scripts and integrates with the bank’s internal systems. This significantly reduces the handling time of common requests and multiplies the call center’s capacity.
NTT handles the complete orchestration of all involved systems and reports on key traffic indicators such as the number of calls answered, the success rate of request recognition and further routing, the proportion of calls resolved by the voicebot, and the system’s workload and response time.
The implementation of the first version of the voice assistant in the MONETA Money Bank call center took place in record time. Just a few weeks after finalizing the assignments and scenarios of common requests, Tom was ready to start handling the first calls from customers in a pilot operation.
“This has significantly reduced the number of routine queries directed to operators and has expedited the handling of our customers’ calls. The deployment of the voicebot has proven to be highly effective and, as a result, we are expanding Tom’s capabilities with new scenarios for typical client requests.”
Results
Tom the voice assistant: indistinguishable from a human call center operator
The deployment of a voice assistant in the MONETA Money Bank call center has multiplied the bank’s capacity for handling customer calls and dramatically reduced the time needed to handle customer requests. The voicebot solution is provided as a fully managed service with guaranteed availability parameters and the ability to identify customer requests based on the analysis of voice input.
Increased customer satisfaction
Today, Tom handles 25% of customer calls at MONETA Money Bank’s call center. During a naturally conducted conversation, Tom identifies the customer’s wishes and verifies their identity. In the initial stage of the call, the customer does not wait for a transfer. If their request falls within the voicebot’s scenarios, it is promptly processed after identity verification. The resolution of other requests is also faster, as the customer is directed to the appropriate operator. Throughout the call, the customer experiences no difference from a conversation with a human operator. During the initial 3-month pilot:
- 43% of inbound calls were actioned by Tom with 47% transferred to agents
- 42% of self-service requests were handled entirely by Tom
- 37% customers were fully verified by Tom
Increased operator motivation
Thanks to the deployment of the voicebot, MONETA Money Bank call center operators do not have to deal with routine and repetitive requests. Instead, they can focus on solving customer issues that align with their specialization. As a result, operators are more satisfied with their work, leading to reduced turnover. Automated handling of routine requests saved operators 471 hours during the 3 month proof of concept. This allowed them to dedicate more time to handling sophisticated inquiries and providing new services to customers.
Cost savings and efficiency gains
The costs of deploying and operating the voicebot are significantly lower than expanding call center capacity with additional operators to handle a similar volume of customer calls within the same timeframe. Moreover, the voicebot service is relatively easy to scale up to a larger number of parallel calls if needed.
The voicebot project has met all the requirements and evaluation parameters set by MONETA Money Bank.
As a result, the development of additional call scenarios that the voice assistant can automatically handle is already under way. The content recognition technology used in the voice communication will also be leveraged for the deployment of a chatbot service for customer who prefer text-based communication.