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Quick as a fox, Solvemate was an ideal solution for Berliner Sparkasse. Now, with machine learning, the bank solves common customer requests around the clock in less than 14 seconds.
Serves almost 1.5 million customers
7,000 handled requests per month
14 seconds average response time
Berliner Sparkasse is a bank with a long history: Founded in 1818, it has been providing financial services to the German capital for two centuries.
It also goes with the times: With its best-in-class mobile offering and video consulting services, Berliner Sparkasse has been defining what it means to be a bank in the digital age.
In 2017, Berliner Sparkasse started using Solvemate to offer its customers a new digital touch point—and eliminate waiting times for its customers.
Daniela Gommert
With almost two million private and business customers as well as 1.3 million accounts, Berliner Sparkasse faces a support volume of 70,000 calls per month.
Berliner Sparkasse’s Innovation Department was tasked with providing better customer service while increasing operational efficiency. They were intrigued by Solvemate as its technology could help them reach both targets at once.
Solvemate’s structured questions approach combined with its powerful machine learning capabilities were the decisive factors. Solvemate demonstrated that answering structured questions is much faster and more accurate than having customers formulate and type out their own requests.
Daniela Gommert
In a joint workshop, Solvemate and Berliner Sparkasse’s support team compiled the 40 most popular requests and the best answers for each of them. With this knowledge, the chatbot could immediately go live.
The support team now regularly adds new requests and answers, whenever they notice gaps in the knowledge base. The team has learned what their customers are asking and which answers perform best.
Joachim Wangnet
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