Today Matthias Pfeifer talks to Sophie about the first chatbot at WIR Bank. In this podcast episode, you can find out about the bank’s experience with the bot, how the first use case was defined and what surprised those involved.

About Matthias Pfeifer

Matthias Pfeifer is Head of Sales and Member of the Executive Board at WIR Bank. The bank is built on three pillars. In addition to traditional topics relating to financing, payments and pensions, the bank has built up its own network of SMEs with its own currency, the WIR. The third pillar is close cooperation with FinTechs.

First Touchpoint

During his extra-occupational Master’s degree, Matthias took a closer look at the topic of chatbots for the first time. The students had the opportunity to spend a day programming a chatbot themselves, he reports enthusiastically. It was precisely this enthusiasm that he took with him when he moved from UBS to WIR Bank a year and a half ago. The only thing missing was an initial small concept and, of course, a use case.

The focus is on the customer’s benefit

Based on this motto, Matthias and his colleagues set out to find out where a chatbot could increase customer benefits and at the same time promote digital transformation within the bank. They found what they were looking for in a use case for their SME network. When an order is processed there, part of it is paid in WIR and part in Swiss francs. The WIR money can then be used to buy something from the other SMEs in the network. A total of 30 customer advisors are available to the 30,000 companies in the network. And this is precisely where the problem lies, reports Matthias, because there are simply not enough of them.

The chatbot supports customers and takes them by the hand by showing them what they can use their WE for. WIR Bank relies on a rule-based bot. This means that the bot does not understand any free text input from the user. Instead, users click through the bot, which tries to find out what users want by asking clever questions. Once it has been established that the user is looking for a watch, for example, they can enter their favorite brand in a field at the end of the journey and the chatbot spits out a link to a company in the network that offers precisely this brand. The chatbot is then no longer active on the platform itself, where a dedicated search engine helps the user to select the right model.

Refining systematic advice with the help of the bot

Matthias is particularly proud of the chatbot’s systematic approach to advising customers. To this end, the ways in which the WIR currency can be used were divided into four areas and then refined further and further. As a result, even the experienced customer advisors were able to learn something new and further refine and systematize their advice in order to provide customers with the best possible advice. “Every customer advisor has their own focus and their own network that they can use when providing advice,” explains Matthias Pfeifer. The chatbot helps to broaden your own horizons and brings a new systematic approach to consulting.

Although the chatbot is intended for external customers and not for internal employees, WIR Bank sees further potential for a future use case here thanks to the learning effect for internal customer advisors. A bot that is used for knowledge transfer, for example for training in a specific subject area in consulting, would be conceivable.

A different way of finding a name

WIR Bank took a very unconventional approach to naming the chatbot, especially when you consider that it is a bank that is known for its conservative approach. With the help of Sophie, a survey was launched on LinkedIn in which more than 50 name suggestions were received, one of which was ultimately selected. The entire process took just a few days and did not involve any lengthy approval processes within the bank.

And how does he speak?

As the chatbot at WIR Bank is a prototype, the personality is not yet as pronounced as it is with other bots, but has a more pragmatic design, reports Matthias. For WIR Bank, which is itself an SME, it is important to communicate with its customers directly and at eye level. This fact has of course also been incorporated into the personality of the bot. So it’s not surprising that the chatbot addresses users as “Du” instead of “Sie”. We have a lot of tradespeople and construction customers, so the ice is often broken quickly and we quickly get to know each other anyway,” says Matthias. WIR Bank has also opted for a younger approach to customers in order to take account of the chatbot as an innovative digital communication channel. We want to communicate with our chatbot in the same way as we do in a personal business relationship, says Matthias Pfeifer.

Next Step’s

Over time, WIR Bank has realized that different target groups are using the bot than originally intended. This is certainly also due to the fact that the chatbot is placed on the homepage of the website and thus attracts the attention of all customer segments, regardless of whether they want to make provisions, save or use their WIR currency. For this reason, the bank would like to test the chatbot in various other places on the company website over the next few months and learn more about the actual target group, namely people who want to use their WIR currency. The experience gained will then be used to review the entire chatbot concept and adapt it if necessary. Actually, there’s no end in sight, the whole thing is an iterative process, Matthias says and laughs.

Learnings

1. puts the customer’s benefit at the center of the search for a suitable use case.

2 A chatbot can trigger unexpected side effects. In this article, for example, by teaching customer advisors a new system for providing advice.

3. take an unconventional approach to the project and, for example, start a survey on LinkedIn to find a name for the chatbot.

4. there is no end to a chatbot project, it is an iterative process.

It’s best to listen to the podcast episode with Sophie Hundertmark and Matthias Pfeifer for yourself. Have fun!

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