Artificial Intelligence (AI) has infiltrated our everyday lives, from digital assistants to facial recognition whether you notice it or not. More than 2,000 AI startups in 70 countries have raised more than $27 billion according to Venture Scanner. When it comes to the adoption of AI, the financial services industry is leading the way. This is particularly evident in how it fosters improved operational efficiency and data analytics as well as enhanced client services and cost reductions. Financial institutions have significant advantage over potential new entrants because they can leverage their huge internal data sets. FinTech startups on the other hand, have the technology but often lack the data sets required. In this case study we focus on how chatbots can automate operations, reach more customers and streamline digital services for financial institutions.
We have asked our Startupbootcamp FinTech alumni Enterprise Bot, an AI based plug and play chatbot powered by Natural Language Processing to share their experience in integrating with AfterPay, the pay-after-delivery solution (a Bertelsmann Group company). Using input from Google Analytics, AfterPay constantly expands the chatbot’s range of answers. Entering a hint or a brief summary is enough for a full response.
Find out more from Ravina Mutha, Co-Founder of Enterprise Bot and Freija Brouwer, Senior Product Manager at AfterPay.
Ravina Mutha, Enterprise Bot: How did you meet the AfterPay team and start the discussions for collaboration?
We were introduced to the AfterPay team through Lennart Swoboda from Arvato Bertelsmann, a program partner at Startupbootcamp FinTech.
Freija Brouwer, AfterPay: Are you continuously looking into new FinTech solutions to keep up to speed with innovation?
Yes, we are continuously working with new technology to keep our leading position in the FinTech market.
Ravina Mutha, Enterprise Bot: How does AfterPay benefit from your Chatbot?
Our chatbot should help to bring significant benefit to both AfterPay and its clients. Through ‘Sofie’, we have already been able to reply to more than one in every five queries directed to the AfterPay contact centre, with an average response time of less than two seconds. Based on these results we are confident in delivering significant cost benefits and customer satisfaction increase for AfterPay.
Freija Brouwer, AfterPay: What part of your business processes does the Chatbot have the biggest impact on?
Sofie, our digital assistant is really appreciated and embedded in our Customer Care department. We can service our customers 24/7 now.
Ravina Mutha, Enterprise Bot: How long was the process from negotiation up to the launch of the product? Were there any complications during the integration process? If yes, how did you overcome them?
It took us approximately six months from negotiation until the launch of the bot. The first challenge for us was the negotiation and proving to AfterPay that our solution would be a good fit. As we were at a very early stage at that point, we needed to build trust and prove ourselves to AfterPay. Fortunately for us, AfterPay took a leap of faith based on our technology and the journey that followed was much simpler. We started work on the bot in March and were able to go live in August.
Ravina Mutha, Enterprise Bot: Given your experience in selling to corporates, what’s the advice you would give to other startups?
B2B sales always takes longer than you expect, but once the deal is closed, it is even more important to be able to set reasonable timelines and successfully deliver the project. It is very important to understand exactly what business problem your product/service solves and to cater your value proposition accordingly.
Freija Brouwer, AfterPay: Will Enterprise Bot replace call centre agents?
Our goal is not to replace call centre agents with a chatbot/virtual assistant. We want to add longer opening hours and be able to respond to the most frequent routine questions. This gives our customer care employees the opportunity to focus on the difficult questions. We don’t put emphasis on time per call but on the quality of the conversation. We hope our consumers will use our payment method more than once.
Numbers in August proved that Sofie was able to handle 23% of all our incoming requests with an accuracy of >85% before handing it over to a real agent. As stated before our Customer Care team is very happy with the fact that they can concentrate on the really difficult questions.
Freija Brouwer, AfterPay: What is your recommendation for technology companies? How do they bypass long sales cycles when selling to corporates and get right into the client’s mind?
First, they must understand the needs of the corporate and how their technology can help, not only in saving money/employees but also gain quality. It would help if they show some real case examples on how the product can be used, or offer a free Proof of Concept.
Enterprise Bot’s other clients include the SIX Group (Swiss Stock Exchange), Generali Switzerland, Lings (Innovative Insurance company) and PwC Switzerland. At the moment, four clients are in PoC stage with projects in Switzerland, the Netherlands and the UK. Enterprise Bot projects cover NLP capabilities in English, German, French, Italian, Dutch and Spanish. If you want to find out more about Enterprise Bot visit the website.
Colab’s next theme is Artificial Intelligence. We are looking for AI solutions that can help financial institutions to detect fraud, profile customers, spot the patterns, streamline low-value processes, assess credit worthiness and save money.
Colab’s reach is global. We are looking for companies who have minimally raised between Seed and Series A, and/or companies who have a solution ready to go to Proof of Concept (PoC) with financial institutions.
If you fit the criteria or know a FinTech company who does, get in touch with us to learn more about how you can participate in the Colab program on email@example.com
Want to hear more about how AI is transforming Financial Services ecosystem? Join us on 27th September in London for our thought leadership panel on the advantages of implementing AI into Financial Institutions.