The current state of chatbot development offers banks an enigma and an opportunity.

Chatbots are clearly state-of-the-art customer service technology. However, they are also next generation technology with growing pains. Like other retailers, banks are contemplating embarking on projects using these technologies.

Is it smarter to be one of the first to adopt and invest in voicebots/chatbots with their current limitations, or to wait until the technology has evolved and risk being left behind by competitors?

The answer depends on the agility of your technological environment and customer service needs. At Alloxentric, we believe banks could be wise to invest now, “by preparing for the best robots to come – and ultimately provide a fully automated yet high quality customer experience”. Current technology allows for a rapid learning curve and its impact on the efficiency of certain operations is so great that there is no point in waiting any longer.

 

Recommendations to minimize risks and expand opportunities

Regardless of a bank’s decision to use bots or not, there are three key factors that will allow them to take advantage of opportunities and minimize risks.

1. Decide which voicebot/chatbot application is best for your situation.

Chatbots can fit into many modes of customer engagement, including social media, mobile applications, instant messaging, text or voice. Bot technology can enhance a bank’s consumer touch points. However, it makes sense to find the engagement platform that best suits your customer’s life cycle. For example, some customer segments will prefer voice bots for collections, others will prefer WhatsApp.

In addition, you need to design the point of contact that best suits your use case. What is your optimal distribution strategy? It may be wise to focus on something specific, such as collections or designing a financial concierge bot.

Finally consider restricted application areas while expanding the potential universe of use cases, both the bot and its customers as well as the organisation have to learn from this process.

2. Be prepared to update technology and processes.

It may be necessary to add new procedures or redesign existing processes to better support new electronic assistants, whether they are voicebots or chatbots. Bank staff may also need training to interact effectively with new mobile tools for customer engagement. An optimised user experience will require natural language processing and the data intelligence to support it.

In addition to understanding the vocabulary and intent of consumer questions, backend data models must provide the correct answers for use cases implemented via bot. This is where data intelligence is key. By adopting state-of-the-art data intelligence solutions, banks will be able to offer users a personalised chatbot experience through intuitive answers to the most frequently asked personal financial questions.

Bots offer the illusion of simplicity for the customer. However, a lot of complexity is used to create this great customer experience. At Alloxentric we integrated an RPA into our solution, but we have had experiences where the Bank already had another RPA but with an inadequate implementation.

Users will be impressed by the way the chatbot can model different financial scenarios based on their personalised information. A chatbot could even congratulate the user for getting a new job to further customize the experience (for example). Through the use of machine learning and data intelligence, the chatbot is able to identify that the direct deposit was from a new employer, and that the user had stopped receiving deposits from their old employer.

The tool can remind users that a new job is a good time to review and optimise their VCT or investment allocations. The Bank can give the option of connecting with a financial advisor or account executive to discuss options, promoting the customer’s financial well-being and cross-selling additional products and services that benefit the user.

The challenge of a conversational text interface is that it puts a blank text box in front of the consumer. This is why at Alloxentric we have gone much further and interact with the client through all media or channels. Voice, web bots, virtual phone assistants, SMS messaging or WhatsApp are all part of the same experience of communicating with the institution.

We have seen that customers are less constrained than computers and can ask questions that are beyond the response capacity of the application, but today we handle a huge amount of cases that grows every day by learning in about 300,000 conversations per month at the time of writing this document.

We are always thinking and redefining the scripts and logic of the existing system. We handle bots with an unambiguous vocabulary and with the expected questions that lead to obvious answers.

3. Understanding that context is key to the chatbot experience.

“Context” refers to everything that makes the client feel that they are having a personal interaction with someone who knows them. Such customer information includes account information, past behavior, current location, environmental factors, recent transactions, and user preferences. The more consumer data available to a chatbot, the more effective the interaction and service will be.

Data intelligence and personalization are key. And we have already integrated all experience supporting institutions with issues ranging from collection (by voice or text) to service bots and many other applications.

Licencia Creative Commons This content is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license.

Max Kreimerman

Author Max Kreimerman

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