Why do Neobanks & Insurtech need #digitalempathy for a long-time customer engagement?

Nov 21, 2018 · 3 min read

Neobanks, other fintech companies (payments, roboadvisors, lending, etc) and Insurtech are becoming more and more relevant and increasing marketshare versus traditional players. As well, the traditional players and incumbents in finance and insurance fields are launching their own “only-digital” initiatives.

The list of new players is increasing quickly.

Chart courtesy of @arifsddq

One of the key advantadges of the new players is how easy the “onboarding” procedure is and how their digital channels (web, app, chatbots) are extremely well designed, #CX matters :-)

The other side of the coin is that it is as easy to belong as to move to another equivalent player. Neobanks and Insurtech may use a brand-fan strategy creating long-life loyalty but it is not easy at all. Not every company can expect to succeed as Apple and making all their “services” iconic.

With the raise of AI the “human factor” is being unfairly underated. Before big data, and even before of IT itself, the knowledge about the customers (not their accounts that were paper stored) was kept in the minds of local bank clerks or insurante agents.

That combination of instinct and knowledge of the client became empathy and personalization of customer service by the employee who served the client and that empathy and “feeling understood” sentiment became customer loyalty and long-time engagement. The engagement needs some perception of the customer about not being seen just as a commercial target.

The real challenge for pure-digital players as neobanks and insurtech companies is how to create digitaly a human-alike empathy and use it through their digital channels (especially the conversational ones as chatbots) to create “long-time engagement”, becoming an effective barrier preventing the churn.

The most intensive cases till now for Artificial Intelligence and machine learning are related to proccess business intelligence to provide recommendation patterns and the NLP for conversational channels as chatbots. Both AI topics are key and customer language needs to be understood to provide effective communication and recommendation is key for upselling new service and products but the missing point is still the needed empathy for long-time engagement.

How could AI based #digitalempathy be generated? Well, Anbotux is trying to pioneer this field. How? We just combined customer-segmentation, customer-journey accesses (from all channels but with more detailed level for chatbots) and a new way of modelling external events to understand reactivities to external events and apply that knowledge to personalize the conversations.

Neobanks and insurtech companies are startups (most of them), agile companies, they are using a limited number of channels (mainly a combination of web, app and virtual assistants or just one of them), have agile methodology to add new tech layers and features, they are cloud based and part of the API economy companies and customed to deal with remote teams.

It is easy for them to integrate Anbotux using the API to start collecting that “customer-minset” knowledge, convert it into #digitalempathy and evaluate how external events can impact or not in their customer base behaviorals.

Let’s work together :-)

Also you can follow us: @anbotux and linkedin


Customer Mindset Analytics & AI based #digitalempathy rules…

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