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Financial Services

Implementing Chatbots in Financial Services

Previously, I discussed chatbot technology in the financial services industry. This post outlines the benefits of implementing chatbots to enhance the customer experience.

Many firms begin their foray into chatbot technology by replacing or augmenting internal service desks. Functions such as information security password resets, IT software installation requests, and HR inquiries are typically the first to use chatbots as the dialogs are simpler and more limited in scope, with a small number of backend systems with which to transact. These firms then turn to deployment in more complex, external-facing capacities, such as customer service, to reduce the number of calls requiring a human agent, thus reducing cost. However, if chatbots are not properly implemented or trained, customers can get easily frustrated as their requests are repeatedly misinterpreted.

In order to maximize the benefit of a chatbot implementation, the range of typical customer dialogs must be compiled and documented, a complete dictionary of industry and company specific terms assembled, and the corresponding back-end systems and transactions identified. Personnel experienced with chatbots need to properly train the AI engines for the phraseology and synonyms, as this critical function is as much art as it is science.

Sentiment engines should be leveraged, such that if a customer is getting agitated, the call is immediately transferred to a human representative who can process the request. In a similar manner, if the customer is deemed to be highly satisfied, the call might be transferred to a representative where additional products or services can be offered.

It should be noted that research has shown that different demographic groups prefer to receive customer service through different channels. For example, millennials tend to prefer texting, while retirees prefer to speak with a human. When properly integrated with a company’s contact center platform, calls and texts can be directed to the appropriate chatbot or individual based on the person’s demographic, call history, product portfolio, or status.

Direct customer-facing chatbot deployments are not the only option. The technology can be used by human customer service representatives to provide expert guidance or as an accelerator in accessing required transactional systems. For example, chatbots can “listen in” to a customer service conversation from the representative’s side, never visible to the customer. Chatbots can guide the representative in addressing the customer’s issue, accelerating the session by accessing the company’s various transactional systems to provide the required information, or impart the updates necessary. With the aid of the “expert” chatbot guide, the duration of the call can be shortened, allowing more calls per representative, thus reducing expense.

With less wait time and a superior service experience, customers are more likely to be receptive to suggestions for additional products and services. Here again, chatbots can function as a guide, using ML to suggest offerings that are likely to appeal to the customer. With full access to a customer’ transaction history, demographics, account profile, and product set, the AI-enabled chatbot can make recommendations in real-time, without delaying the call.

To learn more about the trends and capabilities in AI chatbots, options for integrating them into client service workflows, and how they can reduce expenses and increase revenue in the process you can download our guide here, or click the link below.

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David Willner

David Willner is a business-focused information technology executive in Perficient’s financial services practice. His specialty is in transformation and data strategy programs. Before Perficient, he served as a managing director at J.P. Morgan Chase, senior managing director and chief development officer at Bear Stearns, and chief information officer, corporate comptrollers, at AIG. When he is not improving our client’s operations, systems, and data, he can be found playing guitar in his blues/rock band.

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