Today’s customers demand that every experience provide immediate value on multiple levels. They require a competitive, friendly, quick and personalized user experience. They swear allegiance to no brand and are ready to jump ship to the first competitor that can offer them what they want, when they need it, and at the level of service they feel they deserve. Grant Thorton discuss the what this means in practical terms.

Tech giants, such as Amazon or Netflix, have set the bar high for intuitive personalized user experiences. Many industries, including financial services, are rethinking their own customer service approach to match this new standard and meet the expectations of modern consumers.

It is increasingly evident that the future success or failure of financial services institutions will hinge on their ability to provide personalized user experiences. Institutions must seize the rich customer data that they already possess in order to optimize customer experience and differentiate from their competition. To achieve this outcome, they must shift their mindset, from one focused on what they want to offer to the customer to one that prioritizes what creates immediate value for the customer. In addition, they must be willing to allocate the necessary resources to drive this goal. To this purpose, they can use artificial intelligence (AI) to achieve brand differentiation.

We recently explored issues and opportunities related to customer experience in a joint webinar with Finovate – Data overload? The impact of AI on the customer experience – moderated by David Head, managing director, Grant Thornton, with panelists Carrie Russell, executive strategic advisor, Finn.ai; Tariq Bakhari, CEO, Aggresant, Inc.; Dave Brodsky, VP digital innovation, Wells Fargo; and Katy Gibson, vice president of product applications, Envestnet | Yodlee.

Webinar panelists discussed various ways in which AI can help financial institutions solve their differentiation-through-customer-experience challenge. While currently AI is still in its infancy, the technology has the potential to transform customer experience by enhancing the interaction with the customer, rather than replacing humans with bots.

Paving the way for AI, many banks have implemented machine learning (ML) and natural language processing (NLP), primarily in their back office, to reduce labor costs and increase productivity. In the near future, AI can revolutionize retail banking and other financial service offerings by becoming an omnipotent artificial brain behind the scenes to improve customer interaction and increase personalization.

Here are several insights from the webinar, regarding applications of AI (and of other related technologies) that can create immediate value for the customer:

1. Simplify processes. 
   Allow customers to execute simple transactions through user-friendly tools that leverage their data. In this way, they will see how access to their data creates direct, personal value.
2. Offer customers personalization and optimization of their experience based on live data. 
   AI can replace annoying surveys through real-time data mining and by interacting with customers in real time, eliminating the need for the survey feedback loop. As a transformative technology, AI empowers automated financial assistants that provide updated, real-time customer interactions.
3. Offer recommendations to motivate financial customer behavior.
   Savvy financial services institutions can partner with fintech companies to establish trusted relationships and create a financial wellness experience for their customers. This includes using customer data to help them achieve their short- and long-term goals. Institutions can create tools to help customers: 1) keep on top of day-to-day finances to answer immediate questions quickly (e.g. a financial calendar that can keep track of a customer’s account balance until payday and send bill payment reminders, etc.); and 2) think through long-term financial planning.
4. Use AI or related technologies (e.g. ML, NLP) to enhance rather than replace human interaction.
   AI can enhance the customer experience even when it is not customer facing. For example, call centers can follow 2 paths for interaction with customers: 1) they can be fully automated and chatbots can simply answer calls; or 2) they can use a mix of human and artificial intelligence, where chatbots can aid human call center representatives interact with customers effectively. So far, the second has proved more effective than the first.Turnover and training are well known challenges for call centers. Customers can feel dissatisfied with a call center representative that does not have an answer to their query; the representative can feel that, despite his best effort, he does not have access to the right information to answer the query. AI can help with this issue, not necessarily by replacing representatives and human interaction, but rather by facilitating speed and access to information to help representatives create an outstanding customer experience. This can be particularly effective with new hires that have to get up to speed fast.
5. Get the right channel. Go where the customer is likely to be.
   Customers expect personal experiences that make their lives easier. For example, customers spend most of their time on their cell phones and have started using virtual voice-enable assistance more and more. Financial institutions need to meet the customers where they are to offer convenience and ease of use. This insight should guide investment in new tools. Conversational assistants/virtual assistants can be used for day-to-day transactions and allow customers to explore additional products and services, policies and other information.
6. Think through infrastructure challenges that limit the customer experience.
   When planning investments in AI tools, financial institutions need to think proactively about current infrastructure challenges and future infrastructure advances. Delivering differentiation through technology depends on the capacity of the technological infrastructure to support the tool. At the high end of the technology infrastructure spectrum, 5G capabilities may enable the Internet of things (IoT) new data sources. Are banks/financial institutions prepared to collect and leverage this new data? At the low end, many US citizens barely connect to broadband because of the areas in which they live. Are they untapped customers? What tools/channels work for them, as they are dependent on the limited availability of infrastructure now and in the future?

Financial services institutions are in an excellent position to build a solid technological foundation that will make use of new customer data in meaningful ways. At this critical point, the question remains how to evaluate and select the appropriate tools and how to find a manageable pace of adoption.