Financial services companies are faced with significant challenges to provide a good CX, largely due to the huge volume of inquiries they receive, the wide breadth of products and services they provide, and the relatively limited number of human agents that can handle these inquiries. As a result, many institutions have turned to automated systems and intelligent chatbots to augment their human call center staff.
These automated systems provide significantly more functionality and user friendliness than the interactive voice response (IVR), decision-tree systems of the past. In fact, most enterprise-grade solutions lean heavily on artificial intelligence (AI) technology, and can hold audio or text-based conversations that convincingly simulate how a human would interact. Deep learning (DL) algorithms are used to learn the appropriate answers to questions and to learn how to understand variations in speech, sentence structure, syntax, accents, and terminology used by customers.
While financial services firms had deployed these AI-enabled chatbots and assistants prior to the COVID-19 pandemic, the rapid shutdowns that kept workers and customers home accelerated their use, according to independent advisory firm Strategic Resource Management, which commissioned a consumer survey late in 2020 to analyze changes in banking habits due to the impact of COVID-19. Two key findings from the survey, which was conducted among 2,045 US adults in October 2020, focused on how consumers were interacting with the digital technology and their financial institutions:
- Consumers’ use of digital banking functions is plateauing, but the use of virtual assistants within the home is on the rise. According to the survey, 66% of respondents (77% of those ages 18 to 34, 40% for 55+) used a virtual assistant during the pandemic, with the most common tasks including listening to music, setting timers or alarms, looking up information, and calling friends and family. The age group with the greatest appetite for using virtual assistants was older millennials, ages 35 to 44.
- There is a growing appetite for basic banking capabilities using AI channels. Based on the survey, of those who use virtual assistants, 11% are already using them for banking, slightly higher than the 10% of those who are now using AI-enabled thermostats. When respondents were asked about whether they would use virtual assistants for banking, 25% said they would, but pointed to greater comfort with basic functional transactions, such as checking account balances or requesting appointments, rather than with interactive transactions, such as initiating a loan or seeking out financial advice.
From an operational perspective, financial institutions have a lot to gain by deploying AI-driven assistants. Institutions can deploy these assistants to handle routine tasks that do not require a human to complete, such as account management functions, allowing human staff to focus on higher-value tasks. During the pandemic, virtual assistant provider Interactions added password reset and username retrieval experience to a major US credit union’s mobile application, and in just one month, 15,876 minutes of calls were removed from the credit union’s contact center by containing and completing these transactions within the interactive voice assistant. This translated to a 10% to 50% reduction in the number of calls, as well as shortening live chat sessions on an average of one minute.
CX can also be improved by deploying these assistants, as they can be served immediately, rather than customers having to wait on hold. These assistants are automated and fulfilled completely in the digital realm, so there can be an immediate confirmation of any changes that are made, assuring the customer that the task has been accomplished. Finally, customers are often wary of contacting their financial institution via phone, fearing they will inadvertently be put into a sales funnel by a human agent. By deploying a virtual digital assistant (along with a robust customer data platform or customer relationship management (CRM) system), any upselling or cross-selling can be initiated after the task has been completed, and can be linked to specific customer activities, rather than a generic, scripted offer.
Author Information
Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
