How AI Is Changing Retail Banking
BlogBusiness + ManagementFinancial ServicesBusinessposted by Mark van Rijmenam September 4, 2017 Mark van Rijmenam
With technological advancement, artificial intelligence is set to touch and modify the financial sector, specifically retail banking in many different ways. It’s still the beginning stages of AI adoption for most banks. A Narrative Science survey highlighted that 32 percent of financial executive participants utilize AI technology, such as voice recognition and predictive analytics. Moreover, an Accenture survey noted that 76 percent those surveyed believe most banks will use AI interfaces primarily for customer interaction by 2020. But AI is changing retail banking in more ways than one. Here’s how:
Automated Services via RPA
IT costs are a pain point of retail banking, as they can account for as much as 10 to 15 percent of a bank’s total annual expenditures. While some of these costs are attributable to improving security or enhancing services, maintaining legacy systems account for 70 percent of banks’ IT expenses. However, AI offers an opportunity for reducing these costs via automated services. For example, robotics process automation (RPA) enables you to create a platform that is automated to support functions in various departments, such as front-line operational support for new account entry or back office support for writing off bad debt. An Accenture report notes that RPA can help reduce costs by up to 80 percent. Moreover, incorporating RPA into your artificial intelligence strategy helps improve processes by enhancing agility, performance, and productivity. For example, RPA’s seamless integration with your infrastructure makes it easier to automatically process credit card orders faster with accuracy and transfer data from web format to your mainframe. This enhanced process can reduce the time for performing tasks by 90 percent, which can lead to a better customer experience.
Enhanced Customer Experience via Conversational Commerce Powered by Chatbots
Keeping up with the demands of customer service in retail banking has long been an issue for many banks. Human resources are limited to how much time banking customer service representatives can physically work handling customer issues. Also, not being able to get a response right away when needed can curtail the customer’s experience. In fact, an FIS survey revealed that only 23 percent of retail banking customers from nine countries were satisfied with their banks and noted the lack of personalized banking as a pain point for customers.
However, chatbots offer a solution for addressing customer service issues. Thanks to automation powered by this form of AI, retail banking customers can receive answers to questions immediately and help with making sound financial decisions. For example, Bank of America’s chatbot digital assistant Erica helps the bank’s customers make better financial decisions by offering financial advice based on the customer’s banking habits using cognitive messaging, artificial intelligence and predictive analytics. The bot can suggest what the customer can save to reach a specified financial goal, such as saving $100 towards paying down a credit card. The bot also provides suggestions using predictive analytics to determine the spending and saving habits of the retail banking consumer. Banking customers can also use the bot via text messaging or a mobile app to ask questions and receive financial advice.
While chatbots are helpful for enhancing the customer experience, they can also be used in retail banking to recognize emotions so that they can use a preferred response that is sensitive to the customer’s needs while taking the recognized emotion into consideration before responding. This helps customers receive a more personalized experience. It’s still important to note that chatbots have an accuracy rate of only 85 percent; thus, it’s vital to consider specific situations and anticipate questions and responses for better accuracy rates and an improved customer experience.
Improved User Interfaces With Advanced Machine Learning
Simple navigation for online banking apps and mobile banking apps is an important strategy for retail banks to take as it helps to enhance the customer experience. AI helps to deliver simplified user interfaces that retail banking customers can navigate with ease. Customers will be able to get to the pages they need to quickly. Responsive design and other UI tactics can help make online site content adapt to the device the customer is using at the time for easy navigation. For example, advanced machine learning can be used to simplify the process of uploading documents and loan application approvals by accurately extrapolating information from documents customers upload from their mobile devices using their built-in cameras.
It’s hard to look past how AI is changing the retail banking landscape without discussing its impact on the roles of retail banking workers. The adverse impacts of AI’s integration into modern society have focused on how it can possibly automate jobs, with numerous projections, including automation of 47 percent of U.S. jobs by 2025, 850,000 U.K. jobs by 2030, and nearly half of all occupations globally by 2055. It’s being translated to retail banking with the introduction of chatbots and assisted automated tellers that can help process loans or open accounts and answer questions faster and cheaper than human workers. Moreover, AI is projected to replace 30 percent of jobs in the banking sector within 5-10 years.
However, AI also offers an opportunity for the transformation of roles in retail banking. A report by McKinsey notes the potential for automating roles and tasks that require knowledge and creativity (such as managing, planning, people development and decision making) is lower than the potential for automating jobs that require processing and collecting data, such as verification of financial data. That means that an area of opportunity lies in preparing your bank tellers and other personnel whose jobs have a higher potential for being automated for knowledge-based roles. This can be accomplished via training, mentoring, leadership opportunities and intrapreneurial opportunities.
AI’s fast development is bound to have a significant impact on the retail banking industry. From RPA to chatbots, AI will change how customers interact and how retail banks will conduct business. An investment in AI will be crucial to setting your banking enterprise apart from your competitors. It’s also vital to prepare your staff for these changes by presenting them with career and training opportunities that help them develop the skills and knowledge they need to transition to roles that leverage AI.