Why Banks Need to Embrace AI-First Customer Service

Published On : 06/04/2021

By Jessica Gopalakrishnan, Senior Director, Cognigy

The next wave of automation in banking has been brewing for several years and COVID-19 has accelerated the focus in many areas, particularly in AI, e-identity, contactless payments, RPA and conversational solutions. Deloitte suggests the post-pandemic bank will emerge as a much different one, with greater attention on the digitization of operations and customer service automation.

The case for AI automation technologies for customer service is a strong one: improved productivity, customer satisfaction and cost savings. However, many banking decisions and processes can still be slow and manual. Complex layers impact turnaround times for core procedures from credit checks to employment verification. Mortgage and lending processes, for example, can take up to two months. Manual processing can create such delays, lead to error rates as high as 30%, and increase rework volumes due to employee fatigue and poor training.

While the value of customer service automation may be understood, and most are likely working towards implementing automation in some capacity, competition is fiercely heating up and customers are hot on the hunt for better options and better experiences. In many ways, an automation-first approach—one where automation handles all contact initially—may be the only way to drive customer service forward.

Looking at customer service differently

Banking contact centers and customer service teams face unprecedented, heightened consumer expectations. Not only do consumers today want the best rates from their banks, but they demand excellent service as well—meaning quick resolutions with 24/7 availability across all possible communication channels. Human labor and human management related challenges can be aided through automation, which is why businesses are looking at different ways to bring automation to the contact center and customer service processes.

This means automating the back and forth for both electronic and document-centric processes and then providing a customer facing interface to these processes. If a customer wants to apply for a loan, for example, they should be able to start the process online and then get status updates and information requests through their channel of choice. Traditionally, this is either done by calling in repeatedly or sending emails back and forth with whomever is helping with a loan, resulting in unnecessary manual effort that creates delays in responding to customers.

By automating the experience, the process can be accomplished through self-service. With conversational AI, customers are able to communicate through text or voice channels and interact with chatbots or voice bots using natural language. Instead of pressing a number to get to an operator, customers can simply ask for what they want and get assistance with what they need immediately without waiting on hold.

Dialogues with customers on any channel in an assisted, automated way also create a joint benefit of freeing up time for human agents, reducing the time they spend on basic status updates or requests for information.

Competing for customers beyond digital transformation

Newer banks entering the marketplace are providing innovative, self-service options as well as a myriad of other attractive features to compete with and disrupt traditional and large banks.

Many banks have built up complex systems of legacy tools, which have been deeply rooted into operational structures that aren’t flexible enough to interact with modern systems. With new Fintech and bank challengers crowding the market—cloud-based and mobile-first, digitally enabled—the tug-of-war for market share has intensified.

Challenger banks have the luxury of offering high-interest savings accounts and low-interest loan packages with little unease about funding issues long-term. They can also onboard loans that might be considered too risky for a community bank or credit union and reap the financial benefits of those loan packages.

Combined with consumer expectations, traditional banks are pressured even further. Take mortgage loan processing for example. As one of the biggest drivers for revenue at a bank, if a bank takes too long to process steps, isn’t available on the weekends or evenings, has long phone wait times, has high fees and high interest rates, this overall poor package will prompt consumers to shop around.

Conversational AI + RPA

On the customer service automation side of digital transformation, two technologies aiding banks and financial institutions are conversational AI and robotic process automation (RPA). In just the last few years, banks have found significant value in this convergence. Both employ artificial intelligence to do their job, are available 24/7/365 and add a virtual workforce to an organization that work alongside the human process owners.

Historically, automation technologies have been back-office technologies used to help with things like month-end closings. Today, automation technology is being brought into the contact center, IT, HR and other departments to automate human-to-human interactions and provide faster customer service.

RPA is used to speed up the execution of previously manual business processes. In banking, automation technologies extract or approve all the relevant loan data in seconds, validating customers from multiple sources. And for mortgage applications, data from multiple sources could be simultaneously and automatically validated to reduce delays.

Conversational AI connects people to the systems and data they need to access through a natural language interface. By speaking in their own terms, customers can ask questions without having to navigate hierarchical menus in IVR systems.

When combined, the two technologies make a compelling proposition to slim down operational costs, and drive increased profitability and customer satisfaction.

By offering self-service, Axis Bank, for example, has been able to reduce the turn-around time on savings account opening by about 90% using RPA. Citigroup, Capital One and JPMorgan Chase are currently using AI-based automation to improve efficiency like validating customer data and tracking audit trails for compliance. In 18 months, one of the largest American banks, Bank of America, was able to successfully deploy 22 robots across its front, middle, and back offices, saving the financial institution an early $100,000 per code request in operational costs.

Making an impact with automation

In the last few years there is much commonality in the use cases that are being deployed at banks and financial institutions. Banks, like most companies, are looking to automate their contact centers to improve the experience for the customer, be it with voice, web chat, SMS or a mobile application.

A recent Accenture study found that, despite digital acceleration, banks still lack the ability to achieve peak productivity from technology investments, and they must scale for future readiness. Banking executives expect AI-based technologies will not only transform their industry but will also add net gains in jobs.

As competition in banking continues to fire up, the pressure for better customer service and customer experiences only grows. Automation technologies from process automation to conversation automation can be applied in the back-office and front-office operations to enable and accelerate the future of customer service.

About the Author

Jessica Gopalakrishnan is a marketing strategist experienced in accelerating growth at early stage and mature startups. As the Senior Director of Marketing at Cognigy for the Americans, she is passionate about advancing global awareness about conversational AI, customer service automation and AI-first concepts.

About Cognigy

Cognigy is a global leader in omnichannel Customer Service Automation. Intelligent voice and chatbots powered by its Conversational AI platform help businesses improve service quality, reduce operational costs, and support teams across the enterprise. Cognigy’s award-winning AI understands user intents precisely and enables natural dialogs in over 100 languages. Easily scalable and pluggable, its low-code platform automates business processes through integrations into backend systems, operates as SaaS and on-premise, and is GDPR compliant. Cognigy’s worldwide client portfolio includes BioNTech, Bosch, Daimler and Lufthansa. Learn more at https://cognigy.com.

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