As AI has become a bigger part of many companies’ growth strategies, the pressure for others to incorporate this technology has increased dramatically. While you may be interested in following the lead and taking advantage of this new technology, you may also feel overwhelmed with the sheer number of banking AI options on the market. What are the key banking AI use cases, and which ones are right for you?
While there’s a lot of options available out there and a lot of competing claims from different providers, there are a few key banking AI use cases which you can focus on that will help you narrow down your search. These are proven, well-tested implementations that will likely target the same areas of improvement you’ve been looking to tackle in your own contact center.
By sorting these AI use cases into who exactly will most often use the tools, you will see the main areas to focus on. These are great jumping-off points into how you can look at what AI could do for your contact center, and can help you evaluate future vendors.
Customer-Facing AI: Automated Self-Guidance
One of the biggest areas that AI has already become well implemented into is for customer-facing chatbot applications. These AI-powered tools are designed to answer customer queries and solve problems automatically in a natural, conversational manner. There’s a lot of potential in these solutions, but banks should exercise caution when putting AI solutions in customer-facing positions.
A well-implemented banking AI chatbot can help ease an overburdened call center by handling simple, routine queries and allowing human agents to focus more on the crucial moments of truth that build customer relationships and boost loyalty. This also lowers average wait times across the board, getting customers the help they need faster.
However, a generative AI chatbot may give some unexpected results if a customer is allowed to directly interact with it. Stories of these generative AI chatbots making up false information on the spot, or potentially leaking sensitive information, should be enough to emphasize the importance of a Responsible AI solution. Financial institutions should prioritize a customer-facing AI solution that’s specifically built for the security needs of the financial services industry.
Ensuring your AI chatbot is purpose-built for finance will ensure a faster, easier deployment with less required training necessary. An AI chatbot made for finance already knows how to service the most common inquiries, and will likely be built with the security needed to ensure customer data stays secure.
Employee-Facing AI: Enhancing the Human Touch
While customer-facing AI can significantly improve many aspects of the service experience, customers always need the ability to reach out to a live human representative. Most consumers will not want to discuss crucial financial matters with AI, and would much prefer a live representative who can empathize and personally assist them. However, this doesn’t mean employees can’t have access to banking AI tools that can make their jobs much easier. Look at employee AI tools that, rather than try and replace the everyday duties of your employees, simply help to make their jobs easier.
AI-powered tools help automate administrative tasks, such as writing post-interaction reports, that allow for service reps to have more time for meaningful customer interactions. They also allow for easy autofill answers to commonly asked questions, negating the time needed to respond. AI even presents representatives with an automated database of information to ensure consistent answers on more complex subject matter. With these types of applications of AI tools, all content the AI produces is vetted by a staff member before being presented to any customers, making sure to avoid any unwanted responses that leak sensitive information, add confusion, or result in a poor customer experience.
Employee-facing AI solutions allow for not only faster, more streamlined workflows, but increased scalability as well. These tools can allow you to ensure consistent, high-quality customer experience at scale, as reporting and informational access becomes easier and more repeatable. This also encourages better real-time support, as new employees receive on-the-spot guidance and instant coaching.
Manager (and Executive)-Facing AI: Automated Insights
Quality assurance is one of the most time-consuming aspects of the contact center manager or customer support executive’s job. Going over the vast wealth of data that a contact center produces and determining key areas for improvement/highlights is a lengthy process—one that’s prime for automation. AI is often shown to be quite proficient at creating summaries of large amounts of text or data, so utilizing this feature to create banking AI designed to generate insights into your contact center performance feels like a no-brainer.
For Managers, this AI provides a great opportunity to streamline a normally lengthy process, as well as create the ability to provide more consistent feedback and coaching opportunities for employees. As the data will be analyzed in a consistent manner, with a consistent level of quality and detail every time, the output will always be just as consistent and able to give meaningful insights no matter the scale.
And for Executives, you’ll be able to use this information to make more informed decisions about changes to the organization as a whole. Able to compile large amounts of data into easy to read reports, executives in charge of call center performance will no longer need to worry about expensive and lengthy review processes to determine trends within their organization.
The Next Steps: Banking AI for All
With these three potential proving grounds for AI at your financial institution call center, hopefully you have an idea now of possible places to start implementing this new technology. These should prove as some examples of what you can realistically expect AI to do for your banking contact center. Evaluate future vendors with these areas in mind, and you’ll be on the right path to getting the most out of AI in your banking organization.
In order to ensure a fully successful launch, you should seek out a solution that can deliver on all of these areas of interest, and one that’s pre-built to understand the needs of the financial industry. Glia Cortex is an AI platform that’s been built from the ground up specifically for banking with the security, specificity, and proven results that ensure a promising launch.
See a live demonstration of Glia Cortex in action: Book a Demo with us today!
