Supercharging Conversational AI in banking

The increased sophistication of natural language processing and other Artificial Intelligence (AI) technologies has undoubtedly changed the landscape and transformed what’s possible for institutions worldwide. Take the rise of Conversational AI in the banking industry, for example.

This approach uses AI-powered chatbots or virtual agents to replicate human interactions by deciphering human speech or messages and providing appropriate responses. It’s a dramatic step forward in offering a customer service experience that’s cost-effective, user-friendly, and efficient.

What do we mean by Conversational AI?

Strictly speaking, Conversational AI focuses solely on chatbots and similar tools that replicate human interactions. That said, it’s generally understood that human customer support representatives are needed as well. With personalized help so important to secure a loyal customer base, not having human agents on hand will be seriously detrimental to your business.

However, there’s still a mindset issue at play here that companies need to overcome to fully break down the barriers to conversational AI in banking. Instead of thinking of chatbots as one channel then live access to agents as another, it’s better to think of it all as one interconnected journey.

AI should be thought of as Assisted Intelligence rather than Artificial Intelligence, supplementing agents’ ability to offer a superior customer experience. Customer conversations with organizations can take place across banking chatbots, virtual assistants, voice assistants or more – but the key to providing a customer journey that meets expectations is always having access to a human agent.

Benefits of Conversational AI in the finance sector

The potential benefits of conversational experiences are enormous, with Gartner predicting that it will reduce contact center agent labor costs by $80 Billion in 2026, and the financial services sector is set to benefit from it.

But where will these savings come from?

Automation of repetitive tasks and improved efficiency

Automation has been a staple of organizations for years now, allowing for fewer repetitive or administrative tasks and freeing workers up to pursue more meaningful work. In fact, a reported 90% of workers claim that their productivity has been improved due to automation, with 85% also crediting it with boosting cross-team collaboration.

In a banking experience context, Conversational AI provides similar productivity and efficiency increases. Take for example the interplay between a chatbot and Live Chat channels. The chatbot increases productivity by either directly offering solutions to simple queries or effectively triaging the request to send the customer to the correct agent.

90% of workers claim that
their productivity has been improved due to automation

For one Unblu customer, 76% of requests from calling or email channels were handled by the chatbot – leading to a 3X increase in agent productivity.

Personalized services

Personalization has become a defining characteristic of today’s financial services offerings. Banking customers now expect it in every aspect of their financial lives. Customer feedback surveys show that 56% of US online adults want all of their account information to be available in one place, a number that rises to 68% when just considering millennials.

However, while having access to information can be classed as “nice to have,” what’s essential in any circumstance is that any customer service interaction – whether for customer queries, complaints, or product inquiries – is fully personalized.

By driving efficiency and allowing agents to talk to multiple customers at one time, Conversational AI makes it possible to provide a personalized experience that boosts customer satisfaction.

Increased conversion and retention rates

When done well, efficiency and personalization have two key benefits – they drive conversions and increase customer retention rates. They achieve this by building strong relationships that maximize the sense of trust that the bank customer has in the agent.

As a result, when the moment of truth arrives, the customer is more likely to be receptive, making it easier for the agent to leverage it. On the other end of the spectrum, if a customer receives a poor experience during a time that is important to them, it can influence their decision to move to another company.

This is a key component of how Unblu is able to achieve 95% positive customer satisfaction and 3x conversion rate for our customers.

Challenges faced by banks adopting AI

Despite the potential rewards of Conversational AI, there are a number of challenges that stop banks from accessing the benefits.

Lack of an implementation plan

Creating a new Conversational AI experience can be difficult for companies, particularly when agents are used to certain workflows. This is why there needs to be an agile approach to implementation that balances introducing the new technology with proper onboarding.

The temptation is to dive in and launch a full Conversational AI solution, but this will undoubtedly lead to issues that drag the initiative down or even cause it to fail. Instead, it’s important to pilot the initiative, using a segment of your audience as a tester to sort any teething issues and grow over time.

Privacy and security concerns

Issues surrounding privacy and security are always a hot topic in the financial services industry, whether looking at it from a compliance perspective or in terms of protecting customer data. A survey conducted by Forrester found that banking sector executives consider security to be the biggest obstacle to digital transformation.

This is understandable as an incredible 74% of financial security leaders have experienced at least one ransomware attack within the last year.

Difficulty tracking performance metrics

When you begin a new initiative, the performance metrics you’re used to or what the numbers mean can change. Take average handle time or AHT for example. Logically, you would want a low AHT, as for traditional channels like phone calls the lack of concurrency makes it essential. However, a low AHT on a Conversational AI or Live Chat channel may or may not be a good thing.

Yes, efficiency is important, but the quality of the interactions is key. If there’s too much emphasis on AHT, the agents can’t reach a satisfactory conclusion, which affects satisfaction and conversions.

Now, bearing in mind that a Live Chat channel can handle multiple queries at once, having an extremely low AHT may not be as important as having a high first contact resolution (FCR). The point is, the performance metrics used need to align with the company’s context, and that can take a while to figure out when introducing a new channel.

Poor user experience

One of the main legacy complaints that customers have is in the performance of chatbots. There are a couple of areas where the issues can arise. Firstly, there’s the problem of over estimating what the chatbot can do – particularly out of the box. No matter how good the chatbot is, it will need to be adapted to suit your organization’s specific needs.

Addressing this is a combination of time and active training. As customers use the technology, they will naturally ask common questions. At the beginning, there will be issues that the chatbot isn’t currently able to handle, which will need to be updated with the correct information.

Thankfully, ensuring more efficient and accurate training is one of the areas where Generative AI has dramatically reduced the work necessary. With Generative AI, the chatbot is able to make training suggestions on the intent level that will boost performance with reduced agent input.

Next, there’s the issue of triaging. It may be that there’s no proper rerouting feature in place or it’s lacking the ability to identify the right agent to send a customer to. This can lead to many issues, as there’s no more frustrating customer support experience than being stuck with a chatbot that is unable to solve your issue or redirect you to the correct place.

Elevated Conversational AI for seamless support

New technology and digital channels should work in harmony to meet customer expectations. In this way, banks can reduce customer support costs, while better addressing user requests and increasing customer loyalty, conversion rates, and more. If you’d like to find out how Conversational AI can increase digital engagement, ensure faster responses, and ensure a top customer experience, reach out to us for a personalized demo today.