Banks are ready to embrace AI, but customers are hesitant: How to bridge the trust gap with GenAI and customer communications

Scott Draeger

By Scott Draeger

Scott Draeger is the SVP of Product Marketing and Vertical Solutions at Smart Communications. With a passion for collaboration, he focuses on how communications can be better for the recipient and perform better for the business. He started as a document designer using a collection of hardware and software technologies, before moving to the software side of the industry. His broad experience includes helping organizations improve heavily regulated customer communications all around the world.

Generative AI (GenAI) has unquestionable potential for the banking industry, with some estimates suggesting that it could add the equivalent of $200 billion to $340 billion to banking revenues each year. Banking leaders are already taking steps to capture that value, with over $20 billion invested in AI technology last year – the most significant spending by any sector worldwide – and nearly $100 billion in investment expected by 2027.

But, when it comes to the customer experience, banking customers are not ready to fully embrace AI just yet. Our recent survey of 2,000 customers in finance, healthcare, and insurance showed skepticism over the use of GenAI in their customer communications, with 63% concerned about ethical use and 66% with security concerns. The report suggested a need for greater checks and balances so that the public would feel more comfortable with this still-new technology.

So, how are banks embracing AI, and what concerns do they need to address among consumers?

Fraud, trendspotting and customer service: AI’s greatest strengths in banking

It’s early days, but the banking industry has already identified three core areas to maximize the benefit of artificial intelligence.

1. Fraud Protection: The first is improving fraud detection, which cost the industry nearly $500 billion in 2023 alone. Banks are using AI to monitor transactions in real-time, detect unusual behavior and alert both customers and internal prevention teams to potentially fraudulent activity. Because these AI models can process data and recognize patterns far more effectively than the human mind, they have a significantly higher success rate, saving banks from heavy losses and protecting their customers.
2. Market Trends: AI is also crunching the numbers on market trends, helping investment managers make more intelligent decisions based on more data than they could ever manage before. These prediction tools can also be made customer-facing, which gives a bank’s clients greater access to individualized investment advice and helps them feel more in control of their financial decisions.
3. Customer Experience: Intelligent chatbots, customized service and AI-generated communications are helping banks on the third frontier: customer experience (CX). These investments help reduce wait times, drive greater efficiencies and improve the accuracy of communications they send to customers. But according to our consumer survey, it’s these investments that customers are also most wary of.

Customers are skeptical – and concerned – over GenAI in customer communications.

Our research warns of a potential risk between banks and their customers regarding using GenAI. Two-thirds of those customers have ethical and security concerns (63% and 66%, respectively) over the use of GenAI in the communications they receive, and less than a third (30%) believe that the technology can be better than humans in creating customer communications content.

Consumers are not just skeptical; they want their institutions to put guardrails in place when deploying GenAI, and they want to know when it’s been used. A staggering 81% said that humans should check GenAI content, and over three-quarters want its use to be explicitly called out.

These sentiments are not dealbreakers, but banks must consider how customers feel about this groundbreaking new technology when using it in their communications.

How to bridge the perception gap – openness, security and best-in-class experience

Banks can begin by embracing honesty and transparency as the best policy for GenAI use. They should include disclaimers on content created with GenAI tools so that customers are fully aware of its use. This is also an opportunity to show that humans remain in the loop by adding a signature from the bank employee who checked over the AI-generated content and signed off on its use.

This policy of openness should extend to other aspects of the customer experience where AI is deployed, such as with chatbots and other customer service functions. Customers should also be able to offer feedback on how the technology works so they can feel like they are part of the process.

To address security concerns, banks could disclose the data used to train their customer-facing AI models. Specifically, they can explicitly call out that sensitive, secure and personal data are not being used so that customers can rest easy that their data remain under lock and key. Customers should also be able to opt out of these functions wherever possible to give them greater control over AI’s role in their banking experience.

Finally, there’s no better way to assuage skepticism than by demonstrating the positive power of AI. Banks must ensure that wherever AI is deployed, it delivers maximum benefit to customers and improves their overall experience. Whether through reduced wait times, more timely and accurate messages from their bank, or simply a more personalized experience, customers are more likely to embrace any new technology when they can see a positive impact on their own lives.

AI’s domination of news cycles, political debate and even kitchen table conversations is unlike any technology we’ve seen in the past quarter century. Not since the advent of the internet in the early 90s has an innovation promised such a profound change to our daily lives, so it’s understandable that consumers have strong opinions about its use. Our research shows that the banking industry has a real opportunity to show it understands these concerns and factor them into how it builds AI into every business layer, reaping its benefits for the coming decades.