Even as artificial intelligence-based technologies continue to permeate more and more aspects of our lives, I’ve noticed a stubborn tendency among the banking old guard to focus on improving operational efficiencies rather than enhancing the customer experience. That may make sense on paper, but it’s ultimately bad for long-term user satisfaction.

It’s easy to realize efficiency gains in the call center by automating customer support with AI. It’s far harder to understand what customers really want out of their experience and then use AI to drive towards that. AI offers multiple vectors of possible change, from identifying patterns in otherwise noisy data, to uncovering more appropriate, relevant means of evaluating creditworthiness. We are only just beginning to scratch the surface of what these technologies can offer.

Yet in a world of unintended consequences, it is important that we don’t just innovate for innovation’s sake. Too much technology and we lose the personal touch that we know remains critical for any business. What’s important to understand is that AI is more than just chatbots. In fact, AI can have a positive impact across nearly every aspect of the customer experience. To demonstrate that, I’ve laid out just four of the diverse ways that AI can enhance the banking customer experience.

1 – Conversational Banking

Conversational banking is the closest of these technologies to the popular conception of a chatbot. But let’s be clear: these aren’t your parents’ chatbots. Advances in AI, in particular natural language processing, have empowered businesses to take a lot of boring or routine conversations off the phone and into the online realm. Customers don’t even have to do anything special to communicate with these systems because they handle a variety of natural speech patterns and can even work with syntax they’ve never seen before and still find the answer to customers’ questions. That’s a win-win because customers get the experience of talking to a live person without the pain of having to wait on hold, and banks can save money on call centers while improving the user experience.

2 – Lowering Default Risk

The only thing worse than waiting for an answer is being rejected for credit cards and loan applications. At many banks, this process is still overseen by individuals, and it can take days for customers to get a response. But not only is the process slow, it’s also not particularly accurate either — especially because banks mostly rely on an applicant’s credit score to determine their approval. 

Thankfully, AI developers have created far more accurate solutions that take into account factors such as the amount of equity their customers hold, their job stability, and their debt-to-income ratio. Training these algorithms on large bodies of data, they’ve created programs that approve or deny candidates more quickly and accurately than traditional methods. Having embraced the use of these algorithms from the beginning, many alternative lenders have seen a higher rate of approval for business and consumer loans than traditional banks — an advantage that both they and their customers enjoy. Traditional banks must follow suit.

3 – Improving Security

Biometric security methods don’t just make it harder for criminals to access phones, they actually improve the customer experience over passwords and passphrases by promoting ease of access. Between the ubiquitous smartphone thumbprint reader and increasingly common face-recognition feature sets, customers have clearly embraced the quickness and ease of using biometrics to unlock their phone, make payments, and access other sensitive accounts in place of using hard-to-remember passcodes and other phrases. And they expect that ease of access from their banks, too.

What makes today’s biometrics possible, of course, are advanced AI-based algorithms that take in data from cameras or other sensors, identify key face or fingerprint points, and then compare them against user-provided scans to make an accurate (usually 98% or higher) prediction about whether the user attempting to gain access is the owner of the phone or account. With biometrics being clearly the superior option for both security and customer experience, banks have plenty of incentives to offer biometric authentication wherever they can.

4 – Identifying Fraud

Perhaps AI’s biggest benefit, from a business perspective, is its ability to predict future behavior based on past behavior. Feed a well-trained AI algorithm real-time data, and it can predict with far greater-than-human accuracy the likely outcome. That capability makes it invaluable for banks, which often have to make quick decisions about large sums of money.

Accurately identifying fraud is extremely important to both banks and their customers, and not just for catching cases of credit card fraud or stolen identity. You also don’t want a system that’s too sensitive. (We all have that friend — maybe we are that friend — whose bank uses an overly-aggressive fraud detection algorithm.) By using AI to analyze past instances of confirmed fraud, banks can uncover patterns that help them determine the likelihood of a current transaction being fraudulent. This means avoiding devastating cases of theft, on the one hand, and annoying credit lockdown situations on the other.

Smarter. Better. Faster.

There’s no doubt that artificial intelligence will continue to revolutionize the way customers interact with banks and businesses, and as the 2020s progress, we can expect that rate of innovation to only accelerate. To continue to compete in an ecosystem that is being radically transformed before our eyes, banks must stop playing catch-up when it comes to AI. They must seize this opportunity to modernize their IT infrastructures, not just to ensure that they can power today’s innovative solutions, but also to ensure they’re at the leading edge of whatever innovations tomorrow’s AI researchers develop.

Chuck Fried is the president and CEO of TxMQ – an enterprise solutions provider supporting customers in the US and Canada since 1979.