The Future of Banking Technology Is Here
by Michael Plimsoll
Posted on 03-21-2018
The future of banking technology is not something the average person thinks about, and we usually take our relationship with our bank for granted until something goes wrong—such as losing your wallet. That’s exactly what happened to me a few weeks ago, and although I’m generally happy with the service my bank provides, the loss of my debit and credit cards plunged me into a nightmare of red tape.
Several days after losing my cards, I received a letter in the post, warning me about fraudulent activity that had already taken place on my account, which my bank hadn’t prevented. I had to schedule time to visit the branch to sort this out, since my bank didn’t allow me to talk with a manager online.
As I stood at the back of a long queue, anxious and panicked, I thought of all the ways the bank could have handled this experience more effectively. For example, they should have detected that a thief was trying to use my debit card at an ATM before they placed a charge on it, because it clearly was not me at that location. They should have alerted me instantaneously, via a message on my phone. And I should have been able to sort out the issue and order new cards online, saving me a drive to the branch.
The technology for every one of these improvements already exists. In a variety of industries, artificial intelligence (AI) and machine learning (ML) already enhance and streamline customer experiences. Now customers are increasingly expecting—and demanding—that banks adopt these solutions as well.
Here’s what the future of financial services looks like.
Three key trends driving disruption in the banking industry
- First, digital is driving customer demands and expectations, especially when it comes to banking now. This is particularly true of customers who’ve grown up with the web at their fingertips. A recent Visa Digital Payments study found that 69 percent of European millennials regularly manage their money via mobile devices.
- Second, a new wave of fintech companies (such as True Layer, Paybase, and TransferWise) is disrupting the old high-street bank paradigm. These agile new players understand where the market is heading and what their audiences want. They’re nimble, unencumbered by the complexity (and in many cases, regulatory red tape) slowing down bigger banks.
- Third, today’s regulatory environment creates a lot of moving targets. In an effort to ensure regulatory compliance, many high-street banks shy away from disruptive technologies, taking their eyes off experience-led efforts to focus on safeguarding customer privacy. While this sounds like a benefit, the customer of tomorrow already expects both positive experiences AND tight security. If a bank boasts that they are the most secure option available yet make the consumer jump through hoops in order to enjoy the security advantages, it will never be a win. In fact, a friend of mine, who banked with a leading institution for over two decades, changed providers last week after she found herself in a foreign country with no access to funds after having gone through the fifth hold on her account in just three months due to suspected fraudulent activity. In her words: “I travel a lot. I always let them know where and when I am going. I will not put up with inconvenience when I follow their rules and still get penalised.”
Many banks are beginning to leverage the power of AI and ML to help address these challenges. By letting computers do the heavy lifting, they free their marketing experts to identify new ways to enhance the customer experience.
Although AI and ML are frequently used buzzwords, few really understand their implications. Platforms such as Adobe Sensei make their benefits concrete by using intelligent automated targeting to determine which experiences are best suited for which customers.
For example, say you’re running an A/B test on your website to determine which homepage layout generates the most conversions. After an initial test, you’ve determined that layout A generates a 50 percent conversion rate, whereas layout B generates a 20 percent conversion. Is layout A the only winner? After all, 20 percent of your visitors are still converting in response to layout B, which means you need to continue serving layout B to that audience segment. It would, however, take you days, if not months, to trawl through the data to find the characteristics of the people who liked layout B, though.
This is where machine learning comes in. When a new visitor arrives on your homepage, the algorithm can analyse data you’ve already acquired about that person, recognise that they’re likely to prefer layout B, and then serve them layout B, increasing the likelihood that they’ll convert. This is known as automated targeting, and a growing number of FSI organisations are adopting it today.
But truly personalised customer experiences aren’t limited to your website. AI and ML really shine when you implement them across all channels.
Tools such as Adobe’s Experience Cloud ensure that timely communication is delivered to every customer, via any digital channel necessary. And by putting together data from multiple channels, the Adobe Experience Cloud helps weave a seamless experience across web and branch. Personalised experiences are just the beginning of the benefits AI and ML can deliver. To see their true power in action, you’ve got to see what these technologies can do when something goes wrong.
One way for banks to prevent the kind of fraudulent activity I experienced is to use facial awareness and biometrics to detect that the person using my card isn’t actually me. Adobe has been developing AI and ML in its Cloud products, such as Lightroom, Stock, and Experience Manager for years, developing enhanced object recognition capabilities that can help identify fraudsters and alert banks to take action. Here’s a video demonstrating how this process could come together.
In the video, you saw an ATM using object recognition with facial awareness to assist in fraud detection. Although the process looks seamless on the customer’s end, the AI is working hard behind the scenes, automatically sending a message to the bank manager and a text to the customer when the fraud is detected.
Through all of these developments and disruptors, the core principles of FSI customer service remain the same. As always, consumers expect convenience, personalised service, rapid responsiveness, and attention to detail. As banking moves into the future, AI and ML allow FSI companies to deliver these benefits more effectively than ever before. Click here to read more from me about technological trends affecting the retail banking industry.
Topics: Digital Transformation, A/B testing, anomaly detection, artificial intelligence, customer experience, experience management, Machine Learning, personalisation, UK, UK Exclusive, Digital EMEA