AI, Machine Learning and Other Technologies Are Completely Transforming Banking.
“It all comes down to data.”
That’s one of the main drum beats attendees at the conference heard over and over. The good news is that banks and credit unions have a ton of data. The rub is that if that data isn’t clean, accurate and accessible, financial institutions won’t be able to take advantage of transformative technologies such as AI, voice recognition and data analytics. Unfortunately, the banking industry still has a long way to go.
Only 6% of banks and credit unions believe that they are effectively using data, according to Don Parker, Executive Vice President, MX. Louis Richardson, Chief Storyteller at IBM, told attendees that banks and credit unions are likely making decisions about the customer journey — which products and services to offer on which platforms — leveraging only about 20% of the data they have available. As Richardson explained, it’s like driving your car really fast on a road filled with traffic and construction hazards and having cardboard taped over the windows: “You’re running your business with a handicap.”
Most financial marketers think they know their audience, but they probably don’t. Even if you incorporate data from social media to build consumer personas, you can’t be sure that you are taking that data in context. AI, Richardson explained, uses natural language understanding that provides a more accurate view of consumer behaviors.
“AI gives you views to consumers and access to data that you’ve never had before,” said Richardson.
But even if you had all the data, chances are good that you are not be asking the right questions about that data. Richardson claimed that cognitive AI can help bankers ask better questions about their data to make better decisions.
Bottom line? Financial marketers need to up their data game.
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Voice and AI: The Next Frontier
Data will also be critical in moving beyond the mobile device to other technology interfaces that take advantage of AI.
“Data is the oil for AI,” said Tom Edwards, Chief Digital Officer for Epsilon. “Banks and credit unions need a comprehensive data strategy in order to take advantage of AI.”
Sure, consumers can personalize their mobile experience today by downloading apps, changing settings and updating your display, but smartphones are just first step in a series of new interfaces that will change how consumers view and interact with the world. Multimodal technologies will use AI and deep learning that combine voice, vision and touch into a single interface that adapts to the consumer, rather than asking the consumer to adapt to the device. By 2028 — just a decade away — multimodal devices will become ubiquitous, predicted Edwards.
And then there’s “deep learning.” Deep learning differs from machine learning, noted Edwards, because it is based on models created by humans, whereas deep learning relies on neural networks that learn much like the human brain. The first of the senses — voice — is already becoming AI-enabled. One in five homes has a voice-activated device like Alexa. Bank of America has Erica. Royal Bank of Scotland has Cora.
Edwards also told attendees that Gen Z wants to manage finances using virtual assistants like Alexa. Using employee and consumer feedback, AI, by the way, has allowed Cora to expand her knowledge base by 100% in just 12 months, said Edwards. Amazon’s division focused on Amazon Pay recently folded the Pay team into the division working on Alexa. The implication is clear—Amazon is working on voice-activated payments, said Edwards.
‘Artificial Intelligence’ is Not for Me (And Other Myths)
AI is often cool, sometimes a bit creepy, but some bankers are still wary about the application of AI in banks and credit unions, noted IBM’s Richardson. He set out to debunk a few AI myths for attendees:
1) AI is hard to understand. AI is actually easy to understand. “Effective cognitive AI systems think just like you do,” explained Richardson. It observes, it interprets, it evaluates and it decides, just like a human.
2) AI is not business ready. They are, and they have been for some time. AI systems like IBM’s Watson are able to understand natural language to make the interface with the consumer much more user-friendly. Richardson showed a television clip from 2014 when Watson beat the defending Jeopardy! champions to prove that AI is ready. And it’s getting better, said Richardson. Watson can now see and hear.
3) I should wait and see what happens with AI before committing. AI systems are learning systems and need time to learn about your bank or credit union, your culture and how you do business, said Richardson. To say you want to wait until AI is more evolved before starting the learning process is like saying you won’t send your child to kindergarten for five years until the schools improve. “Every day you are not letting AI learn your business, you are one more day behind,” warned Richardson.
Humans Still Matter
AI and machine learning are powerful technologies that every bank and credit union—no matter how small—should embrace as a tool to better understand consumers, their journeys and build personas. After all, James Robert Lay, CEO of Digital Growth Institute, told attendees, “The consumer journey should be at the center of everything you think and everything you do.” However, only 17% of banks and credit unions have mapped consumer journeys, noted Lay.
Even with technologies such as AI that can uncover consumer behaviors and predict the products and services that consumers need next, humans still have a role to play in attracting and retaining consumers. The consumer journey is fraught with potholes. Consumers abandon somewhere between 70% and 90% of online loan and account applications because they are too complicated, noted Lay. You can significantly decrease abandon rates by connecting an applicant to a human being.
“Communicating with another human is the most influential activity in a consumer’s buying journey in getting them to convert,” said Lay. And AI can help you route these consumers to the right employee within your bank or credit union. Once there, it’s time for the machine and the human to work together, with the machine analyzing the data and employees demonstrating PET, which stands for “Purpose,” “Empathy” and “Trust.”
In an increasingly commoditized digital world, consumers still crave the basics: health, wealth and happiness, said Lay. AI and machine learning can help banks and credit unions meet those basic human needs. As IBM’s Richardson told Forum attendees, “The goal of AI is to use a machine to be more human.” To learn more about AI and experiment with technologies such as natural language understanding and visual recognition, Richardson invited attendees to visit Watson.