Artificial intelligence (AI) is a hot topic in multiple industries. But why, and how, is artificial intelligence used in banking?
Regardless of whether financial institutions want to improve customer service, bolster personalization efforts, or optimize processes, AI-powered technology is something to consider.
The benefits of using AI
Machines are becoming more accurate than human beings. AI solutions have even been used to predict heart attacks before they happen.
A major reason why AI is so accurate has to do with machine learning. According to TechTarget, machine learning "allows software applications to become more accurate in predicting outcomes without being explicitly programmed."
As technology that employs machine learning continues to "learn," its accuracy increases. To jumpstart this learning, data scientists can provide the model with specific input and output information upfront. They can also be involved in giving the machine feedback on whether they were accurate or not. The more information the technology has access to, the more they will learn and improve.
Alongside accuracy, another benefit of AI is objectivity, which humans do not naturally have.
AI technology doesn't get tired, and can work 24/7. Because of this, AI based technology can serve hundreds of customers at once.
Ultimately, speed helps both customers and businesses.
For customers, this eliminates the need to wait in line, or on hold, for hours. Customers can instantly receive fast, personalized, and accurate customer service.
For businesses, this may result in significant cost savings. If an AI-powered voicebot can serve customers accurately and quickly, there's less of a need for human interference.
However, businesses must keep in mind that consumers still want human interaction – especially for high-value decisions. In fact, 45% of consumers said human-to-human communication during their final decision to "purchase" is critical.
AI can help provide the ultimate personalized experience.
One example of a company that uses AI for better personalization is Amazon. As you shop, machine learning algorithms see (and learn from) what you view, buy, and add to your cart. This information is then used to provide specific product recommendations and suggestions.
Another example of machine learning in the workplace can be found in your Gmail account. Google first rolled out Smart Reply in 2017, which helps users quickly respond to emails with curated responses that are appropriate responses to the email you received. As you continue to use Smart Reply, machine learning will learn to suggest responses that sound the most like you. For example, using "Sounds good" versus "Sounds good!"
How banks use AI
JPMorgan Chase, Bank of America, Lloyds Banking Group, and NatWest are just a few examples of the banks that are incorporating this kind of technology into their business. Let's see how they're using it:
JPMorgan Chase has multiple areas where they're using machine learning.
The first is called Contract Intelligence or COiN, and is used to analyze and extract information from important documents. JPMorgan Chase used this to process 12,000 credit agreements in seconds instead of the typical 360,000 hours.
JPMorgan Chase is also using AI in the creation of their pricing and quoting tools, and in the recommendations they give customers.
Bank of America
In May 2018, Bank of America launched an AI-driven virtual assistant called "Erica" to their 25 million mobile banking customers.
Erica's capabilities are constantly evolving, but currently she can:
- Help customers access information (account activity, routing numbers, bills)
- Transfer money between accounts
- Schedule an in-person meeting at a branch
- Locate the nearest branch
- Educate about money management
When asked about Erica, Aditya Bhasin, head of consumer and wealth management tech, said:
“Erica’s knowledge of banking and financial services increases with every client interaction. In time, Erica will have the insights to not only help pay a friend or list your transactions at a specific merchant, but also help you make better financial decisions by analyzing your habits and providing guidance.”
In November 2018, Bank of America announced that Erica had 4 million users. As of March 2019, that number is 6 million users. It's safe to say that Erica is here to stay.
Lloyds Banking Group
They're using AI to help their human employees. When providing customer service, employees use chatbots to help them access relevant information faster.
When asked about their reasoning for using a combination of humans and technology, Marc Lien, director of digital development and applied sciences, said:
“For us, it’s about augmentation rather than pure automation — pairing brilliant people in our business with increasingly smart technology to deliver great things.”
NatWest started a pilot program in 2017 with an AI-powered virtual bank teller named Cora. Cora can answer up to 200 basic questions, so customer service representatives are only involved in complex, high-impact customer questions.
As of February 2018, Cora has about 100,000 conversations a month, but she is projected to have up to 2 million per month by the end of the year.
When asked about Cora, Kevin Hanley, director of innovation at NatWest said:
"We’re really excited about this technology because we think it could create another way for our customers to bank with us on top of the usual services we offer and be used to help answer questions round the clock, whilst cutting queuing times for simple questions. The technology has real potential for the future."
AI and machine learning helps both banks and consumers improve accuracy, speed, and convenience. What else do consumers want from banks today? Check out our Modern Banking Research to learn more.
October 15, 2019
3 minute read