4 Latest AI Trends Advancing in the U.S. and Banking Industry
AI adoption is accelerating in the banking industry. You may be wondering, “How many other banks are adopting AI?”
According to a report by UBS, 75% of banks with assets of $100 billion or more and 46% of banks with assets of less than $100 billion have adopted AI. The larger banks are more likely to be adopting AI.
However, when considering the adoption of AI in your own company, you may first want to know what AI can be used for, or you may want to refer to case studies from overseas where AI adoption is advancing.
In this article, we will first consider AI trends in the US banking industry, as well as looking at some examples of AI applications in global markets. Finally, we’ll discuss three banking operations where AI can be introduced.
AI Trends in the U.S. Banking Industry in 2022
How important is the use of AI in the banking industry in other countries? Let’s check by looking at the “4 AI Trends in the Banking Industry” in the U.S. in 2021.
Banking Industry AI Trends 1. Ai’s Growing Presence
According to a survey by the Economic Intelligence Unit, 77% of bank managers believe that AI will separate the winners and losers in the banking industry.
In another figure released by Contentstack, 66% of bank executives believe that new technologies, including AI, will be the biggest trend in the coming years through 2025. The fact that last year’s response to the same question was 45% shows the importance of AI technology in the banking industry.
AI is increasingly present in two main areas:
- Decision support
- Customer experience
Increasingly, managers are being supported with blockchain, machine learning, and risk management automation to make decision-making easier.
In the area of customer experience, there is a growing trend toward the adoption of interactive AI such as chatbots, virtual assistants, and digital humans.
McKinsey’s analysis presents five benefits of using AI in banking:
- Access to new customers
- Market expansion
- Increased engagement
- Reduced risk
- Reduced service delivery costs
In particular, the use of interactive AI is expected to educate customers about financial literacy, reach new customers, and expand the market.
Banking Industry AI Trend 2. Digital Ecosystems
A digital ecosystem is a structure in which different products, services, and even industries work together using IT to generate profits.
It means that different services such as asset management, consumer finance, health insurance, and housing will become profitable structures or platforms that work together online.
Even before the pandemic, the U.S. banking industry was looking to create a digital ecosystem:
according to a 2019 Accenture survey, 89% of banks believed that creating an ecosystem would create significant value for their future business.
Two of the most important aspects of creating a digital ecosystem in the banking industry are “enhanced cybersecurity” and “customer experience.” While there must be ironclad security, there must also be a user-friendly experience.
Forming a digital ecosystem that combines the two will require collaboration between the banks themselves and vendors with expertise in fintech and interactive AI.
Banking Industry AI Trend 3: Changes in the Branch
After 2022, the role of the branch will change dramatically. While the branch itself will not disappear anytime soon, there will be a clear distinction between the role of the branch and that of online banking.
In the actual branch office, the customer service will be for corporate clients and those requiring complex support. Online, they will handle general reception and transactions.
It is important to note that the loss of the branch office should not mean the loss of corporate and customer engagement as well.
Even online, the service must be able to provide a human touch.
For example, Singtel in Singapore has prepared digital kiosks that utilize interactive AI.
Digital kiosks with in-person support by interactive AI and online support by digital humans help maintain engagement.
Banking Industry AI Trend 4. Commitment to ESG
U.S. banks are emphasizing their commitment to ESG, which stands for Environmental, Social, and Governance. In other words, it refers to management that emphasizes environmental considerations, social contributions, and compliance with laws and regulations.
ESG commitments enhance a bank’s brand value. 33% of U.S. consumers say they would prefer to buy products from brands that do good things for society and the environment. Younger generations, in particular, believe that they are voting with their wallets.
In one survey, 90% of young people even said they changed the brands they buy from after seeing a company fulfilling its social responsibility.
In response to the ESG-oriented trend, three-quarters of banks are “considering increasing their investments in environmental issues,” according to a Deloitte survey.
In addition, there is a growing trend toward supporting the wellbeing of employees in terms of social contribution and legal compliance.
The idea is that only by protecting the mental and physical health of employees can they do good work for society. Leading banking companies are taking steps to reduce the drudgery and stress of their employees by introducing AI.
Advantages and Disadvantages of AI Chatbots as Seen in the U.S
The trend of introducing AI into the banking industry will continue, with Banking and Financial institutions being among the top 3 industries currently utilizing chatbots.
According to Cornerstone Advisors during early 2020, only 13% of banks and credit institutions had a chatbot, and a further 16% were just planning to introduce one by 2021.
In the later half of 2022, these percentages continue to increase according to the eMarketer forecast for bank chatbot users in the USA (between 2021-2025). By 2030, it’s predicted that chatbots will be so well integrated into banking processes that customers won’t be able to make the distinction between a chatbot or a digital agent.
What are the benefits of AI chatbots being implemented in the banking industry?
There are four advantages of AI chatbots in the banking industry:
- Providing high-quality customer support
- Prevent fraud
- Improving efficiency of back-office operations
- Realization of up-selling and cross-selling
The following is a brief explanation of each of these benefits.
1.Providing high-quality customer support
The most obvious use of AI chatbots is in customer support. It is the chat bot that appears in the corner of the screen when you access a website.Chatbots can speedily provide services such as payment processing, lost card processing, account information confirmation, and asset management advice.
2. Fraud Prevention
AI chatbots can connect to the bank’s back-end systems. AI analyzes chatbot users’ conversations and operations in real time and can detect suspected fraud patterns at an early stage. Since the detection accuracy is higher than that of humans, the fraud prevention detection rate can be improved.
3. Improved efficiency of back-office operations
Chatbots are not just a service for customers. Bank employees can also use them to improve operational efficiency.
For example, they can be used to manage FAQ information and train new staff. Having chatbots for employees can increase productivity and speed up growth.
4. Realization of up-selling and cross-selling
Banks offer a wide variety of services. These include mortgages, checking accounts, business loans, home insurance, and pension plans. Customers may only use one or two of the services offered by their bank.
An AI chatbot can recommend other services when the customer is using the bank app. It analyzes the customer’s usage and presents them with a selection of services that can save more money or be more convenient.
They introduce mortgages tailored to the user’s age and asset situation, and direct them to the annuity page. As a result, they can upsell and cross-sell to existing customers.
Disadvantages of AI Chatbots
Looking at the merits of AI chatbots, you may feel that you should just implement chatbots for now. However, there are two disadvantages of AI chatbots.
- No advantage over other companies
- No human touch
Since many banks have introduced AI chatbots anyway, there is no advantage if you adopt the same system now. Furthermore, many chatbot systems are text-based services. The disadvantage is that you are interacting with customers without the human touch.
One way to solve the disadvantages of AI chatbots is to adopt interactive AI digital humans. An interactive AI digital human is a product that can combine avatar customer service with texting services.
In fact, the “human touch” is a very important appeal point for products offered by banks.
This is because financial products are related to major life events. Examples include buying a first home, starting a business, or retiring. Many consumers want to receive human support in choosing the financial products they purchase for their life milestones.
That’s why 42% of firms say making chatbots more human is a top priority, and 32% want chatbots to be able to have deeper conversations.
Three categories of the banking industry where AI can be implemented
The first thing you should do is consider where to deploy AI in the following categories
- Front Office
- Middle office
- Back office
In the “front office,” AI can be employed to provide information to customers through dialogue. In the “middle office,” AI could be used to detect and prevent fraud, and in the “back office,” AI could be used to verify credit information.
The following are examples of how AI is used in the above three categories in various global markets.
1. AI case studies in the front office
ASB Bank (New Zealand), one of the largest banks in the Asia-Pacific region, provides entrepreneurial support with an interactive AI digital human.
Swiss Union Bank (UBS) has hired a digital human as its chief economist to explain financial forecast data to clients.
2. AI case studies in the middle office
Leading investment bank Goldman Sachs (U.S.) is using AI to detect fraudulent activities such as insider trading.
Goldman Sachs, a major investment bank, is promoting the automation of stock trading using AI-based trading algorithms. To monitor and prevent fraud, the bank is also using solutions from DigitalReasoning, an AI venture that provides conversation analysis solutions.
This enables the company to analyze the meaning and nuances of the contents of traders’ e-mails, documents, etc., and detect fraudulent activities such as insider trading. It is expected to not only uncover fraudulent activity, but also serve as a deterrent to prevent such activity.” – AI White Paper 2019
In Japan, Kirayaka Bank in Yamagata Prefecture has introduced Nice Advanced Process Automation, an RPA with artificial intelligence, to reform its work style.
ORIX Bank Corporation uses the investment real estate analysis tool “Gate.” to analyze property data with AI.
3. Examples of back-office AI implementation
JPMorgan Chase, the largest U.S. bank, is focusing on automating administrative work by establishing teams specializing in big data, robotics, and cloud infrastructure.
Specifically, the company has automated the process of reviewing commercial loan agreements using software called Contract Intelligence (COIN), which leverages machine learning and cloud technology. The company says it has realized significant time savings and reduced interpretation errors.” – AI White Paper 2019
Some financial institutions in Japan are using the AI system Deserve to screen credit cards.
Mitsubishi UFJ Bank offers the Mortgage Quick Screening service, which uses AI to screen mortgages.
Final thoughts
The banking industry AI trends in the U.S. are the result of Ai’s growing presence, the formation of digital ecosystems, the changing role of branches, and the increasing importance of social responsibility of banks.
AI will be a must-have feature in the banking industry, and by making good use of it, you can develop your bank’s services and market size.
