Artificial Intelligence in Finance [15 Examples]

Have you ever asked a chatbot a question about opening a savings account? Has your bank ever called you to verify account activity on your credit card? The world of artificial intelligence is booming, and it seems as though no industry or sector has remained untouched by its impact and prevalence. The world of financing and banking is among those finding important ways to leverage the power of this game-changing technology.

Artificial intelligence has streamlined programs and procedures, automated routine tasks, improved the customer service experience and helped businesses with their bottom line. In fact, Business Insider predicts that artificial intelligence applications will save banks and financial institutions $447 billion by 2023.

The majority of banks (80%) understand the potential benefits of AI, but now it’s more important than ever with the widespread impact of COVID-19, which has affected the finance industry and pushed more people to embrace the digital experience.

In a recent AI News article, Mani Nagasundaram, senior vice president and head of solutions of global financial services at HCL Technologies, explained that COVID-19 has forced banks and financial institutions to respond to customers at an even faster pace — and around the clock. Artificial intelligence can free up personnel, improve security measures and ensure that the business is moving in the right technology-advanced, innovative direction.

According to Forbes, 70% of financial firms are using machine learning to predict cash flow events, adjust credit scores and detect fraud.

Read on to learn about 15 common examples of artificial intelligence in finance, how financial firms are using AI, information about ethics and what the future looks like for this rapidly evolving industry.

15 Common Examples of AI in Finance

Risk assessment
Can you use artificial intelligence to determine whether someone is eligible for a loan? Definitely. In fact, banks and apps are using machine learning algorithms to not only determine a person’s loan eligibility, but also provide personalized options, according to Towards Data Science. The advantage? AI isn’t biased and can make a determination on loan eligibility quickly and more accurately.
Risk management
Risk mitigation is always an important — yet ongoing challenge — in banking (and practically every other industry). Now, machine learning can help experts use data to “pinpoint trends, identify risks, conserve manpower and ensure better information for future planning,” according to Built In.
Fraud detection, management and prevention
Have you ever received a phone call from your credit card company after you’ve made several purchases? Thanks to artificial intelligence, fraud detection systems analyze a person’s buying behavior and trigger an alert if something seems out of the ordinary or contradicts your traditional spending patterns, according to Towards Data Science.
Credit decisions
Towards Data Science explains that artificial intelligence can quickly and more accurately assess a potential customer based on a variety of factors, including smartphone data (plus, machines aren’t biased.)
Financial advisory services
Looking to follow the latest financial trends? Interested in a portfolio review? Artificial intelligence algorithms can analyze a person’s portfolio (or the latest trends or most types of relevant financial information) so that you can receive the information you need as quickly as possible, according to Forbes.
Trading
Since artificial intelligence is used to analyze patterns within large data sets, it’s no surprise that it’s often used in trading. As Built In explains, AI-powered computers can sift through data faster than humans, which expedites the entire process and saves large chunks of time.
Managing finances/personalized banking
Chatbots and virtual assistants have reduced (and in some cases eliminated) the need to spend time on the phone waiting to speak with a customer service representative. Now, thanks to technology and AI, customers can check their balance, schedule payments, look up account activity, ask questions with a virtual assistant and receive personalized banking advice whenever it’s most convenient, according to Towards Data Science.
Preventing cyberattacks
Consumers want to be reassured that banks and financial institutions will keep their money and personal information as safe and secure as possible, and artificial intelligence can help. It’s estimated that up to 95% of cloud breaches are caused by human error. Artificial intelligence can boost company security by analyzing and determining normal data patterns and trends, and alerting companies of discrepancies or unusual activity.
Better predict and assess loan risks
As Forbes explains, artificial intelligence can analyze a customer’s spending patterns and actions, which can predict loan borrowing behavior. This is also important in areas around the world where people have smartphones and other means of connection and communication but may not have traditional credit. Forbes gives this example: A loan applicant can download an app and the lender would use it to analyze the person’s “digital footprint” — which includes social media use, browsing history and more in order to build a more complete picture.
Enabling 24/7 customer interactions
Thanks to artificial intelligence and the prevalence of virtual assistants and chatbots, customers can ask questions at all hours of the day (and night!) and don’t have to wait to speak with a person.”It’s always about making the human interaction more efficient, because in many of these cases, there’s still a customer service rep,” says Rob Thomas, senior vice president of IBM’s Cloud and Data Platform, in a recent Yahoo! Finance video. “But AI is making them more productive, making them better at solving the problem.” This means “virtual assistants can respond to customer needs with minimal employee input,” according to AI News. “A straightforward means of increasing productivity, the time and effort spent on generic customer queries is reduced, freeing up teams to focus on longer-term projects that drive innovation across the business.”
Reducing the need for repetitive work/process automation
AI can automate repetitive mundane, time-consuming tasks, such as reviewing documents or pulling information from applications, which will free up employees to tackle other projects.
Reducing false positives and human error
People make mistakes, and human error is an unfortunate reality. In the financial services industry, 94% of surveyed IT professionals said they aren’t confident that their employees, consultants and partners can safely protect customer data. Thankfully, artificial intelligence can help reduce false positives and human error.
Ability to execute tasks of any length
Artificial intelligence has the ability to scale, meaning that you can use this type of advanced technology for short- or long-term projects.
Making smart underwriting decisions
AI solutions are helping banks and lenders “make smarter underwriting decisions” when it comes to the approval process for loans and credit cards, according to Built In. This is done by using a variety of factors that paint a more accurate picture of those who may be traditionally underserved.
Save money
Every item previously mentioned on this list can contribute to increased revenue. By automating tasks, you free up employees to take on additional responsibilities instead of hiring more personnel. Virtual assistants and 24/7 chatbots create a more positive customer service experience, and using AI to help determine whether someone qualifies for a loan typically means finding those with good credit who won’t default.

Examples of Financial Firms That Are Using AI

According to Forbes, 54% of financial service organizations with 5,000+ employees are using artificial intelligence. Here are some examples:

Capital One: “Eno” was the first natural language SMS text-based assistant offered by a bank in the United States.
Bank of America: The chatbot “Erica” debuted in 2018 and has served more than 10 million users. As of mid-2019, Erica was able to understand almost 500,000 question variations.
JPMorgan Chase: The bank uses key fraud detecting applications, including implementing an algorithm to detect fraud patterns, according to Business Insider. Details of credit card transactions are sent to data centers, which decide whether the transactions are fraudulent.
Kensho: According to the company’s website, Kensho builds analytical products used by some of the world’s leading financial institutions, including Goldman Sachs, Bank of America, Merrill Lynch and JPMorgan Chase.
Alphasense: This is “an AI-powered search engine for the finance industry … [serving] clients like banks, investment firms and Fortune 500 companies,” according to Built In. The platform uses natural language processing to analyze keyword searches and discover trends and changes in the markets.

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Ethics in AI in the Finance Sector

Artificial intelligence does not come without some ethical challenges, especially when it comes to protecting your personal and financial information. The Fintech Times highlights three areas of concern when it comes to AI in the finance sector:

Bias: AI failures can happen, and in many cases, it’s a problem with the algorithm. Here’s an example from The Fintech Times: “If an AI system calculating the creditworthiness of a customer is tasked to optimize profits, it could soon get into predatory behavior and look for people with low credit scores to sell subprime loans. This practice may be frowned upon by society and considered unethical, but the AI does not understand such nuances.”
Accountability: Who is responsible if artificial intelligence makes an incorrect decision? For example, who should be at fault if a self-driving car gets into an accident?
Transparency: How and why do algorithms come to particular conclusions? It’s not always easy to tell.

There’s also the idea often associated with artificial intelligence that robots will soon replace human workers. Forbes explains that while research shows that AI will replace certain categories of jobs, businesses and companies will be freed up to take care of other higher value responsibilities.

Another ethical concern, according to Investopedia, is the idea of “weaponized machinery” — whereby the use of artificial intelligence and machine learning tools are employed for unethical purposes, such as hacking into people’s private information.

The Future of AI in Finance

Since artificial intelligence has become more widespread across all industries, it’s no surprise that it is taking off within the world of finance, especially since COVID-19 has changed human interaction. By streamlining and consolidating tasks and analyzing data and information far faster than humans, AI has had a profound impact, and experts predict that it will save the banking industry about $1 trillion by 2030.

“Artificial intelligence technologies are increasingly integral to the world we live in, and banks need to deploy these technologies at scale to remain relevant,” according to McKinsey & Company. “Success requires a holistic transformation spanning multiple layers of the organization.”

It’s also important to note that millennials and “Gen Zers” are becoming the banks’ “largest addressable consumer group” in the United States, which means financial institutions are looking to increase their IT and AI budgets “to meet higher digital standards” since younger consumers often prefer digital banking. In fact, 78% of millennials say they won’t go to a bank if there’s an alternative.

AI in Finance Also Means New Career Opportunities

High-paying career opportunities in AI and related disciplines continue to expand in nearly all industries, including banking and finance. If you’re looking for a new opportunity or a way to advance your current career in AI, consider the University of San Diego — a highly regarded industry thought leader and education provider. USD offers an innovative, online AI master’s degree program, the Master of Science in Applied Artificial Intelligence, which is designed to prepare graduates for success in this important fast-growing field. This program includes a significant emphasis on real-world applications, ethics, privacy, moral responsibility and social good in designing AI-enabled systems.