How To Use AI In Finance

• Hugh O'Neal
• October 24, 2022

Artificial intelligence (AI) and machine learning in finance cover everything from chatbot assistants to fraud detection and task automation. According to the Insider Intelligence AI in Banking report, most banks (80%) are well aware of the potential benefits of AI. The decision of financial institutions (FIs) to adopt AI will be accelerated by technological advances, greater user acceptance, and changing regulatory frameworks. Banks using AI simplify tedious processes and significantly improve the customer experience by offering 24/7 access to their accounts and financial advisory services.

General information about AI in finance

Artificial intelligence leads to significant cost savings. According to an Accenture study, banks use AI banking tools to increase their transactions by 2.5 times with the same staff. And financial services companies are well positioned to use artificial intelligence. Without data, AI in banking is impossible. But the financial industry collects a lot of data in the ordinary course of business. Admittedly, using artificial intelligence and machine learning in finance is nothing new. Artificial intelligence is responsible for detecting suspicious credit card transactions. With identity theft on the rise, the sector needs to use the right technology to protect its customers and reduce liability. As the mode of operation becomes virtual, vulnerabilities in financial systems are exposed. In the past, bank robbers wore ski masks and carried guns; these days, criminals use code and keyboards. The only method to combat technological threats is to use better technologies. AI enables financial institutions to create a friendly customer experience, reduce employee errors and increase investment efficiency. Intelligent Decision Management Systems (DMS) help an institution meet requirements by reducing errors, and the time it takes to capture customer information accurately. However, a proper assessment of AI in banking and financial services would be incomplete without examining some misconceptions about AI. The myth is that machine learning is as good as human intelligence. In addition, even where artificial intelligence surpasses human capabilities, such as using multiple variables to predict outcomes, the costs often outweigh the benefits.

How to use AI in finance?

Artificial intelligence has become a real breakthrough in the world of finance. An AI system analyzes millions and billions of data points, finds patterns and trends that humans might be missing, and even predicts future patterns. You can use artificial intelligence and natural language processing to create conversation trees that allow customers to communicate and perform specific actions in a chat or a voice application. Here are some options to use AI in finance:

• Risk assessment. Can artificial intelligence be used to determine if someone qualifies for a loan? Banks and apps employ machine learning algorithms to determine a person’s eligibility for a loan and provide personalized options.
• Risk management Risk mitigation is always an essential task in banking. Now, machine learning helps experts use data to spot trends, identify risks, save labor, and get better insights for future planning.
• Fraud detection, fight, and prevention. Have you ever received a call from a credit card company after making a few purchases? Fraud detection systems identify a person’s buying behavior and trigger an alert if something seems out of the ordinary or goes against your traditional spending patterns using AI.
• Credit decisions. Artificial intelligence quickly and more accurately evaluates a potential customer based on various factors, including smartphone data (plus, machines are not biased).
• Financial advisory services. Try to stay up to date with the latest economic trends. Are you interested in a portfolio review? Artificial intelligence algorithms analyze a person’s portfolio to get the information they need quickly.
• Trade. Since artificial intelligence helps to analyze patterns in large datasets, it is not surprising that it is often used in trading. AI computers can sift through data faster than humans, speeding up the entire process and saving large chunks of time.

Each element mentioned on this list can contribute to an increase in income. By automating tasks, you free up employees to perform additional duties instead of hiring other staff. Virtual assistants and chatbots working around the clock create a more positive customer experience.

Advantages of using artificial intelligence in the financial industry

Artificial intelligence automates routine manual tasks, helps prevent fraud, and improves the overall customer experience, to name a few benefits. Here we look at AI’s main benefits to a financial services organization.

• A better understanding of financial data. AI can provide a financial company with a better experience of financial data. It will help them plan a constructive approach that will benefit them and their clients.
• Work faster. Since AI ​​works in real-time, it works faster than conventional manual processes. Earlier manual processes required some time to consider various aspects when deciding. Automation following the requirements can give results and predictions in a few seconds. Here, too, a difficult decision can be made with great ease.
• Less cost. The introduction of AI reduces the need for human experts to work. It reduces the cost of doing the necessary work and making critical management decisions. Companies must create the required algorithm to help them easily accomplish the desired work.
• Compliance and elimination of fraud in the process. Regulatory compliance is one of the top priorities for any financial industry. Failure to do so may result in financial penalties, suspension of certain operations, risk of instability in the process, etc. AI ensures security and compliance and eliminates fraud in the process. It can work according to the criteria specified in the algorithm.
• Work with big data. One of the great benefits of AI is its ability to process big data. It can process extensive data simultaneously, far superior to the manual process.

Soon, companies can be expected to rely on AI to make critical firm-related decisions. AI also determines how customers will react to different situations and challenges. Artificial intelligence will help people and businesses make more intelligent decisions quickly. However, the key here is to find the correct balance between people and machines.

Main ways how AI changes the financial sector

With the advent of AI, routine tasks have to some extent, given way to technology, which has revolutionized the way work is done in an organization. Finance is no exception: technical solutions have become the basis for many of its operations. No one has the time or patience to handle manual checks and the dangers of erroneous data in their operations.

• AI in personal finance: consumers want financial independence, and empowering them to take control of their financial health is the driving force behind the adoption of AI in personal finance. Whether it’s 24/7 financial guidance through natural language processing-based chatbots or personalizing information for wealth management solutions, AI is essential for financial institutions aspiring to become leading players in the industry.
• AI in consumer finance: the essential business case for AI in finance is its ability to prevent fraud and cyber attacks. According to Insider Intelligence, consumers are looking for banks and other financial services to provide secure accounts, especially as losses from online payment fraud are expected to rise to $48 billion annually by 2023. AI can analyze and identify irregular patterns that would otherwise go unnoticed by humans.
• AI in corporate finance is beneficial as it better predicts and evaluates credit risks. Artificial intelligence tools such as machine learning can help improve loan underwriting and reduce financial risk for companies looking to increase their value. AI also reduces financial crime through enhanced fraud detection and anomalous activity detection as company accountants, analysts, treasurers, and investors work towards long-term growth.

The US Bank uses AI in both its middle and back office applications. US Bank unlocks and analyzes all relevant customer data using deep learning to help identify intruders. According to an Insider Intelligence report, such technology has been used to combat money laundering and has doubled the performance of the traditional capabilities of previous systems.

AI challenges in finance

Artificial intelligence is not without ethical concerns, especially when protecting your personal and financial data. The Fintech Times highlights three spheres of concern when it comes to AI in the financial sector:

• Bias: AI glitches can happen; this is a problem with the algorithm in many cases. Here is an example from The Fintech Times: «If an AI system that calculates a customer’s creditworthiness is tasked with optimizing profits, it may soon become predatory and look for people with a low credit score to sell subprime loans. Society may frown upon such practice and consider it unethical, but AI does not understand such nuances».
• Responsibility: who is responsible if artificial intelligence makes the wrong decision? Who should be to blame if a self-driving auto gets into an accident?
• Transparency: how and why do algorithms come to certain conclusions? It’s not always easy to say.

There is also the idea, often associated with artificial intelligence, that robots will soon replace humans. Forbes explains while research shows AI will replace specific categories of jobs, businesses and companies will be freed up to take on other more important responsibilities.

Some good examples of companies using AI

According to Forbes, 70% of financial companies use machine learning to predict cash flow events, adjust credit ratings, and detect fraud. AI is also radically changing the working model of the financial services industry. Let’s look at some of the most successful examples:

• Capital One: «Eno» was the first natural language SMS text assistant offered by a bank in the United States.
• Bank of America: Chatbot “Erika” debuted in 2018 and has served over 10 million users. As of mid-2019, Erica could understand nearly 500,000 question choices.
• JPMorgan Chase: The bank uses critical fraud detection applications, such as implementing an algorithm to detect fraud patterns. Credit card transaction information is sent to data centers to decide if the transactions are fraudulent.
• Kensho: Kensho, a company of S&P Global, provides machine intelligence and data analytics to leading financial institutions such as JP Morgan, Bank of America, and Morgan Stanley. Kensho’s software offers analytics solutions using a combination of cloud computing and natural language processing, providing easy-to-understand answers to complex financial questions and quickly extracting information from spreadsheets and documents.
• Alphasense is an artificial intelligence search engine for the financial industry that serves clients such as banks, investment organizations, and Fortune 500 companies. The platform utilizes natural language processing to detect keyword searches in documents, transcripts, research, and news to detect changes and trends in the financial markets.

As pressure builds on financial institutions to cut commission rates on individual investments, machines do what humans don’t: work for a single down payment. Another growing area is bionic consulting, which combines machine computing and human understanding to provide options that are much more effective than their components.

The future of AI in the finance

It’s no wonder AI is gaining momentum in banking, especially now COVID-19 has changed human contact. AI has had a considerable impact, simplifying and unifying activities and processing data much faster than humans. According to Business Insider Intelligence’s Autonomous Next study, the cumulative potential cost savings through AI applications is estimated at around $447 billion by 2023, with the front and middle office accounting for $416 billion of that amount. It’s also worth noting that millennials and Gen Z are fast becoming the «largest customizable consumer group» of banks in the United States. Financial firms want to increase their IT and AI spending «to meet higher digital standards». About 78% of young people say they won’t use a bank if there is an alternative.

Final words

Without a shadow of a doubt, AI is the future of the financial industry. Given the speed with which it is taking progressive steps to simplify the financial processes, it will soon replace people and offer faster and much more effective solutions. Bots are gradually evolving as AI innovations emerge. Significant investments are made by firms that see it as a long-term investment to cut costs. It helps companies save money on hiring people and also avoid human error in the process. While the pace at which the financial sector is evolving is still in its infancy, the outlook can be expected to lead to more minor losses, smarter trading, and top-notch customer service.