Artificial Intelligence in Finance: Applications and Benefits

Artificial intelligence is the technology that has human abilities for problem-solving. People use machine learning algorithms, neuro-linguistic programming (NLP), and computer vision in healthcare, education, insurance firms, logistics, and other businesses. The financial sphere can also benefit from AI. Smart systems help people with calculations, data analysis, and forecasting. 

What is AI in finance?

Artificial intelligence helps with numerous operations in the financial domain. AI can assist in performance assessment, data analysis, mathematical calculations, pattern predictions, customer service, and more.

How is AI used in finance?

According to Statista, the global AI market in finance expects 28% growth between 2023 and 2032. It means AI technologies will continue taking on routine and repetitive activities, allowing people to make complex decisions and innovate. Currently, AI is used in numerous spheres of financial business.

Predictive Data Analytics

Predictive analytical programs examine historical data while assessing risks in mortgage and loan underwriting. Algorithms explore financial data and evaluate credit history, income, debts, cash reserves, etc. Then, underwriters or AI assistants check if the amount of money a person wants to borrow is adequate for the price of the dwellings they are planning to purchase. The advantage of applying AI is that computers can make an unbiased decision about someone’s loan eligibility.

Security and fraud detection

Data security presupposes continuous and repetitive data checks to identify suspicious activities. Those suspicious interventions may lead to cyberattacks, data spills, money laundering, and other serious crimes. J.P. Morgan Chase implemented a similar solution to identify fraudulent activities in time. The central office receives data about each transaction and checks if it meets security requirements.


AI technologies in trading involve machine learning, NLP, sentiment analysis, and other algorithms that help create a multilateral approach to market forecasting. Such an approach allows for accurate analysis, minimized risks, and optimal stock pricing. Methods of exploiting AI in trading vary depending on the type of trading. For instance, high-frequency trading demands systems with reactive replies; arbitrage trading relies on price fluctuation analysis, and algorithmic trading involves deep analysis of historical data.

Personal finances

Virtual assistants can help manage personal finances and save money for long-term goals. Modern applications help monitor costs and track income, suggest ideas on how to improve patterns, and start saving for the future. Such apps classify expenses and offer credit cards and financial products that fit spending habits. They may also provide automated savings possibilities and investment consultations.

ERP systems

An enterprise resource planning (ERP) system is software that companies use to manage their accounting and financial operations connected with supply chains, analytics, and others. Traditionally, the information is put into the ERP manually. With time, rule-based automation appeared, which passed a part of the routine tasks to the computer. However, those systems were still slow in updating and required much human control. AI technologies have brought relief to office staff. Machines cope with data verification, reporting, and analysis. They can digitize paper invoices, extract the necessary data, and even send requests if any information is missing.

Customer interactions

Chatbot implementation enables banks and insurance firms to speed up customer interaction. Chatbots are available 24/7. They can help with due dates, transaction statuses, deposit information, and other requests. The first SMS chatbot that used natural language processing was Eno. Clients of the Capital One bank could ask Eno any questions regarding their accounts, such as checking the balance, the latest transactions, paying bills, etc.

Benefits of AI in finance

  • Automated systems tackle mundane tasks. They eliminate manual work and allow the staff to devote time to optimizing workflows or developing any new inventions. Humans can think and create while computers work.
  • AI technologies complement humans. Deep analysis of the information, data extraction, and summarizing aid people in their decision-making processes. Besides, chatbots can manage simple customer questions, such as checking the balance or informing clients of the bank’s working hours.
  • AI technologies make processes faster. Financial audits and month-end closes happen quicker and with reduced stress for the accountants and analysts. Besides, exploiting modern technologies at work increases the expertise of the staff.
  • Computers make fewer mistakes in document processing. However, this advantage will work only if the initial historical data that algorithms use is flawless.
  • Cutting-edge technologies demonstrate business modernity and improve performance. AI can indicate more profitable areas for business development and enhance workforce planning. According to figures, the banking industry can increase profit by 9 to 15% if it utilizes AI technologies.

Challenges of AI in finance

Investing huge sums into AI development is not enough to be on the wave of innovation. According to Gartner, only 24% of companies claim their digital investments have paid off.

How to address this issue? The expert from the Belitsoft software development company, Dmitry Baraishuk, claims that it is important to estimate the opportunities for business and the IT sector before any investment. On the one hand, companies should examine their legacy software, current business trends, and their ability to cope with new demands. On the other hand, IT experts should report on the risks of using obsolete programs and their maintenance costs. The IT department also has to assess the complexity of the new software for the staff. If both sides agree on the necessity of new software for the company, it is reasonable to realize this project.

One more challenge is the quality of historical data. AI uses it to build its predictions and make trustworthy analyses. Controversial or insufficient input data may lead to flaws in forecasts.

How to address this issue? It is a human who has to check the information and streamline the processes to make AI work in a team. Make sure your staff is competent enough to set up the AI technologies and “teach” them.


Gen Z is the fastest-growing target market for financial services today. Those young people dictate their vision and demands, and companies have to adapt rapidly. Gen Z fancies paying with smartwatches, using digital wallets, and consulting bots. Therefore, applying cutting-edge technological progress is a must if financial businesses wish to hold their customers. 

Artificial intelligence is a tool that makes the financial business run smoothly. It tailors financial products and services to the needs of customers and plays a vivid role in forming the business landscape.

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