AI can be integrated into various sectors, and finance is no exception. AI in the finance is already transforming this field by providing businesses the opportunity to operate more precisely, efficiently, and more reliably. In this article, we will analyse how machine learning is changing this industry and the value it brings to financial services companies and their customers.
What is AI in the Finance Sector?
When we focus on the financial industry, we can see that machine learning and advanced algorithmic solutions are being adapted for data analysis, task automation, and decision-making. AI in the finance is inevitably improving business efficiency in the financial market.
This market is modernizing with innovative solutions, enabling a better understanding of financial markets, the integration of unique client attraction strategies, and more. The most important aspect remains that all these solutions are reliable because they are powered by analysis of large data sets.
In 2021, the AI market value in the financial sector reached $9,45 billion USD. It is believed that by 2030, this market could grow by 16.5%. These statistics show that AI’s value in this field is significant.
In general, there are five key AI applications in the financial sector:
- Product or service personalization.
- Creating new opportunities.
- Risk and fraud control.
- Ensuring transparency.
- Reducing cost through operational automation.
All these solutions offer several benefits. First, task and process automation save business time, allowing customers to receive services faster. Also, data-driven recommendations are more reliable, reducing the risk of human error. Finally, AI in the finance improves operational efficiency, as systems can complete various tasks faster than human resources.
In Which Ways Can AI Be Used in the Finance Sector?
From a broader perspective, machine learning and its integration can be applied across various areas of financial services and products. Below, we will discuss some of the most popular AI applications:
- Credit evaluation. By leveraging AI in the finance tools, financial service providers can analyse not only a client’s financial situation but also their online behaviour, enabling them to make confident decisions regarding credit issuance. AI solutions like Ocrolus and Enova use machine learning to analyse customers’ financial actions and provide recommendations on loan eligibility.
- Improvement of customer service. AI chatbots or virtual assistants can operate 24/7. First, this allows clients to receive consultations on their inquiries at any time, immediately, or at least be directed to the appropriate specialist. Second, such solutions personalize the user experience in real time by focusing on their expectations.
- Detection of fraudulent activity. In a highly sensitive sector like finance, the risk of fraud and cyberattacks increases significantly. Threats such as illegal money extraction or data breaches pose serious risks, making prevention and robust security measures essential. AI solutions can monitor network traffic, analyse payment data, and identify emerging challenges in a timely manner.
- Personalized recommendations for clients. Another application of AI in the finance sector is the personalization of customer experiences. Various AI tools can analyse an individual client’s financial data and provide detailed reports or plans for managing personal finances, including spending patterns, potential risks, and saving strategies.
- Predictive analytics. In banking operations, predictive analytics can forecast economic crises, inflation, and currency fluctuation risks. It can also track market trends related to stock prices or other investment opportunities.
Final Thoughts
The application of AI in the finance sector enables financial service providers to remain competitive and innovative. Moreover, it creates new opportunities for risk management and reliability, allowing them to deliver high-quality services and products to their clients.
If you are interested in this topic, we suggest you check our articles:
- The Impact of AI in Stock Market Analysis: How Sentiment Analysis Transforms Investing
- Exploring the AI Impact on Industries: 5 Key Sectors
Sources: BuiltIn, Google Cloud, IBM
