The role of (AI) artificial intelligence in finance is diverse and dynamic. It is considered a game changer in the industry by streamlining operations, assisting customers, predicting future trends, and enabling data-driven decision-making across all levels.
According to Statista, the AI in the FinTech market is estimated to be $44.08 billion in 2024 with a CAGR (compound annual growth rate) of 2.91% to cross $50 billion by 2029. The statistics show that many financial establishments are adopting AI and ML solutions to offer better services to customers. Additionally, AI in finance can be used for several other activities like automation, customer service, fraud detection, etc.
In this blog, we’ll look at how AI is impacting the financial markets and has a vital role in revolutionizing trading.
Role of AI in Financial Markets
Risk Management:
Risk is one of the biggest concerns for financial institutions. It can be in terms of customers, market uncertainties, defaulters, fraudulent transactions, cyberattacks, etc. Artificial intelligence can be used to measure, predict, and neutralize various risk factors. This is done through data analytics and business intelligence where large amounts of data are analyzed to identify weak areas. Similarly, establishments can use AI-based security software to strengthen their system security and prevent hackers from accessing their sensitive information.
Predicting Market Trends
Another reason to use artificial intelligence is for leveraging data in finance and predicting upcoming market trends using advanced analytics. The financial and stock markets are highly volatile and often prone to ups and downs. Powerful predictive analytical tools can be deployed to determine market trends based on current and historical data. This will help the business and its customers make data-driven decisions to minimize losses and increase their revenue. AI and ML applications in finance can identify hidden patterns and trends in large datasets to derive insights in real-time.
Fair Lending Practices
Financial lending establishments use credit scores to determine the risk quotient of lending money to an applicant. They use proprietary models to calculate the interest rate and other terms of the agreement to offer a loan to a person. The process is usually not transparent as each establishment follows a different model. By adopting AI tools, the industry can streamline the process and make it more transparent. It can lead to fair lending practices and increase the chance for applicants to get approved for a loan, especially those who are declined by following conventional/ traditional methods.
Compliance with Industry Regulations
The financial industry regularly assesses and updates the regulations to ensure better services to the public. Every institution and financial company in the sector has to adhere to these guidelines and regulations. AI can make this easier through automation. By automating the recurring processes and monitoring the transactions, banks and other financial institutions can ensure compliance with industry regulations. Automation also reduces the risk of human error and increases overall efficiency.
Enhanced Customer Experience
AI in the financial markets can be used to provide better and high-quality services to customers. For example, AI chatbots can provide real-time assistance to customers 24*7. Trading platforms can use bots to help traders make decisions based on data-driven insights. Financial companies can set up automated processes for various transactions like recurring payments (credit, debit, etc.) Better customer experience results in greater satisfaction and creates brand loyalty in the market. This establishes the financial institution as a popular and reputed service provider.
Greater Operational Efficiency
We cannot ignore the role of AI in streamlining day-to-day operations in a company. Many banks, insurance, credit card, and lending companies hire third-party AI service providers to set up seamless data flow and integrations between different applications used by their employees. This allows managers and decision-makers to access analytical insights through customized dashboards and make faster and more efficient decisions in real time. Adopting AI for operational efficiency also results in cost and time savings for the company.
Benefits of AI in Trading
AI in trading is gaining prominence as new trading platforms enter the market. Many latest trading and crypto exchanges use artificial intelligence to offer enhanced services to users. Let’s check out how AI can be useful in stock trading.
Advanced Analytics
Artificial intelligence algorithms are powerful and can process huge amounts of data in quick time. This allows investors and traders to make immediate decisions based on data-driven insights instead of guesswork.
Algorithm Trading
AI has massively transformed algorithm trading which used to rely on mathematical models and preset rules. With the advancement in technology, trading platforms can use artificial intelligence to analyze trends, sentiments, market swings, and several other factors far more efficiently.
Fraud Detection
Fraud detection is one of the common ML applications in the finance and trading sectors. The algorithms are trained to detect anomalies and unusual trading patterns. The application sends an alert, enabling the financial company to monitor the situation and block doubtful/ fraudulent transactions.
Better Investment Strategies
A volatile stock market demands investors to think on their feet. At the same time, they should have a proper investment strategy to earn profits. AI can help even novice investors develop strategies for choosing the right stock and identifying the correct time to make the move.
Discovering Hidden Patterns
In today’s technologically advanced world, several trading platforms (stock, hedge funds, crypto, etc.) use artificial intelligence to uncover hidden patterns based on data from stock markets. This gives the platform a competitive edge to take advantage of market opportunities.
Greater Accuracy
AI-based data analysis can be more accurate than manual analysis. Moreover, it is fast and provides reports in real time. Investors can forecast the upcoming market trends and plan their trading options to maximize returns.
Cost-Efficiency
By automating many processes using artificial intelligence, trading platforms can optimize resources and reduce operational costs in the long run. Though setting up the initial infrastructure will require money, it is a worthy investment that delivers ROI over the years.
Conclusion
AI in financial markets will continue to play a prominent role in enhancing customer experience, increasing operational efficiency, optimizing resources, and reducing costs. It can help companies and customers make better decisions based on data-driven reports.
Third-party service providers like Pro Minds AI Labs offer end-to-end solutions to set up artificial intelligence models in financial companies and help them achieve their business objectives. The solutions are tailored to suit the requirements of each client and deliver guaranteed results.