How Is AI Used in Finance?

AI has been successfully deployed in the financial sector but how is it utilized today? Learn more about its many use cases.

Twelve Leading AI Use Cases in Finance

Artificial intelligence has already emerged as a powerful force in the finance industry thanks to the new solutions it offers, many of which increase efficiency, improve decision-making, or deliver customer service. With applications in everything from detecting fraud to developing individually tailored investment strategies, AI in the financial sector is already greatly altering many processes from transaction processing and fraud detection to risk analysis and trading decision-making, among others. By cutting down on repetitive functions and sifting through huge volumes of data, AI minimizes the chances of errors while enhancing output across different areas of finance. Check out these use cases in which AI is changing the landscape of finance for the better.

1. Fraud Detection and Prevention

AI-based systems are able to detect fraud by rapidly analyzing transactions for suspicious activities. AI systems can be trained to assess customer behavior in real time and identify potentially suspicious activities or transactions such as unusual spending patterns and attempts to access accounts from unauthorized locations. AI-powered fraud detection relies on high-performance computing solutions, like those from Supermicro, to analyze vast transaction datasets instantly and detect anomalies with minimal latency. AI is also used by financial institutions to detect new types of fraudulent schemes and prevent them. Furthermore, it helps in increasing the overall conversion of fraud detection processes, securing the company's assets and customer confidence.

2. Personal Finance Management

AI has revolutionized personal finance by powering smart budgeting apps and tools. These systems are capable of tracking spending, classifying expenditures, and giving necessary financial advice so that the users can reach their saving targets. AI also makes users aware of irregular expenditures and recommends more cost-effective alternatives, such as lower-interest loans or budget-friendly subscription plans, which enhances financial management. Such features coupled with real-time information and forecast algorithms easily avail tailor-made solutions which allow people to make wise decisions and develop sound financial habits.

3. Algorithmic Trading

AI plays a pivotal role in algorithmic trading today. It enables rapid data analysis to execute trades at the most opportune times. Essentially, such algorithms are constantly monitoring price and market conditions and as soon as a change in price is forecasted, an action to change the state of the market is performed. With very low latencies, AI can make near-instant decisions on whether to trade or hold, ensuring optimal timing for maximum returns. In this way, the chances of loss are minimized while controlling the return on investment. 

4. Credit Scoring and Loan Underwriting

When it comes to credit scoring, AI is able to access and analyze data from various social networks and payment activities. This means AI-trained models integrate machine learning into the model to assess credit risk and hence make better lending decisions. With AI technology, a risk assessment can also be done whereby the technology studies documents submitted for evaluation. Due to AI's increasing accuracy and efficiency, fair decisions can be made in a short period of time.

5. Regulatory Compliance and Reporting

The inherent nature of financial regulations necessitates high levels of accuracy. The automation that AI provides achieves just this outcome. Through AI tools, any transactions that breach compliance are flagged, and as new regulations are created, the tools are able to adjust and track market behavior. Regulatory requirements are more easily met through modern language technology, as it extracts useful information from legal documents while wiping out the need for human scrutiny. By performing work such as that, AI increases precision but at the same time helps institutions adapt to regulation changes with minimal disruption and compliance risks.

6. Wealth and Portfolio Management

Investment advisors now have the luxury of doing their work aided by technology. Robo-advisors can leverage machine learning techniques, for example,  to assess client goals, and risk tolerance, not to mention market trends. As such, they provide truly data-driven investment strategies. AI also monitors portfolios in real-time, identifying opportunities for optimal investment performance. Clients will, therefore, always be able to find customized investment solutions that fit any market regardless of volatility.

7. Customer Service with Chatbots

AI-driven chatbots are transforming customer service in finance by offering instant, 24/7 assistance. Using natural language processing, AI-powered chatbots will continue to assist customers in retail banking, insurance, real estate and other industries for some time to come. Chatbots already automate many tasks where human insight or diving into details is not essential. Since they typically save time for customers, they are a big part of the picture in numerous financial industry sub-sectors. For a deeper dive into AI’s role in financial services, including customer engagement, Supermicro’s webinar on AI-optimized infrastructure provides valuable insights into real-world applications.

8. Risk Management and Stress Testing

AI is a powerful tool for risk management. It means financial institutions can better predict and mitigate potential threats. Predictive models and scenario analysis tools are utilized to stress test assets and prepare them for market downturns or even recession influence. Such AI-driven risk assessments rely on high-performance computing solutions to process complex financial models and simulate stress scenarios with precision. Also, AI looks for vulnerabilities in the financial systems and provides appropriate information for improvement. By incorporating data into decision-making processes, the institutions are able to take measures that will protect their business from risks as well as maintain stability in turbulent times

9. Insurance Claims Processing

Today, AI expedites the process of filing insurance claims through the use of automated policy documents. The machine learning-based algorithms will review and analyze the images and data of the claims in order to settle them efficiently and accurately. Software can support indicators and features of non-genuine claims. These efficiencies, brought about by AI, significantly reduce the time taken to process claims and improve the satisfaction of policyholders.

10. Expense Management for Businesses

Businesses benefit from AI-powered tools designed to simplify expense management. These systems greatly reduce workloads by automating invoice processing. AI also provides expense analysis, allowing companies to understand how effective they are in terms of spending and where they can cut costs. More widely, AI empowers businesses to maintain financial control and make data-driven decisions for improved operational efficiency.

11. Anti-Money Laundering (AML) and Know Your Customer (KYC) Processes

AI significantly eases AML and KYC processes. Among other methods, it does so by detecting suspicious activities and verifying customers. For instance, machine learning algorithms analyze customers’ transaction histories for abnormal or suspicious transactions that might be attempts at money laundering. Additionally, AI makes the completion of KYC requirements easier since AI discriminates and cites information from customers' documents using optical character recognition (OCR). 

12. Predictive Analytics for Market Forecasting

Predictive analytics powered by AI assists financial companies in their forecasting of market developments with improved reliability. Using historical data, and economic indicators, AI algorithms make predictions about asset performance and market movements. These forecasts, which often depend on high-performance AI infrastructure, such as Supermicro’s AI-optimized solutions, help investment managers to decide how to adjust their portfolio strategies for optimized outcomes. Likewise, predictive analytics helps financial organizations in spotting new opportunities and dangers which reinforces their action strategies in agreement with the ever-changing nature of the market.

Additional Resources:

• AI Solutions for Financial Services
• How AI-Powered Solutions Accelerate Financial Services
• White Paper: How AI is Propelling Innovation in Financial Services
• Datasheet: AI in Financial Services - Unlock Growth Opportunities