According to Mercer, AI use among asset managers has increased from 55% to 91% in just two years. If this isn’t a testament to the growing influence of AI in finance, we don’t know what is. As per the testimonials of executives in finance, AI not only help them do their work, but also helps them do it better by exploring every possible avenue, some they haven’t even thought about yet.
But let’s be real, AI isn’t all sunshine and rainbows; there are some dark parts you should also understand. The benefits and risks. In this blog, we will explore real-world uses of this technology in finance, along with its benefits, challenges, and future trends.
Core Technologies Behind AI in Finance
Several technologies sit under the AI umbrella, and each solves a different financial problem. Think of it as an organic body: unlike a machine, which comprises parts working in isolation, AI infrastructure in finance works in conjunction with other components.
Machine learning picks up on patterns and learns from them to help banks understand loan risk and better understand their customers. Deep learning allows fraud to be detected by identifying unusual patterns. NLP enables AI to understand text and speech, improving the usefulness of chatbots. Reinforcement learning allows the AI to learn from its mistakes to improve decision-making. Computer vision lets the AI read images and documents, whilst generative AI can help create reports and useful financial data.
9 High-Impact Use Cases of AI in Finance
Fintech rules around the world differ, and these “high-impact” use cases may vary. So, don’t put us on trial if things are different.
Fraud Detection and Prevention
AI helps banks detect fraud by monitoring customer transactions. It can quickly spot unusual activities, such as a large payment from another country and alert the bank before money is lost. Unlike traditional systems, it can learn about new fraud methods and improve its detection over time.
And do you know that a 2025 report from Feedzai said 90% of financial institutions use AI to speed up fraud investigations and detect new fraud methods?
Credit Scoring and Risk Assessment
AI in finance also helps banks decide whether a person is likely to repay a loan. It looks at details like income, credit history and bill payments. This can also help people with limited credit history get better access to loans.
You will be shocked to know that AI-based credit scoring can help increase loan approvals, reduce risks and make lending decisions fairer when trained on good-quality data.
Algorithmic and High-Frequency Trading
It also helps traders study market prices, news and past data to make faster trading decisions. It can process large amounts of information in seconds, which is difficult for humans to do.
You will be shocked to know that trading companies use AI to study market changes, find opportunities and manage investment risks.
Portfolio Management and Investment Research
AI in finance helps investors and asset managers understand market trends and choose suitable investments. It studies large amounts of data and helps them decide where to invest their money.
You will be shocked to know that Mercer’s report once said that 91% of asset managers use or plan to use AI, compared to 55% in 2023.
Benefits of AI in Finance
AI helps financial institutions work better, faster and smarter and here are some benefits that you should know:
Better Risk Management
AI can look at data all the time to spot danger signs like fraud or risky loans before they turn into big losses.
Saving Time and Money
This is the most obvious of the bunch. You don’t have to pay employees to do the same old paperwork. For example, IBM used AI to cut its paperwork time by over 90% and save $600,000 a year.
Personal Service for Everyone
AI isn’t like a colleague who says the same thing to everyone. It’s a system of neural networks that understand how to treat different people accordingly.
Handling More Work Easily
One of the best use cases of AI anywhere is the ability to scale. For example, Bank of America’s virtual assistant, Erica, has handled over 2 billion customer chats. You need a sea of people if you go down the traditional route.
Risks of AI and How to Fix Them
Life isn’t always sunshine and rainbows. This is especially true for AI applications. Among the immense benefits, some grave disadvantages also need attention.
Unfair Choices
If the AI is not trained with fair data, then it can make unfair choices. Such as refusing someone a loan when they do not deserve to be refused. Customers will be unhappy and could get into legal issues. Companies could prevent this by testing the data, testing the AI on various groups, monitoring the AI regularly and making important decisions a human’s choice.
Black Box Problem
Some AIs do not provide explanations with their answers, meaning it can be difficult to explain your choices to customers and government officials. Companies should use an AI which provides explanations, documents how it works and use a simpler AI for important decisions.
Hacker Attacks
Hackers may target an AI system to steal confidential information or cause it to produce incorrect answers. This can cause serious issues for the company and customers. The company can prevent this by having strong security measures, regularly testing the system, and only allowing trusted individuals access to the data. They should also be looking for any unusual activity.
Also Read – Customer Retention Strategies: Keep Customers Coming Back
The Future of AI in Finance
The working of way banks, financial companies and investors work has changed as AI in finance makes its entry into the market. It helps save time, reduce costs, detect fraud, manage risks and provide better customer service. However, it also comes with challenges such as unfair decisions, privacy issues and cyberattacks. Companies must use AI carefully, protect customer data and make sure humans are involved in important decisions. In the future, AI will play an even bigger role in the financial industry. Businesses that use AI in the right way can work smarter, serve customers better and stay ahead in the growing digital world.
FAQ:
1. Which AI is Used in Finance?
AI in finance supports accounting, trading, and research. ChatGPT helps with reports and queries, Claude with document analysis, and Gemini with data analysis through Google Sheets.
2. How does JP Morgan Use AI?
JPMorgan Chase uses AI and machine learning across its operations, with hundreds of active applications to boost productivity, detect fraud, and support wealth management.
3. Which AI is Best For Banking?
The best AI for banking depends on the task, whether it’s financial modelling, credit scoring, fraud detection, or customer service. No single AI tool is best for everything.
