What is AI in Finance?

With AI, banks can now consider factors other than your credit score when you apply for a loan. They look at your job history, bill payment habits, and even your social media activity to get a better idea of your financial situation. This helps them make decisions faster and more accurately. Plus, it means people with solid job security and good bill payment habits might have a better chance of getting approved, even if their credit score isn’t perfect. So, borrowing money has become quicker and more open to everyone. This AI in Finance blog, we will be covering the following topics:

• What is AI in Finance?
• How is AI used in finance?
• The Three AI-Powered Platforms Utilized by Fintech Companies in India
• Financial IT Companies Leveraging AI in Finance
• Tools Used in AI for Finance

What is AI in Finance?

AI in finance means using advanced technologies like machine learning, natural language processing, and data analytics to improve how banks and financial companies handle different tasks. These tasks range from assessing risks and detecting fraud to managing investments and providing customer service. By using AI, these institutions can do these jobs quicker and more intelligently, leading to better decision-making and smoother operations.

How is AI used in finance?

AI is really shaking things up in finance. It’s making banking tasks smoother and finding valuable insights in all the data, which is changing how and where investments happen.

1. Algorithmic Trading:

With machine learning, investment firms can study past market data to help them decide when to buy or sell in algorithmic trading plans. Imagine AI-powered robots analyzing lots of information about the stock market really quickly. They look for patterns and trends, like when to buy or sell stocks. This helps investment firms make fast decisions and make more money.

2. Fraud Detection:

Machine learning helps models learn from previous fraud cases to spot similar patterns and predict possible fraud as it happens. Then, these systems watch out for similar tricks in real-time, just like a smart security guard keeping your money safe. It watches all the transactions and looks for anything strange, like if someone suddenly spends a lot of money in a different country. If it sees something fishy, it alerts the bank to check it out and stop fraud.

3. Customer Service:

Banks use chatbots for customer service, utilizing Natural Language Processing (NLP) technology. Think of AI chatbots as helpful assistants on a website or app. They’re like virtual helpers that can answer questions, solve problems, and even help with things like paying bills. They use special technology to understand and talk to customers just like a real person would.

4. Credit Scoring:

Neural networks, with deep learning methods, examine complicated connections among various factors to make credit scores more precise. When you apply for a loan, AI looks into your financial past to see how you’ve handled money. It checks if you’ve paid bills on time, how much debt you carry, and if there have been any loan problems. Based on this data, AI gives you a score, and lenders then use this score to decide if they’ll give you a loan and at what interest rate. If you’ve been good with paying bills and have a perfect credit score, you’ll likely get approved for a loan with lower interest.

5. Application Processing:

Using Machine Learning, models study old application data to make decisions automatically and make the process of applying for things like loans faster and smoother. When you apply for a loan, AI helps speed up the process by handling a lot of the paperwork. It reads through documents like bank statements, pay stubs, and identification cards using a special technology called Natural Language Processing (NLP). This allows AI to quickly extract important information, like your income or address, without needing a person to go through each document manually. By automating tasks like data entry and verification, AI makes the loan application process faster and more efficient for both applicants and lenders.

6. Cost Reduction:

With predictive Analytics, AI algorithms analyze historical data to forecast future trends and optimize resource allocation, helping financial institutions minimize costs and improve efficiency. AI helps save money by using robots to do tasks that would normally require people. This includes handling data, helping customers, and managing risks. By doing these tasks more efficiently, banks can save money in the long term.

The Three AI-Powered Platforms Utilized by Fintech Companies in India:

1. Digitap.AI: It helps people who are new to credit or have lower credit scores by using smart technology to assess if they can get loans or not.
2. Scienaptic: It makes financial transactions easier and faster by using smart computer programs to give helpful advice and predict the future.
3. Zaggle: It helps businesses keep track of their money and prevent cheating by using clever computer programs to spot problems and give good advice.

Some financial IT companies are leveraging AI in finance to innovate and improve their services. Moving forward, let’s discuss some of these companies that are Using AI in their financial task.

Financial IT Companies Leveraging AI in Finance

1. IBM uses AI to help financial organizations manage risks better by analyzing complicated patterns in transaction data. This includes keeping things secure, preventing fraud, following rules about money laundering, knowing who their customers are, and making sure they’re following all the rules.
2. Oracle, using AI technology, enables ERP systems to scan paper invoices automatically. The system then enters important details like the supplier’s name, items purchased, and costs. This helps detect fraud, manage accounts, and speed up approval processes.
3. Microsoft has developed a new AI chatbot called Copilot, designed specifically for finance workers using Excel and Outlook. This Copilot for Finance can perform some common tasks tailored to their roles right within these tools.
4. Even leading financial institutions like Paytm, HDFC Bank, and Bajaj Finance utilize AI.
5. Paytm, a top digital payment platform in India, uses smart AI to stop fraud and keep transactions safe. It also uses AI to improve customer service and give personalized advice.
6. HDFC Bank uses AI for many things, like helping customers with chatbots, predicting risks, and making smart investment decisions. It also uses AI to make getting loans easier and faster.
7. Bajaj Finance uses  AI algorithms to quickly decide if someone can get a loan and how risky it might be. They also use AI chatbots to help customers and give special offers to keep them happy.

Now that we’ve explored the various ways companies leverage AI in Finance let’s delve into the tools commonly employed in AI for financial applications.

Tools Used in AI for Finance

Many other companies are using AI in finance to come up with new ways of doing things, make customers happier, and make their businesses run smoother.

The Tools Used in AI for Finance are:

1. ChatGPT:

In finance, ChatGPT is used in several ways, such as in customer service, personal finance, market analysis, risk management, portfolio management, and financial education.

2. ClickUp:

ClickUp allows you to track financial goals, manage your accounts, and calculate your business profits.
It also provides a finance management template to help you track and monitor budgets, analyze your financial performance using tools like visual analytics, and collaborate with team members on financial planning.

3. Booke.AI: 

With Booke.ai, you can harness the power of real-time OCR AI to extract data from invoices, bills, and receipts, accelerating your transaction processing and saving you precious time. You will receive quicker replies and effortlessly streamline your financial communications.

Check out our AI in Finance Course to learn in-depth about these and many other AI tools used in finance. AI is transforming finance by automating tasks, enhancing decision-making, and improving customer experiences. While challenges like data privacy exist, its potential for innovation and efficiency is clear. The future of finance depends on effectively leveraging AI for the benefit of both businesses and consumers.