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HomeUncategorizedHow is Machine Learning Used in the Finance Industry?

How is Machine Learning Used in the Finance Industry?

The advent of technologies like artificial intelligence and machine learning have undoubtedly brought a digital transformation in the finance industry. These technologies have made simple machines to think, behave, and act like human beings. The biggest benefit AI and ML are rendering to the finance world are to automatically fetch and process an enormous amount of data available over the web to bring out useful insights. 

These insights help in taking futuristic decisions that can lead to the growth and success of the business. Where AI works on the pre-defined algorithms, machine learning doesn’t even need that; the technology automatically learns from the experiences to take action or provide useful information. Let’s explain how technology can be used in the finance sector for

1. Fraud prevention and detection 

Machine learning technology can help financial institutions to monitor thousands of transactions happening every day over the web. The technology with the help of pattern recognition can detect suspicious activities in seconds and send an immediate alert to the banks or the users. 

2. Market predictions  

Machine learning can collect and process the humongous amount of data to bring useful information out of it. The process might take months if done manually. Based on the data, the technology can predict market changes, consumer behavior, and a lot of other things that can help businesses to make better decisions. Using those predictions, investors can invest their money with a higher chance of profit than loss. 

3. Risk management 

In the finance domain, risk management includes investment risks, trading risks, and a few others. Machine learning, when integrated into various finance apps, can work actively at every stage (preparing data, data modelling, stress testing, etc.) to determine that model being used for trading is right or not. In short, the technology can analyze stress testing market model to evaluate the risks in the trading behavior. 

4. Customer support

Offering customer support services has become an integral part of every business not only the ones in the finance sector. With the help of artificial intelligence and machine learning, businesses can automate customer support services. Wondering how? The technology can be used in the chatbots that will provide auto-generated answers by understanding the intent of the queries. 

5. Robo-advisory

Machine learning also plays a major role in the advisory sector; it can assist in portfolio management, online wealth management, recommending finance-related products, and accomplishing various other tasks with precision and perfection.  

6. Automated trading system

Machine learning, in combination with artificial intelligence, can facilitate algorithm trading. It can work on complex algorithms to create fruitful strategies and take fast trading decisions. Once created, an algorithm in the ML can help in making millions of trades in a single day. 

7. Settling trade

Modern trade can be done easily over the web; you can exchange payments in seconds. However, trading online might also fail due to several problems. ML technology can not only figure out the problem that is becoming an obstruction in the way of trade settlement but also provides a solution. 

How to develop an ML based finance application?

So you know the uses of machine learning in the finance domain and want to build an application using this technology. Here is what you have to do- either choose good ML development agency or hire ML developers. In both cases, make sure you research the market thoroughly to end up choosing the one that can provide you with a good value of your money. Check the portfolio of the company and also the reviews submitted by their clients. Besides this, ensure that the company or the developer has experienced in developing ML finance apps. Choose wisely!

How much does it cost to build an ML based finance app?

ML app development cost may vary on the type of finance app, size and location of the development company, the time required to build the app, tools & technologies needed for the development, the platform on which you want to release the app, and a few other factors. Only after determining them, you would be able to have an estimate of the cost of an ML-based finance app. Roughly, it would be around $25,000 to $55,000. You can contact a reliable finance app development company, provide your particular app requirements, and get an estimate of the cost. 

Final Words

Machine learning, when integrated into various finance applications, can make them smarter. The technology can be used to enhance security, detecting and preventing frauds, predicting investment, robo-advisory, network security, risk management, money-laundering prevention, and other areas. Read this article to know more about this. On the other hand, if you want to integrate this technology in your existing business applications or want to build a new app from scratch, then contact a reliable AI/ML development company.

Disclaimer: The information in this article is provided for general education and informational purposes only, without any express or implied warranty of any kind, including warranties of accuracy, completeness or fitness for any particular purpose. It is not intended to be and does not constitute financial, legal, tax or any other advice specific to you the user or anyone else. TurtleVerse does not guarantee the accuracy, completeness, or reliability of the information and shall not be held responsible for any action taken based on the published information.



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