With big data being consumed by big data software companies and cloud providers, there has been a substantial increase in the practical application of AI.

Artificial intelligence is already being applied in many fields to perform a specific task, such as medical diagnosis, remote sensing, e-commerce, and robot control.

Financial institutions have long used an artificial neural network to detect system changes and abnormal claims while alerting and flagging them for investigation by humans.

Many banks are using artificial intelligence systems to do their accounting, organize operations, manage properties and invest in stocks.

Artificial intelligence, defined as the theory and development of computer systems to perform tasks normally associated with humans, such as decision-making, visual perception, and speech recognition, has been around for a long time.

With advances in computing hardware, big data, and machine learning, artificial intelligence becomes more powerful and useful every day.

Recent advances in artificial intelligence have ushered in a new era in finance, and in a short period of time, big data and machine learning have produced breakthroughs that have resulted in better customer experience and productivity.

Software plays a very important role in this progress and there are still many challenges to be solved. There is a need for software to be designed and optimized to take full advantage of the features of the underlying hardware to improve performance. It is also necessary to simplify the libraries, framework and other tools to speed up the development process. Some of these issues have been fixed thanks to the advancement of the GPU.

Here are some areas in finance where artificial intelligence is already having an impact:

• Financial service providers and banks are implementing AI to help predict and plan how customers manage their money, thereby making AI an integral part of business development strategy.

• The ability of intelligent machines to turn data into customer insights and improve services is transforming the digital experience. Using complex algorithms and machine learning, AI can process thousands of structured and unstructured data points, and because financial professionals rely heavily on data, this ability can significantly impact how they do their jobs.

• Auditors feel relieved of responsibilities by the automation potential provided by artificial intelligence. They are using AI to automate time-consuming and manual activities, giving them time to focus on more important work. AI can help auditors review contracts and documents faster by employing machine learning technology that can find key phrases in documents that take a long time to decipher or interpret. Currently, AI can process the language in a document and produce relevant results, this has played a crucial role in improving productivity.

• Data-driven management decision at low cost is ushering in a new style of management, and in the future, managers will be able to challenge machines rather than human experts. The machines will analyze the data and make a recommendation on which the team leaders will base their decision.

• Application embedded in end-user devices and financial institution servers can analyze large volumes of data, providing personalized forecasts and financial advice. Apps like this one can also help you track progress, develop financial plans and strategies.

• Personalization is an important area where many banks are already experimenting with various ways of combining services and products for customers. AI can help customers simplify the money management process and make a recommendation for upgrade using matching algorithms.

In conclusion, financial service providers need to pay attention to AI as the technology continues to evolve and become more widespread. The way companies innovate and implement core strategies is changing, the corporate organization must adopt AI in others to take full advantage of the trend.