With large data software companies and cloud providers consuming a large amount of data, there has been a significant increase in the practical application of AI.
Artificial intelligence is already being used in a wide variety of fields to perform a specific task, such as medical diagnosis, remote sensing, electronic commerce and robotic control.
Financial institutions have long used an artificial neural network to detect system changes and abnormal claims while alerting and flagging them to be investigated.
Many banks use artificial intelligence systems to maintain accounting, organize operations, manage real estate and invest in stocks.
Artificial intelligence defined as a theory and development of computer systems to perform tasks normally associated with humans, such as decision making, visual perception and speech recognition have been around for a long time.
With advances in computational hardware, big data and machine learning, artificial intelligence is becoming more powerful and useful every day.
Recent advances in artificial intelligence have ushered in a new era in finance, and within a short period of time, big data and machine learning have made breakthroughs, resulting in improved customer experience and productivity.
Software plays a huge role in this breakthrough, and there are still many challenges to solve. Software needs to be designed and optimized to fully benefit from the features of the underlying hardware to improve performance. Libraries, frameworks and other tools are also needed to streamline in others to speed up the development process. Some of these issues are resolved due to the advance in GPU.
Here are a few areas of funding that artificial intelligence is already impacting:
• Financial service providers and banks use AI to help predict and plan the way clients manage their money, thus making AI an integral part of the business development strategy.
• The ability of smart machines to transform data into customer insight and improve services transforms the digital experience. By using complex algorithms and machine learning, AI can process thousands of structured and unstructured data points, and because finance people rely heavily on data, this capability can significantly affect how they perform their jobs.
• Auditors feel free from responsibility because of the automation potential provided by artificial intelligence. They use AI to automate time-consuming and manual activities, giving them time to focus on a more important job. AI can help accountants review contract and document faster by using machine learning technology that can find key phrases from documents that take a lot of time to decipher or interpret. Currently, AI can process language in a document and produce relevant results, this has played a vital role in improving productivity.
• Data-driven low-cost management decision initiates a new management style, and in the future managers will be able to ask questions about machines instead of human expert. Machines analyze data and make a recommendation on which team leaders base their decision.
• Integrated application in end-user devices and financial institution servers can analyze a large amount of data by providing customized forecasts and financial advice. Applications like this can also help track progress, develop financial plans and strategies.
• Personalization is a major area where many banks are already experimenting with different ways to match services and products to customers. AI can help customers simplify the money management process and make an upgrade recommendation by matching algorithms.
Finally, financial service providers need to be aware of AI as technology continues to evolve and become more mainstream. The way companies innovate and implement big strategies is changing, the business organization needs to embrace AI in others to take full advantage of the trend.