How Artificial Intelligence (AI) Is Disrupting Financial Services
With big data software companies and cloud providers using up a large amount of data, there has been a substantial increase in the practical application of AI.
Artificial intelligence is already being applied in a lot of fields to perform a specific task such as medical diagnosis, remote sensing, electronic trading and robot control.
Financial institutions have longed used an artificial neural network to detect system changes and abnormal claims while alerting and flagging them for human to investigate.
Many banks are making use of artificial intelligence systems to maintain book-keeping, organize operations, manage properties and invest in stock.
Artificial intelligent 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 has been in existence for a long time.
With advancements 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 yielded breakthrough that resulted in improved customer experience and productivity.
Software plays a huge role in this breakthrough and there still remain a lot of challenges to solve. There is a need for software to be designed and optimized to fully take the advantage of the features of the underlying hardware to improve performance. There is also need for libraries, framework and other tools to be streamlined in other to accelerate the development process. Some of these problems have been solved because of the advance in GPU.
Here are a few areas in finance that artificial intelligence is already having an impact:
• Financial service providers and banks are deploying AI to help predict and plan the way customers manage their money and thus making AI an integral part of business development strategy.
• The capability of smart machines to turn data into customer insights and improve services is transforming the digital experience. By utilizing complex algorithms and machine learning, AI can process thousands of structured and unstructured data points and because finance professionals heavily depend on data, this capability can significantly impact how they do their jobs.
• Auditors feel freeing of responsibilities due to 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 job. AI can help auditors to review contract and document faster by employing 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 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 able to question machines instead of human expert. Machines will analyze data and make a recommendation that team leaders will base their decision upon.
• Embedded application in end-user devices and financial institution servers can analyze a large volume of data, providing customized forecasts and financial advice. Applications like this can also help to track progress, develop financial plans and strategies.
• Personalization is a major area where many banks are already experimenting with various ways to match services and products for customers. AI can help customers to simplify money management process and make a recommendation for upgrade by matching algorithms.
In conclusion, financial service providers need to pay attention to AI as the technology continues to evolve and become more mainstream. The way businesses innovate and implement major strategies are shifting, corporate organization needs to embrace AI in other to fully take the advantage the trend.