Artificial intelligence can soon be a powerful and a new way of making decisions across trading, lending and risk management in banks. Artificial intelligence is making the financial services industry by high pressure up gradation. Almost every company in the financial sector technology had already started using artificial intelligence to save time, reduce cost, and add value. The future of finance will be heavily influenced by emerging companies and artificial intelligence technology applications setting the stage for increased competition among then industries leading companies.
In the next few years, artificial intelligence will help financial sector companies maximize their resources, decrease risk, and generate more revenue, in the trading, investing, banking etc. artificial intelligence has helped to push the finance sector in term of technological advancements in the industry. For example, a consumer can use facial recognition to log in to the financial app and can use voice command. There is no other business sector that is more focused on developing and implementing artificial intelligence for speed, accuracy, and efficiency as much as the financial industry. Artificial intelligence is machine learning algorithms, software that self-improves as it is fed with more and more data, it is as a trend that the financial industry can benefit from immensely. Artificial intelligence in finance is creating a huge impact.
Impacts of AI in the finance industry:
Maximising resources:
Artificial intelligence helps companies in the financial industry to save time and money through the use of algorithms to generate views and improve customer service and make predictions about the sales performance of the company
Trading:
Better trading is done through algorithms artificial intelligence can help and form rules and the trading decisions, helping to process the data and creates the algorithms managing the trading rules. Investment firms have started implementing trading algorithms based on sentiment and insights from social media and other public data sources from years.
Investing:
In the terms of wealth management, B 2 C portfolio management and rebalancing decisions made by human and often to analyze a person’s portfolio, risk tolerance, and previous investment decisions to make an advice. Artificial intelligence can also use to track account activity and help financial advisors to customize the guidance they give to the investors.
Banking:
Chabot’s help banks serve customers more efficiently, and those are not advanced enough to handle support cases autonomously. As these are powered by natural languages processing, bots can listen in to the agent call, provide accurate or correct answer very fastly, and also suggests the best practice answers to improve sales effectiveness. In the financial firm, data is unstructured and the company will have many databases that store information about each entity separately. It is difficult to link and connect information. A team of human analysts is used to be needed for such type of projects but now it can be done through artificial intelligence with human supervision.
Fraud identification:
Machine learning algorithms like which are used in a MasterCard decision intelligence technology analyses various data points to identify fraudulent transactions that humans might, by using machine learning to spot unusual patterns and improve general regulatory workflows help financial organizations be more efficient and accurate
