How is AI used in financial services?

Using artificial intelligence in the financial services industry is becoming more and more commonplace in the UK. Why? Because of the huge potential for better efficiency and lower costs that using AI facilitates.

In fact, according to new research conducted by Microsoft, the financial sector is the leader in artificial intelligence usage in the UK.

Almost three-quarters of banks, insurance companies and other financial service firms stated in the report that they used AI solutions in some shape or form.

This figure also represents an increase of 7% in the last 12 months, as well as being more than double (56%) the national average of AI usage.

Saving costs

According to estimates from Business Insider, AI technologies have the potential to save the financial services sector around $447bn in total by 2023. The large majority of this will be due to automating the process of front and middle accounting.

Better performance

In the report by Microsoft, called Accelerating Competitive Advantage with AI, financial companies that said they were already implementing AI solutions stated their company was performing better as a result.

In terms of figures, this represented an 11.5% better performance than those not using AI, which is also an increase of 5% from the 12 months previously.

How is AI used in the financial services sector?

Artificial intelligence is used in a myriad of ways in the financial services industry, for example:

• Detecting fraudulent behaviour: AI is commonly used in the financial services industry to process colossal amounts of data and identify key patterns in it, quickly and efficiently. By doing so, banks can process millions and millions of transactions to detect fraudulent activity. AI is particularly useful here as machine learning algorithms (an offshoot of artificial intelligence) can easily analyse millions of data points that would otherwise go unnoticed by humans.
• Risk assessment: AI solutions can scan through thousands of personal financial records in order to give a loan recommendation that is more accurate than just going on someone's credit score, which is otherwise how applicants are assessed. This includes vehicle insurance, PI insurance, business, travel, health and more.
• Robo-advisors: Robo-advisory services are another way the financial services are using AI. These are algorithms that have been built and powered by natural language processing and machine learning, to put together a financial portfolio based on the customer's risk tolerance and goals.
• Customer service: keeping customers happy is vitally important, and the financial service industry uses chatbots in order to help with customer satisfaction. These bots are built on machine learning that learns over a period of time, meaning the advice and service it provides becomes better, as well as helping to keep costs low.
• Reviewing documents: for example, JP Morgan has invested in an AI technology called COiN that can assess and extract data from 12,000 documents in a matter of seconds. For a human to do the same thing, this would take approximately 360,000 hours of work. The benefit for the firm is clear to see.
• Trading purposes: did you know that AI can be used in trading too? This is because machines can learn to observe patterns in historical data and then make predictions based on these patterns, meaning that it can be used to see what might happen in the future. In this context, algorithmic trading involves the use of highly complex AI software to make very fast trading decisions. This has a number of benefits, as it means that trades can be executed at the best rates and multiple market conditions can be automatically checked at once. There is also no human error potential involved, which could prove costly should something go awry.