Finastra, a fintech company, recently introduced a new AI solution. The software is intended to enable banks to more conveniently comply with regulations and process payments more efficiently. More on how to evaluate the use of artificial intelligence and machine learning in finance below.
Use of AI in the financial sector: a blessing and a curse?
Banks see the use of artificial intelligence (AI) as the biggest cost reducer in the future, as an article on the online portal der-bank-blog.de explains. The possible savings through AI in the financial world are probably many times higher than in other industries. Aside from reducing existing expenses, the most significant economic potential of artificial intelligence lies in preventing lost opportunities, the so-called opportunity costs, the blog post adds.
AI systems can analyze large amounts of financial data in real-time and identify patterns to help companies manage expenses efficiently. An article from bank-verlag.de also emphasizes that they can play a crucial role in detecting fraud and combating financial crime. The responsible employees could be alerted to suspicious activities using AI systems in order to then investigate the cases in more detail.
However, the use of artificial intelligence in the financial sector has some critical aspects. Privacy and security are just some of the many concerns as today’s and future technologies process large amounts of sensitive financial information.
Technology and data protection: How AI and machine learning support
According to a report by it-finanzmagazin.de, Mike Vigue, product manager at Finastra, underlines the importance of a solution in the area of instant payment transactions that focuses equally on security, scalability and flexibility aspects. In the future, the company plans to expand the software solution to include the use of artificial intelligence and machine learning methods. However, it remains to be seen how these developments will affect data protection and possible questions regarding automated decision-making processes.
The Finastra application, as the article from the online portal it-finanzmagazin.de explains, helps banks to use and comply with requirements for instant payment transactions. In the United States, this would include FedNow, the Federal Reserve’s instant payment service – in Europe, however, TIPS, the European Central Bank’s TARGET Instant Payment Settlement. This also reduces the risks of financial crime, the article adds.
Carrying out these tasks solely by compliance officers would be expensive and error-prone. Therefore, AI systems should also contribute to cost savings in this area in the future.
Expanding market for automated compliance products
In Europe, companies in particular benefit from the vast amount of data protection regulations that promise to shed some light on the matter. In order to keep track of the issue of compliance, some companies are already using software products that are intended to help them comply with compliance regulations.
The company Secjur, for example, offers an automation platform for compliance processes based on artificial intelligence. According to an article on the online portal mq.ch, the Hamburg start-up’s customers include small and medium-sized companies as well as large corporations such as Siemens.
The future will have to show how quickly the change towards digitalized compliance really progresses. A study conducted by Deloitte in 2022 came to the conclusion that 23 percent of German companies still do not use technical tools to support compliance processes. Another 39 percent only use one or two solutions.
Editorial team finanzen.net