This article was originally published in IT Finanzmagazin. 

By Patrick Schmid, CTO SAP Fioneer

While traditional AI and machine learning have been in use for years, Gen AI, i.e. AI that can also generate data, is still in its infancy. This could open up exciting opportunities for financial service providers. 

According to recent estimates by Accenture, banks and insurance companies are the frontrunners when it comes to the potential for automating everyday tasks using artificial intelligence. Unsurprisingly, as financial service providers and AI are a true dream team. The former work with a lot of very complex data points that are stored and processed in multi-layered software architectures. And AI, in turn, needs exactly that to work well: large amounts of data, because they are the training material for good results. 

Gen AI is already being used in financial services

The first use cases already exist: chatbots for customer service can understand natural language and also respond in natural language. 

“Simple customer inquiries can be processed at any time, in several languages and with a high quality of service, while advisors deal with more complex issues such as financial advice.”

In addition to this example at the interface between customer and financial institution, the far greater potential lies within the organization. If Gen AI solutions are trained with complex data from core banking or insurance systems, they can not only improve the efficiency of existing processes but also enable new business models such as personalized and dynamic products that are tailored to the individual risk profile and customer preferences. Gen AI can also perform complex analyses and predictions that help financial institutions make better decisions.

But Gen AI is not magic

Gen AI is not a magical algorithm that conjures up good results from bad data. Most banks and insurance companies have historically grown IT systems that are often not optimized for fast and efficient access to data. But to train reliable models and implement Gen AI solutions, you need an integrated platform – ideally in the cloud. 

“Necessary projects require time, expertise and investment, which must be carefully weighed up.”

However, there are considerable arguments against this: the decisive factor for business users will be that Gen AI can generate analyses and insights in real time based on the full depth of the available data. Work steps can be automated and thus significantly simplified in use, and data-based forecasts can increase efficiency and reliability in decision-making. Savings can also be expected in the long term in terms of IT costs, for example through accelerated implementation or documentation  

Ultimately, Gen AI is not only an innovative tool, but also a way to accelerate digital transformation and remain fit for the future.