CEE22: How AI Changes Financial Services (an article)

During the latest CEE22 SME Banking Conference, Federico Avellán Borgmeyer – Chief Partner Officer and Member of the Management Board at efcom (Germany) – during a Panel Discussion on the topic of How AI Changes Financial Services, which he moderated, during his introduction speech to that Panel, tried to find the answer on to which extend financial organizations are using AI at the very moment.

He asked attendees to answer three questions on that.

The first one was: How many AI implementations have been undertaken in your organization? The Conference participants could answer on their mobile devices and choose between 0 and 10. The generalized answer was 3.6. That this number is not as significant as we wish it to be.

The second one was: How was the financial return on your AI investments so far? In this case, Conference attendees had to choose from 0% or less up to 35% and more. The average answer was 8.5%.

Federico mentioned Deloitte’s report mentioning that AI Frontrunners enjoy the highest returns. The more AI implementations you do, the more return you get. Frontrunners receive 35% returns and more, and financial organizations receiving 8,5% returns are at the starters phase.

Federico focused that right now AI in financial services is primarily used to improve efficiency and reduce costs. The creation of new business models should also be of great importance.

After that Federico presented some of efcom’s AI use cases in factoring. Among them, he singled out: Factoring Expert Matching (matching payments with invoices), Smart Cash Flow (capturing new SME factoring customers), and Predictive Customer Behavior (forecast risks & opportunities).

In the last part of the presentation, Federico asked the CEE22 attendees to give their opinion on the third question: Why hasn’t AI made it yet into financial services?

The leading opinions among the conference audience were the lack of trust in AI benefits and the lack of AI skills of employees.

Federico mentioned that these results coincide in some way with the results of a PwC Study, in which the main answer from the banks sounded: Lack of available data. Financial organizations do have a lot of data on their customers. The problem here could arise when they don’t have it in a structured or centralized way. Most probably the main challenge for the financial organization is the lack of skills of employees and lack of management support. So, a change of mindset and level of knowledge should be a changer to move forward with AI implementations in the financial sector.


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