The Deutsche Bank just does not come from the negative headlines. As it became known in the past week that the institute is in the focus of the authorities, because it has not prevented money laundering activities at Danske Bank. In the past, bankers were forced to pay millions in fines, as Russian customers, for example, had laundered money through the bank’s systems. Therefore, the money laundering prevention of the Group is increasingly becoming the focus of attention. Apparently, there is a need to catch up in this area. So instead of continuing to pay high penalties, the board has decided to invest in modern technologies. The bank’s data lab in Dublin has therefore developed an intelligent algorithm that currently scans historical records for patterns and abnormalities.
Also credit card fraud could fly up faster in the future
The idea behind it: artificial intelligence could succeed in identifying certain features that were always associated with money laundering. In turn, a forecasting tool could be developed from this. So if the features occur again in the future, ring the alarm bells and the corresponding transactions are stopped and checked in detail. The approach works not only with money laundering, but with all criminal acts in connection with the banking business – including credit card fraud and manipulated loan applications. The advantage of the automated system is that suspicions are detected much faster and so a quick reaction is possible. However, it is only a supplement to the previously used control mechanisms.
Create money using artificial intelligence
A similar approach should also be used to detect attacks on the bank’s IT systems. Already today enormous amounts of information lines are checked regularly. Again, there is hope that the new technology can speed up the process. In concrete terms, the time until a case of suspicion has been checked should be reduced from around twenty minutes to a few seconds. Even in its core business, Deutsche Bank already relies – at least in part – on artificial intelligence. For example, there is a product called Robin that aims to combine AI analysis with human expertise. However, the product does not exist long enough to be able to judge whether this will actually lead to higher profits.