Danske Bank Deploys Quantexa’s AI Platform for Financial Crime Detection
- Security , Fraud Detection
- 17.12.2020 08:36 am
Quantexa, the data and analytics software company pioneering contextual decision intelligence, announced today its AI-based technology is supporting Danske Bank as it enhances its Anti-Money Laundering (AML) monitoring and investigation capabilities.
After a successful pilot in 2018, the bank is now using Quantexa’s CDI platform to perform transaction monitoring on Danske’s market trading business and financial crime investigations. With Quantexa’s contextual monitoring, entity resolution & network analytics capabilities, Danske Bank uses artificial intelligence (AI) to uncover the real-world context in data to detect financial crime.
The implementation of Quantexa’s Contextual Decision Intelligence tools has helped enhance Danske Bank’s ability to detect suspicious activity within its market trading business for areas such as foreign exchange, securities and equities.
“Harnessing technology enables us to identify complex financial crime behaviours more effectively. Running advanced analytics on a wide range of datasets can help us better detect, investigate, and prevent financial crime,” said Satnam Lehal, Head of Financial Crime detection in Danske Bank.
Quantexa’s open platform architecture produces high-quality alerts for markets monitoring, so the bank has taken the pilot project to the next stage and integrated it with its existing infrastructure. Danske Bank is continuing to increase its financial crime detection and monitoring capabilities across several areas in the bank.
“The significant success of our contextual approach to monitoring in Danske Bank’s markets business and supporting financial crime investigations is another great example of our ability to surface suspicious activity, even in the most complex product and data sets,” said Vishal Marria, CEO of Quantexa. “We look forward to continuing our work with Danske Bank and furthering our mission to help uncover organised crime networks by making data meaningful for more effective decision making and providing flexible software tools that integrate into existing environments, across any size of organisation.”