Standard Chartered has partnered with Quantexa, a contextual decision intelligence software company, to amplify its anti-financial crime efforts globally. Working as part of a wider ecosystem, Quantexa will support Standard Chartered’s Financial Crime team through use of dynamic entity resolution, network analytics and contextual data to tackle major real-world challenges, including money laundering, fraud and terrorist financing. Quantexa’s decision intelligence platform utilises artificial intelligence (AI) to provide Standard Chartered with a connected 360-degree customer view, empowering the bank’s investigators to make faster, more accurate decisions.

Developed in partnership, the platform enables Standard Chartered to conduct complex financial thematic investigations more efficiently and effectively, demonstrating the bank’s ongoing commitment to uphold the highest global standards in compliance and risk management. The bank can now see a holistic view of investigations, providing a deeper understanding of the trends and risks across billions of data points from more than 40 countries.

By automating labour intensive, manual intelligence gathering, the bank’s investigators now have more time to focus on finding true risk, as well as have improved consistency in their investigations. The platform will become a support tool for Standard Chartered and presents rich detail about customers and transactions in one place, visualising the relevant relationships and behaviours to provide context for faster decisions. It also allows the bank to leverage its existing investments in monitoring and case management for more efficient and effective financial crime compliance.

“Quantexa’s solution consolidates information from multiple sources, leverages advanced analytics, visualisation and contextual output," said Praveen Jain, head of FCC Controls Strategy and Innovation at Standard Chartered. "This not only simplifies tasks for the analyst, but also helps them understand the flow of funds, see the relationships between entities and identify otherwise hidden linkages that may have been difficult to establish previously.”