Kazakhstan Stock Exchange (KASE, or the Exchange) and Scila AB entered into an Agreement for supply and implementation of the automated surveillance system Scila Surveillance™ at KASE in order to counteract unfair practices in the exchange market. Scila AB is a leading independent provider of technologies for market surveillance, anti-money laundering and risk management, offering…
London, Stockholm – 25 November 2021 Archax, the first and only UK Financial Conduct Authority (FCA) regulated digital securities exchange, broker and custodian, has selected Scila Surveillance and Scila AML for monitoring of its markets, provided by the Stockholm-based leading independent surveillance, risk & anti-money laundering technology provider Scila AB. Archax was also the first…
Scila AB, the Stockholm-based leading independent provider of trade surveillance, anti-money laundering and risk management technology has opened a regional office in Singapore covering the Asia-Pacific region. Scila has worked with customers in the region since 2009, and currently provide mission-critical solutions to exchanges and a wide range of market participants in the region and…
Athens, Stockholm – 8 July 2021 Cyprus Stock Exchange will shortly go live with Scila Surveillance, provided by the Stockholm-based leading independent surveillance, risk & anti-money laundering technology provider Scila AB. Scila provides Cyprus Stock Exchange with a powerful and flexible real-time market surveillance solution which is deployed at customer sites in more than 20…
William Karlsson Lille and Daniel Saphir from Royal Institute of Technology (KTH) have published a master thesis in collaboration with Scila. Their thesis “Value at Risk Estimation with Neural Networks: A Recurrent Mixture Density Approach” investigates if neural network techniques can be used to improve value at risk estimations. More specifically, the thesis focuses on…
The Executive Chairman of Scila, Lars-Ivar Sellberg, has written an article, A Layered Approach to Anti-Money Laundering, which adresses rule based, statistical and AI/Machine Learning approaches within the AML-solution space
