Rethinking risk prediction models


Imperfect information leads to poor decision making and a subsequent increase in risks. Advanced methodologies imported from the world of macro-economic prediction-making are increasingly filtering down to asset management. Economic modelling has improved considerably over the years enabling economists to gain a better understanding of the factors driving instability and cycles. Modern models integrate new techniques, such as cognitive psychology to understand how human behaviour creates waves of optimism and pessimism which lead to boom and bust cycles. Social media’s massive data samples help give a clearer picture of user sentiment. 

Joseph Saliba

These advances in macro-economic risk prediction modelling find their applications in investment management, and CACEIS is keen to bring these benefits to its clients. Our data analytics solution, relying on our “data lake”, is designed to address issues about capital in- and out-flows. It plays a key role in generating tailored management reports that form an essential part of a company’s risk and compliance management process. Indeed, these massive amounts of data sourced both internally and from data providers and other contributors, give an accurate, real time picture of holdings across the board. Beyond risk managers, the value proposition of our data analytics services is also of interest to marketing departments.

We integrate data from social media in order to measure the impacts of sales campaigns and provide a better understanding of online brand recognition – a key issue as investors increasingly turn to e-services for investment advice.

CACEIS will soon implement a new online application, WebInvestor, which enables our clients’ investors to access real time information on their investments and helps reduce the environmental impact of printing and mailing documents such as statements and contract notes. We also invest into Distributed Ledger Technology and participate in some of the key research and working groups in this field. We hope to uncover applications for this technology and for the benefit of our clients’ operations.

CACEIS is committed to “client efficiency”. This is a result of ensuring the optimal balance between increasing our confidence on information technology performance, innovation and digital services, and seeing the human factor and client satisfaction remain at the centre of our relationship.