Which topics and priorities will be the focus for chief risk officers in 2019? A range of experts and representatives of major banking institutions addressed these questions at a recent event, CRO and CFO Banking Agenda 2019, organised by CeTIF, the Research Center on Technologies, Innovation and Financial Services, in collaboration
Anti-money laundering is an important issue for governments and banks alike. The fight to prevent terrorist financing and profiting from crime means that banks and other financial institutions are increasingly required by regulations to put anti-money laundering systems in place. Many are turning to analytics in the process, and particularly to
The number of models used by large operators in the financial sector is increasing by around 10 to 25 percent per year. Most of the new models are designed to meet business needs, such as pricing, the definition of strategic plans and the management of liquidity. Some, though, are for
Hackathons are short-term programming events that use data and analytics to solve real-world challenges. They have been around for a while now, and there is general agreement that they are great opportunities for networking and experimenting. There is also, however, now a growing sense that organisations can use them to
The recently released results of a new joint survey from SAS and the Global Association of Risk Professionals (GARP) on the use of AI in risk management makes for very interesting reading. Here are the highlights from the study, which involved more than 2,000 participants from across the global financial
Let’s be blunt. Procurement fraud is a problem. Orders and purchase procedures are one of the most vulnerable areas of corruption. The scale of irregularities and abuse in the procurement area is large. In fact, procurement fraud is the second-biggest economic crime after theft. Estimates suggest that businesses can
The idea of running software in a self-contained package took off with the launch of Docker in 2013 and has become a hot topic in the application development and DevOps community. In a recent survey by Red Hat, 57 percent of companies questioned said they use containers for some workloads
Changing how we’ve viewed the beautiful game forever. How often have we looked at a game and wondered, “How did he miss that?!” Now, with expected goals (xG) metric, we can really see if our frustration is justified, and perhaps use that to predict future results. The use of analytics
Data scientists spend a lot of their time using data. Data quality is essential for applying machine learning models to solve business questions and training AI models. However, analytics and data science do not just make demands on data quality. They can also contribute a lot to improving the quality
What is that makes some innovations "stick" and others disappear into the ether, never to be seen again? In a high-technology industry, it is tempting to say that the technology simply wasn’t right, or the timing was wrong. However, history suggests that this is probably not the case. Much of the
