As technology and analytics continue to evolve, we're seeing new opportunities not only in the way that we analyze data, but also in deployment options. More specifically, real-time deployment of analytical algorithms that enable organizations to detect and respond to security threats, offer timely incentives to customers, and mitigate risk by detecting compliance
Why visualization? Several reasons, actually, the most compelling being that sometimes visualization literally solves the problem for you. I remember an exercise in eighth grade English class where we were asked to describe, in words only, an object set in front of us with sufficient clarity such that our classmates,
It’s been very hot here in Northern Italy: electricity provision has struggled to keep up and we’ve had frequent power outages in the area, even within our apartment building. A bit inconvenient? Don’t get me started. I feel like my home appliances have turned against me, taking me back to
In my previous post I talked to John Cassara about the growing threat of mobile payments and how mobile phones can be used to launder illicit funds globally. I spoke with him again recently on the topic of financial intelligence. Here are the highlights from our discussion. So what is
I enjoy watching TV crime series like Law and Order, Crime Series Investigation (CSI), CriminalMinds, Numb3rs, Person of Interest, as well as real-life mystery stories on shows like 20/20 and others. Obviously, the popularity of these types of shows means I'm not the only one who enjoys this type of entertainment. Here at SAS,
Financial institutions have been managing their AML models to meet regulatory expectations for some time. But what about customer risk rating models? We’re seeing a trend where firms are re-evaluating whether their heuristic, rules-based customer risk rating models can withstand regulatory expectations. Rules-based models follow simple analytical formulas, such as,
In the oil and gas industry, analytics are used to improve both upstream and downstream operations, from optimizing exploration and forecasting production to reducing commodity trading risk and understanding customer's energy needs. If you plan to derive value from the digital oil field, big data, and analytics, one of the first things
Looking at the top 100 organizations in the world, have you ever wondered which ones we’d really miss if they were to disappear? Give it a try. I bet you don’t choose the ones with the highest profits. You probably make your picks based on meaning. You probably chose the
Oh, how times have changed during my 20-plus years in the insurance industry. Data wasn’t a word we used much back in the 80s and 90s, unless of course you worked in those arcane and mysterious IT data centres. Even amidst the computerisation of the insurance industry in the 80s, many
In my previous blog post, I discussed the benefits of a Statewide Longitudinal Data System (SLDS) and shared a SAS book on the subject: Implement, Improve and Expand Your Statewide Longitudinal Data System by Armistead W Sapp III and Jamie McQuiggan. Today, I'm sharing a conversation I had with one of the book’s authors,
