Mike McClain, Senior Web Designer & Site Manager
A mammoth fertilizer plant explosion late last night leveled much of a town called West in Texas. Reports list at least five and up to 15 dead and more than 160 injured. Several blocks of the small town near Waco have been wiped off the map by a blast that registered on the Richter scale. “Homes have been destroyed. Part of that community is gone,” said Sgt. William Patrick Swanton, a local police officer, at a press conference.
While insured property losses from the Boston Marathon bombing are small, the insurance of sports events is likely to be impacted, according to catastrophe modeling firm RMS.
Dr. Gordon Woo, catastrophist at RMS noted that the shortage of terrorism insurance cover in the years after 9/11 had led to the securitization of the cancellation risk of the 2006 FIFA World Cup.
Having seen an uptick on volatility as measured by the VIX in the last few days, I find that this is a good time to talk about a phenomenon many people do not know. Volatility tends to be persistent, with low volatility leading to more low volatility, and high volatility leading to more high volatility. But more interesting still, volatility can feed on itself, with increases in volatility leading to further increases in volatility and decreases in volatility leading to further decreases in volatility. And there is a simple reason for this, which I will explain in this article.
Choosing the right talent for one of the most challenging jobs in the cyber economy can be a tough job, but what kind of CISO should you be looking to recruit to lead your organization? Amar Singh provides his model CISO for your consideration
Cyberspace is now the primary medium for revenue generation for most online-savvy organizations, and it is responsible for billions of dollars of commerce and revenue growth. A significant majority of goods and services are being bought and sold on the internet, across the globe. Whereas, earlier, e-commerce was only prolific in the West, today China and other nations in Africa and Asia are also seeing significant commerce in cyberspace.
Your Disaster Recovery Plan has a Recovery Time Objective (RTO) – or, perhaps multiple RTO’s for each Application or Service being recovered). Your Business Continuity Plans have RTO’s for the underlying functions or business processes they are designed to recover.
But do these RTO’s really mean the same thing? Probably not; and if your Business Continuity Recovery Teams don’t understand that difference, they may be in for a very rude surprise when a disruption occurs.
There was a time when Disaster Recovery was mostly for companies running extremely mission critical applications like banks and stock exchanges. But then every business needs to have a DR strategy in place. As we've seen in recent years, natural disasters can lead to long-term downtime. Because earthquakes, hurricanes, snow storms, or other events can put datacenters and other corporate facilities out of commission for a while, it's vital that companies have in place a comprehensive disaster recovery (DR) plan.
As of Wednesday, China has reported 82 human infections of H7N9, including 17 deaths. About 40 percent of the patients had no contact with poultry or environments where birds were located, previous epidemiological studies found. It remains a mystery how they became infected, Zeng said.
We are living in a time of technological ferment, if you will, and there are multiple IT approaches in the works ─ all with the mission of dealing with the ‘data deluge.’ Obviously, as data grows, there’s more to back up. And the various strategies for dealing with it include deduplication, block-level backups, snapshots for recovery and so forth. But there’s one I haven’t heard discussed too much: what about using flash drives for backup?
The use of predictive analytics in insurance is becoming increasingly widespread as companies realize how the power of insight can impact business growth, risk management, and loss control. The number of insurers using these sophisticated models is growing daily and, there are more business capability areas that are reaping the benefits. Recent SMA research indicates that over one-third of insurers are currently investing in predictive analytics and models.
Data is at the center of most challenges facing our industry today, with business drivers such as new regulations, aggregated risk management, and deep customer insight all having critical data management implications. The term Big Data has become a common way to describe this, and while some of these challenges are associated with large volumes, it isn't really the size of the data that's at issue. I'd argue that at this point we know how to handle large volumes: use shared-nothing architectures that scale horizontally on commodity hardware. The trickier problem has to do with a different "V" of Big Data - variety - and it is that aspect that I'd like to focus on.