So how is this information kept? To be valuable, this information has to be tied directly to each individual's personal identifiable information. Thus the advent and growth of “big data” and data analytics and the accompanying increase in concerns about network security and privacy.

For instance, there are only a few times in our lives when our buying habits change abruptly; first real job, marriage and divorce are a few. The biggest change of all, though, is having a baby. Studies show that all our buying habits are in flux when a baby is due, from the cars we drive to the breakfast cereal we eat. Capture this inflection point in people's lives and retailers can make some real money, both in the short term and for years to come.

So how is it determined that pregnancy has occurred or is imminent? Not through a pregnancy test, but by carefully and closely watching and monitoring an individual's personal buying patterns and ferreting out specific trends and markers.

From a personal story illustrating how personally invasive data mining can be (“How Target Figured Out a Teen Girl Was Pregnant Before Her Father Did,” Forbes, 2/26/12): Target assigns every customer a guest ID number, tied to their credit card, name, or email address that becomes a bucket for that person's history. “When someone starts buying scent-free soap and extra-big bags of cotton balls…it signals they could be getting close to their delivery date.” Target's computers crawled through this data and identified 25 products that assigned a “pregnancy prediction” score.

After his daughter got a packet in the mail with coupons for baby clothes and cribs, an irate father contacted the retailer and demanded an explanation. The store manager apologized and called a few days later to apologize again—when the father admitted that after a conversation with his daughter, he learned she was pregnant and due in August.

So what can be done about stopping or slowing big data and analytics? Likely nothing. The revenue associated with profiling customers is too great. Some people credited Target's growth from $44 billion in 2002 to $67 billion in 2010 to the company's focus on items designed to appeal to specific guest segments, such as mothers-to-be. As insurance and risk professionals, we should be cognizant that data collection on a massive scale is only going to grow.

Increased information security precautions, heightened privacy awareness, and overall security rigor must grow as data bases grow. That seems reasonable, logical and, frankly, essential. Limits for any Cyber Insurance purchase must grow proportionally also.

Big data is not only a concern in the retail segment; it's happening across all industries, including utilities, financial institutions and service firms. Big data is the future, and the insurance industry at all levels must proactively address this exposure. Most Cyber Insurance applications ask “a point in time” question regarding data base size. It seems prudent when devising a risk management plan or purchasing Cyber Insurance to evaluate how that data base may grow in the coming months and years by asking the IT specialists.

When considering Cyber Insurance, it is important to understand that the world of business has changed. Information about an individual is a commodity and the more information about more people, the more valuable the information/commodity is. Cyber Insurance and risk management professionals must deal with the large increases in information and the accompanying exposures by securing the expanding exposure and insuring the loss when aggregated personal information is compromised.