There's a lot of talk right now about the Internet of Things and how it's likely the prime catalyst for the digital transformation of organizations over the next few years. Billions of sensors, and devices with sensors, all generating data in a hyper-connected world where it can be easily shared
The insurance industry is heading for a crisis. Depending on which report you read the insurance industry is facing a shortfall in job vacancy from anything from 40,000 to nearly half million in the next few years. Baby boomers in specialized jobs like underwriters and claims adjusters are retiring and insurers
This is my second blog on the topic of anonymization, which I’ve spent some time over the past several months researching. My first blog, Anonymization for data managers, focused on the technical process. Now let’s dive into the role for analysts, report designers and information owners. To analysts and reporting
SAS/IML software is used by many SAS programmers, primarily for creating custom algorithms and macros that implement statistical analyses that are not built into any SAS procedure. I know that PROC IML is used regularly by pharmaceutical companies, by the financial and insurance industries, and by researchers in medical colleges
Summertime has arrived! Here are some fun, serious and what some might think are absurd questions about water safety. Take the quiz and test your knowledge.
Double negatives seem to be everywhere, I have noticed them a lot in music recently. Since Pink Floyd sang "We don't need no education", to Rihanna's "I wasn’t looking for nobody when you looked my way". My own favourite song with a double negative is "I can't get no sleep" - Faithless. This
If you buying or selling a house. The relator will tell the value of the property is all about location, location, location. For insurance companies location is just as important. For an underwriter assessing the risk on a property is essential that they consider the location of the property. How
Who is your best customer? The answer to this question can vary dramatically depending on your industry. A retailer’s best customer is someone who comes back to their store over and over again. A gym owner’s best customer could be considered consumer who pays their monthly on time but never
For health and life sciences organizations, discussions about big data include gaining value from that data in the form of real-world evidence. Consider for a moment the amount of healthcare data that exists today thanks to the adoption of electronic health records. Then think about the future with data from
You might have lots of data on lots of customers, but imagine if you could suddenly add in a huge dollop of new, highly informative data that you weren’t able to access before. You could then use analytics to extract some really important insights about these customers, allowing you to
This month we take a fresh analytical view of our hypothetical VirtualOil portfolio by comparing the forward price of WTI (the green line) to the prompt month price (red line). The resulting graphic (chart 1) demonstrates the relative stability of the 48-month forward price in contrast to a very active spot
The analytical lifecycle is iterative and interactive in nature. The process is not a one and done exercise, insurance companies need to continuously evaluate and manage its growing model portfolio. In the last of four articles on the analytical lifecycle, this blog will cover the model management process. Model management
As we enter the era of “everything connected,” we cannot forget that gathering data is not enough. We need to process that data to gain new knowledge and build our competitive advantage. The Internet of Things is not just a consumer thing – it also makes our businesses more intelligent. Whenever
Insurance relies on the ability to predict future claims or loss exposure based on historical information and experience. However, insurers face an uncertain future due to spiraling operational costs, escalating regulatory pressures, increasing competition and greater customer expectations. More than ever, insurance companies need to optimize their business processes. But
It’s an incredibly exciting time for data science. Just ask Jake Porway, former New York Times Data Scientist and now CEO of DataKind, who opened his April 28 SAS Global Forum keynote by asking busy conference goers to pause and reflect on the revolutionary times we are living in. “Cell phones
A very common type of graph contains two series plot, where the user is expected to evaluate the difference visually. I saw one such plot on the web today shown on the right. This graph has two curves, one for malpractice premiums and one for claims, with a shaded band
There is no doubt that analytics is an overused and often abused term. So what does really analytics means? In part 2 of a series of articles on the analytical lifecycle, this blog will highlight some of the common and emerging techniques used to analyze data and build predictive models
If you are one of the thousands of SAS users soon to be in Dallas for SAS Global Forum, you've probably already used the online tools to help you view sessions related to your industry. It’s easy to do by filtering on your own particular industry, such as banking, or
The move to value-based payments is well underway and accelerating. The shift is putting unprecedented pressure on health care providers to better manage the cost and quality of care they deliver. Who will have a much better shot of success? Organizations that understand how well they are performing, where they have opportunities to improve
The Internet of Things (IoT) is going to take us into the next big technology wave, which will include a massive proliferation of personal connected devices like we have never seen before – cars, toothbrushes, household appliances, watches, medical devices, bicycles, and all sorts of things on our body and in
JBF Special Issue on Predictive Business Analytics Dr. Chaman Jain, professor at St. Johns University, and editor-in-chief of the Journal of Business Forecasting, provides his preview of the Winter 2014-15 issue: Predictive Business Analytics, the practice of extracting information from existing data to determine patterns, relationships and future outcomes, is
In my last blog I detailed the four primary steps within the analytical lifecycle. The first and most time consuming step is data preparation. Many consider the term “Big Data” overhyped, and certainly overused. But there is no doubt that the explosion of new data is turning the insurance business
Advances in technology, evolution of the distribution channels, demographic shift, economic conditions and regulations changes. How does an insurer prioritize all these seemingly competing goals and create sustainable competitive advantage. One answer is analytics. Many insurance companies are just beginning to take steps toward becoming an “analytic insurer” – one
Beyond traditional clustering and predictive models lies social network analysis. It can help describe customers’ behaviors in new ways, but what exactly is it and how can businesses use it? To find out more, I interviewed Carlos Andre Reis Pinheiro. He’s been working in social network analysis around the world
The old adage is that “Data is the lifeblood of the insurance industry.” However, for many insurance companies, data is like the red-headed stepchild. No one is willing to take care or have responsibility for it. In the past, insurance companies have created data governance programs, but these have often
Many states are starting to crack down on the serious abuses of government programs, cutting down on outright fraud as well as reducing abuses and errors. I wanted to highlight one of those, now that they've been on this path for a few years. North Carolina, where SAS is headquartered,
Business analytics is about dramatically improving the way an organization makes decisions, conducts business and successfully competes in the marketplace. At the heart of business analytics is data. Historically, the philosophy of many insurers has been on collecting data, data and more data. However, even with all this data, many
According to analyst firms, consulting companies and various other research, customer experience is the primary priority for insurance companies. But is customer experience overrated? Let’s start by considering the primary interactions between an insurance company and its customers: new business, billing, renewals and claims. Ask any insurance executive, especially property
This is the last of my series of posts on the NIST definition of cloud computing. As you can see from this Wikipedia definition, calling anything a “cloud” is likely to be the fuzziest way of describing it. In meteorology, a cloud is a visible mass of liquid droplets or frozen
Over the past decade in insurance, the rise of the aggregators (organisations that compare quotes between different insurers) and direct channels has had a profound impact on personal lines distribution in the UK. However, personal lines brokers remain a critical route to market, especially at a time when many insurers
