Tag: insurance

Analytics
Stuart Rose 0
No more excuses.. Analytics IS a game changer

Good news...an analytics survey last year found that 72% of insurance executive agreed that analytics is the biggest game-changer in the next 2 years. Bad news...compared to other industries the adoption rates of analytics in the insurance has lagged other industries. To reverse this trend and help insurers travel down the

Analytics
Stuart Rose 0
Help wanted

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

Analytics
Stuart Rose 0
Customer experience conundrum

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

Stuart Rose 1
Time is precious, so are your analytical models

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

Stuart Rose 1
Putting predictive analytics to work.

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

Analytics
Stuart Rose 3
Demystifying analytics

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

Data Management
Stuart Rose 1
Data is King

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

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