Whether you are fixing the kitchen sink, doing yardwork or cooking a meal, it is often essential to have the right tools for the right job. The same applies when it comes to predictive analytics. Solutions for business intelligence, data visualization, and reporting are very different to those for predictive analytics. It’s even important to use the right predictive analytics software, especially when it comes to analyzing insurance data.
Why is this? Well, insurance data is different. The frequency of claims is relatively small. Then there is the randomness of the data. For example, two claims that may appear similar may vary considerably in severity. The data can be noisy with many missing values. So when it comes to applying predictive analytical techniques that have been designed for banking, manufacturing, life sciences, and other industries, they do not work as effectively on insurance data.
Guidewire Predictive Analytics uses advanced analytical algorithms that have been designed specifically for the insurance industry. These algorithms take into consideration the unique characteristics of insurance data, enabling greater model accuracy, lift, and stability than other more horizontally focused predictive analytical software products.
Another thing to consider when selecting the right predictive analytics software is the advantages of machine learning. Using machine learning technology, models can be built much faster, non-linear interactions between variables become clearer, and probably most importantly, machine learning is not constricted by human hypotheses. For example, not all 17-year-olds are bad drivers.
To learn more about the power of predictive analytics software, watch this short video by Wade Bontrager, Vice President, Predictive Analytics, Guidewire Software.