There are various ways that big data analytics can assist the insurance industry. Below are a few examples of this.


Predicting Fraudulent Claims

One of the most effective and prominent uses involves handling the abundance of fraudulent claims made by customers. These claims occur on a regular basis and often have a significant impact on company profits. OLSPS Analytics’ fraud prediction solution is designed specifically to reveal and prevent such cases of insurance fraud.


Churn Prediction

Furthermore, insurance companies operate in a competitive market, where attracting new clients and reducing customer churn is a high priority. OLSPS Analytics’ churn prediction solution identifies the sources of customer churn and yields accurate timely predictions, providing these companies sufficient time to take appropriate action and prevent the loss of customers.


Market Segmentation

Small inaccuracies in market analysis can lead to major financial losses. Our market segmentation solution provides further valuable insights by analysing and segmenting markets into clusters of defining characteristics. Companies are subsequently able to design customised insurance packages and more personalised market strategies targeting these market segmentations, thus attracting more customers to make use of their services.


Risk Segmentation

Our scorecard solution can be used to help companies mitigate risks by ranking customers relative to a target. For example, in the insurance industry, this solution is used to mitigate moral hazard and adverse selection risks by assigning accurate risk profiles to current and potential customers.



Analysing customers and the market is vital; however, a company’s front-line management and sale staff also has a significant impact on the revenue generated by these firms. Therefore, our workforce analytics solution, Enjol, has been specifically designed to uplift and maintain the performance of these staff members by making use of modern principles of workspace psychology, survey tools and predictive analytic models. Enjol is ideal for companies with a large employee base, where keeping track of the wellbeing of all staff members on a regular basis requires a lot time and resources and is often unrealistic.

Reshaping the Insurance Industry with Big Data