Alongside the business process changes impacted by Big Data Analytics do not ignore cultural changes.
It is proven that predictive analytics yields as good, and often better, results in reducing fraud as the established ( and very large & costly) Fraud Investigation empires. This means these will be dismantled in progressive companies whilst the empire builders in those insurance companies lagging behind will keep these departmental high costs and lengthy investigations as the norm.
That means higher costs, lower customer service and decline fore those insurance companies.
Alongside the improvements to be gained from big data analytics we should also remember that a large proportion of data is still text based- I have seen figures as high as 90%- and often inaccessible. This has to be digitised and "analytics ready" if insurance companies are to have a complete picture of claims, claimants and the parties involved in every claim. Without it they cannot enjoy the benefits of big data
Marketing departments within insurance companies have also begun to use Big Data to identify customers most at risk of cancelling or leaving. As with policy underwriting or fraud detection, this is done by comparing the data on a customer’s activity to that of customers who have cancelled their policies in the past. For example, if an analytic system flags up a high (or low) number of calls to a helpline as a possible indicator that a customer may soon leave, then effort can be committed to attempting to change that person’s mind. This could be done by offering discounts or lower priced premiums, or, most likely more effectively, by dedicating more customer service time to sorting out that customer’s issues.